for Journals by Title or ISSN
for Articles by Keywords
  Subjects -> ENGINEERING (Total: 2258 journals)
    - CHEMICAL ENGINEERING (190 journals)
    - CIVIL ENGINEERING (177 journals)
    - ELECTRICAL ENGINEERING (99 journals)
    - ENGINEERING (1203 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (60 journals)
    - MECHANICAL ENGINEERING (90 journals)

ENGINEERING (1203 journals)            First | 1 2 3 4 5 6 7 | Last

Showing 201 - 400 of 1205 Journals sorted alphabetically
Current Applied Physics     Full-text available via subscription   (Followers: 4)
Current Science     Open Access   (Followers: 28)
Dams and Reservoirs     Hybrid Journal   (Followers: 3)
Data Handling in Science and Technology     Full-text available via subscription   (Followers: 5)
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 25)
Designed Monomers and Polymers     Hybrid Journal  
Designs, Codes and Cryptography     Hybrid Journal   (Followers: 6)
Development Engineering     Open Access  
Developments in Clay Science     Full-text available via subscription   (Followers: 1)
Developments in Geotechnical Engineering     Full-text available via subscription   (Followers: 4)
Developments in Mineral Processing     Full-text available via subscription   (Followers: 2)
Diálogos Interdisciplinares     Open Access  
Diamond Light Source Proceedings     Full-text available via subscription  
Diffusion Foundations     Full-text available via subscription  
Digital Signal Processing     Hybrid Journal   (Followers: 12)
Discrete Optimization     Full-text available via subscription   (Followers: 5)
Doct-Us Journal     Open Access  
Documents pour l'histoire des techniques     Open Access   (Followers: 1)
Dyes and Pigments     Hybrid Journal   (Followers: 1)
Dyna     Open Access  
Dynamical Systems : An International Journal     Hybrid Journal  
E&S Engineering and Science     Open Access  
El Hombre y la Máquina     Open Access  
Electromagnetics     Hybrid Journal   (Followers: 3)
Electrophoresis     Hybrid Journal   (Followers: 19)
Elementos     Open Access  
Elsevier Geo-Engineering Book Series     Full-text available via subscription   (Followers: 2)
Elsevier Ocean Engineering Series     Full-text available via subscription  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 38)
ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations     Open Access   (Followers: 1)
Energies     Open Access   (Followers: 3)
Energy and Power Engineering     Open Access   (Followers: 16)
Energy Conversion and Management     Hybrid Journal   (Followers: 7)
Energy Engineering     Full-text available via subscription   (Followers: 9)
Energy for Sustainable Development     Hybrid Journal   (Followers: 8)
Energy Procedia     Open Access   (Followers: 2)
Energy Science & Engineering     Open Access   (Followers: 3)
Energy Science and Technology     Open Access   (Followers: 13)
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects     Hybrid Journal   (Followers: 1)
Energy Sources, Part B: Economics, Planning, and Policy     Hybrid Journal   (Followers: 6)
Energy Systems     Hybrid Journal   (Followers: 12)
ENGEVISTA     Open Access   (Followers: 1)
ENGI : Revista Electrónica de la Facultad de Ingenieria     Open Access  
Engineer : Journal of the Institution of Engineers, Sri Lanka     Open Access  
Engineering     Open Access   (Followers: 1)
Engineering & Technology     Hybrid Journal   (Followers: 22)
Engineering : The official journal of the Chinese Academy of Engineering and Higher Education Press     Open Access   (Followers: 1)
Engineering Analysis with Boundary Elements     Hybrid Journal   (Followers: 1)
Engineering Computations     Hybrid Journal   (Followers: 3)
Engineering Economics     Open Access   (Followers: 4)
Engineering Economist, The     Hybrid Journal   (Followers: 6)
Engineering Failure Analysis     Hybrid Journal   (Followers: 64)
Engineering Geology     Hybrid Journal   (Followers: 8)
Engineering International     Open Access  
Engineering Journal     Open Access   (Followers: 1)
Engineering Management Journal     Hybrid Journal   (Followers: 19)
Engineering Management Research     Open Access   (Followers: 6)
Engineering Management Reviews     Open Access   (Followers: 1)
Engineering Optimization     Hybrid Journal   (Followers: 7)
Engineering Science and Technology, an International Journal     Open Access  
Engineering Sciences     Open Access   (Followers: 1)
Engineering Studies     Hybrid Journal  
Engineering With Computers     Hybrid Journal   (Followers: 7)
Engineering, Technology & Applied Science Research     Open Access  
Entramado     Open Access  
Entropy     Open Access   (Followers: 4)
Environmental & Engineering Geoscience     Full-text available via subscription   (Followers: 3)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 6)
Environmetrics     Hybrid Journal  
Épités - Épitészettudomány     Full-text available via subscription   (Followers: 1)
EPJ Photovoltaics     Open Access   (Followers: 3)
Épsilon     Open Access  
Ergonomics in Design: The Quarterly of Human Factors Applications     Hybrid Journal   (Followers: 13)
ESAIM: Control Optimisation and Calculus of Variations     Full-text available via subscription   (Followers: 1)
ESAIM: Mathematical Modelling and Numerical Analysis     Full-text available via subscription   (Followers: 4)
ESAIM: Proceedings     Open Access  
Estuaries and Coasts     Hybrid Journal   (Followers: 17)
European Journal of Combinatorics     Full-text available via subscription   (Followers: 3)
European Journal of Engineering Education     Hybrid Journal   (Followers: 3)
European Journal of Lipid Science and Technology     Hybrid Journal   (Followers: 1)
European Journal of Mass Spectrometry     Full-text available via subscription   (Followers: 16)
European Medical Device Technology     Full-text available via subscription   (Followers: 3)
European Physical Journal - Applied Physics     Full-text available via subscription   (Followers: 7)
European Transport Research Review     Open Access   (Followers: 21)
Evolutionary Intelligence     Hybrid Journal   (Followers: 1)
Evolving Systems     Hybrid Journal  
Exacta     Open Access  
Experimental Techniques     Hybrid Journal   (Followers: 56)
Experiments in Fluids     Hybrid Journal   (Followers: 7)
Fibers and Polymers     Full-text available via subscription   (Followers: 4)
Filtration & Separation     Full-text available via subscription   (Followers: 4)
Finite Fields and Their Applications     Full-text available via subscription   (Followers: 4)
Fire Science Reviews     Open Access   (Followers: 5)
Flexible Services and Manufacturing Journal     Hybrid Journal   (Followers: 1)
Flow, Turbulence and Combustion     Hybrid Journal   (Followers: 22)
Fluid Dynamics     Hybrid Journal   (Followers: 9)
Fluid Dynamics Research     Full-text available via subscription   (Followers: 9)
Fluid Phase Equilibria     Hybrid Journal   (Followers: 4)
Focus on Catalysts     Full-text available via subscription  
Focus on Pigments     Full-text available via subscription   (Followers: 3)
Focus on Powder Coatings     Full-text available via subscription   (Followers: 3)
Focus on Surfactants     Full-text available via subscription   (Followers: 3)
Food Engineering Reviews     Hybrid Journal   (Followers: 3)
Food Science and Technology     Open Access   (Followers: 3)
Formación Universitaria     Open Access   (Followers: 3)
FORMakademisk     Open Access  
Formal Methods in System Design     Hybrid Journal   (Followers: 7)
Forschung     Hybrid Journal  
Forschung im Ingenieurwesen     Hybrid Journal   (Followers: 1)
Foundations and Trends in Systems and Control     Full-text available via subscription  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 7)
Foundations and Trends® in Electronic Design Automation     Full-text available via subscription  
Foundations of Science     Hybrid Journal  
Frontiers in Aerospace Engineering     Open Access   (Followers: 7)
Frontiers in Energy     Hybrid Journal   (Followers: 3)
Frontiers in Geotechnical Engineering     Open Access   (Followers: 2)
Frontiers of Environmental Science & Engineering     Hybrid Journal   (Followers: 4)
Frontiers of Nanoscience     Full-text available via subscription   (Followers: 1)
Fuel and Energy Abstracts     Full-text available via subscription   (Followers: 4)
Fuel Cells     Hybrid Journal   (Followers: 3)
Fuel Cells Bulletin     Full-text available via subscription   (Followers: 4)
Fusion Engineering and Design     Hybrid Journal   (Followers: 9)
Fuzzy Information and Engineering     Open Access   (Followers: 3)
Fuzzy Sets and Systems     Hybrid Journal   (Followers: 4)
Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards     Hybrid Journal   (Followers: 8)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 58)
Geotechnical Testing Journal     Full-text available via subscription   (Followers: 9)
Géotechnique     Hybrid Journal   (Followers: 12)
Geothermics     Hybrid Journal   (Followers: 5)
Glass Technology - European Journal of Glass Science and Technology Part A     Full-text available via subscription   (Followers: 3)
Global Journal of Engineering Research     Full-text available via subscription  
Global Perspective on Engineering Management     Open Access   (Followers: 2)
GPS Solutions     Hybrid Journal   (Followers: 16)
Graphs and Combinatorics     Hybrid Journal   (Followers: 6)
Grass and Forage Science     Hybrid Journal   (Followers: 6)
Great Circle: Journal of the Australian Association for Maritime History, The     Full-text available via subscription   (Followers: 8)
Handai Nanophotonics     Full-text available via subscription  
Handbook of Adhesives and Sealants     Full-text available via subscription   (Followers: 1)
Handbook of Sensors and Actuators     Full-text available via subscription   (Followers: 8)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 3)
Heat Exchangers     Open Access   (Followers: 1)
Heat Transfer - Asian Research     Hybrid Journal   (Followers: 9)
Heat Transfer Engineering     Hybrid Journal   (Followers: 24)
Historical Records of Australian Science     Hybrid Journal   (Followers: 2)
Human Factors in Ergonomics & Manufacturing     Hybrid Journal   (Followers: 5)
IBM Journal of Research and Development     Hybrid Journal   (Followers: 17)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 43)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 34)
IEEE Communications Magazine     Full-text available via subscription   (Followers: 63)
IEEE Control Systems Magazine     Full-text available via subscription   (Followers: 61)
IEEE Engineering Management Review     Full-text available via subscription   (Followers: 33)
IEEE Geoscience and Remote Sensing Letters     Hybrid Journal   (Followers: 56)
IEEE Industry Applications Magazine     Full-text available via subscription   (Followers: 17)
IEEE Instrumentation & Measurement Magazine     Full-text available via subscription   (Followers: 55)
IEEE Journal of Biomedical and Health Informatics     Hybrid Journal   (Followers: 12)
IEEE Journal of Oceanic Engineering     Hybrid Journal   (Followers: 11)
IEEE Journal of Selected Topics in Quantum Electronics     Hybrid Journal   (Followers: 9)
IEEE Journal of Selected Topics in Signal Processing     Hybrid Journal   (Followers: 26)
IEEE Journal of Solid-State Circuits     Full-text available via subscription   (Followers: 20)
IEEE Journal on Selected Areas in Communications     Hybrid Journal   (Followers: 16)
IEEE Latin America Transactions     Full-text available via subscription   (Followers: 2)
IEEE Microwave and Wireless Components Letters     Hybrid Journal   (Followers: 15)
IEEE Microwave Magazine     Full-text available via subscription   (Followers: 28)
IEEE Potentials     Full-text available via subscription   (Followers: 18)
IEEE Signal Processing Letters     Hybrid Journal   (Followers: 33)
IEEE Spectrum     Full-text available via subscription   (Followers: 123)
IEEE Technology and Society Magazine     Full-text available via subscription   (Followers: 4)
IEEE Transactions on Advanced Packaging     Full-text available via subscription   (Followers: 7)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 34)
IEEE Transactions on Applied Superconductivity     Hybrid Journal   (Followers: 4)
IEEE Transactions on Automation Science and Engineering     Full-text available via subscription   (Followers: 11)
IEEE Transactions on Circuits and Systems II: Express Briefs     Hybrid Journal   (Followers: 15)
IEEE Transactions on Components and Packaging Technologies     Full-text available via subscription   (Followers: 15)
IEEE Transactions on Control Systems Technology     Hybrid Journal   (Followers: 40)
IEEE Transactions on Education     Hybrid Journal   (Followers: 7)
IEEE Transactions on Electronics Packaging Manufacturing     Full-text available via subscription   (Followers: 19)
IEEE Transactions on Energy Conversion     Hybrid Journal   (Followers: 11)
IEEE Transactions on Engineering Management     Hybrid Journal   (Followers: 25)
IEEE Transactions on Evolutionary Computation     Hybrid Journal   (Followers: 9)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 16)
IEEE Transactions on Instrumentation and Measurement     Hybrid Journal   (Followers: 48)
IEEE Transactions on Intelligent Transportation Systems     Hybrid Journal   (Followers: 6)
IEEE Transactions on Knowledge and Data Engineering     Hybrid Journal   (Followers: 27)
IEEE Transactions on Magnetics     Hybrid Journal   (Followers: 10)
IEEE Transactions on Microwave Theory and Techniques     Hybrid Journal   (Followers: 23)
IEEE Transactions on Nuclear Science     Hybrid Journal   (Followers: 8)
IEEE Transactions on Plasma Science     Hybrid Journal   (Followers: 7)
IEEE Transactions on Power Delivery     Hybrid Journal   (Followers: 17)
IEEE Transactions on Professional Communication     Hybrid Journal   (Followers: 6)
IEEE Transactions on Reliability     Hybrid Journal   (Followers: 30)
IEEE Transactions on Semiconductor Manufacturing     Hybrid Journal   (Followers: 6)
IEEE Transactions on Signal Processing     Hybrid Journal   (Followers: 58)
IEEE Transactions on Vehicular Technology     Hybrid Journal   (Followers: 2)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 8)
IEEE/ACM Transactions on Computational Biology and Bioinformatics     Hybrid Journal   (Followers: 14)
IERI Procedia     Open Access  
IET Circuits, Devices & Systems     Hybrid Journal   (Followers: 18)
IET Generation, Transmission & Distribution     Hybrid Journal   (Followers: 2)
IET Image Processing     Hybrid Journal   (Followers: 13)
IET Micro and Nano Letters     Hybrid Journal   (Followers: 6)

  First | 1 2 3 4 5 6 7 | Last

Journal Cover AIChE Journal
  [SJR: 1.098]   [H-I: 104]   [27 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0001-1541 - ISSN (Online) 1547-5905
   Published by John Wiley and Sons Homepage  [1598 journals]
  • Particle size effect on the catalyst attrition in a lab‐scale
           fluidized bed
    • Authors: Dongfang Wu; Fanghua Wu, Yongdan Li
      Abstract: Catalysts readily suffer from particle attrition in fluidized beds. In this paper, a commercial FCC catalyst was sieved into several particle‐size intervals to investigate the size effect on particle attrition. It is shown that an exponential decay equation presents a suitable description of attrition and that catalyst attrition is dependent on particle size. Steady‐state specific attrition rate decreases with increasing particle size; however, initial specific attrition rate and decay time parameter change irregularly. For comparison of attrition resistances, a long attrition test is required to reach steady‐state attrition, and the steady‐state specific attrition rate is recommended. It is seen that the smallest particle‐size interval is the most seriously attrited, while the two largest particle‐size intervals are the most attrition‐resistant. Furthermore, weak interactions appear among attrition behaviors of different intervals, and a linear combination method is effective to combine all interval samples to predict the attrition of the original full‐sized sample. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-19T04:05:43.754845-05:
      DOI: 10.1002/aic.15458
  • Scaling of Continuous Twin Screw Wet Granulation
    • Abstract: Scaling rules were developed and tested for a continuous twin screw wet granulation process using three scales (11mm, 16mm and 24mm barrel diameter) of twin screw granulators (TSG). The distributive feed screw (DFS) configuration used produced high porosity granules (50‐60%) with broad bimodal size distributions, especially in the 16mm and 24mm TSGs. Three dimensionless numbers, Froude number (Fr), liquid‐to‐solid ratio (LSR), and powder feed number (PFN), were identified and their effect on granule size distribution, porosity and liquid distribution tested. Granule size increased with increasing LSR as expected. However, Fr and PFN had no significant effect on d10 or d50 and only a small effect on d90. In contrast, granulator scale had a strong effect on granule size distribution, with d90 increasing almost linearly with barrel diameter. This is consistent with breakage of large granules being a dominant mechanism and directly controlled by the geometry of the screw. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-19T04:05:32.353007-05:
      DOI: 10.1002/aic.15459
  • Enhancing liquid micromixing using low‐frequency rotating
    • Abstract: Magnetic nanofluid actuation by rotating magnetic fields was proposed as a high‐performance tool for liquid mixing with enhanced micromixing features. A comparative study was conducted to evaluate the mixing index in T‐type mixers of magnetic and non‐magnetic fluids subject to static (SMF), oscillating (OMF) and rotating (RMF) magnetic fields. RMF excitation unveiled superior mixing indices with strong dependences to magnetic field frequency and content of magnetic nanoparticles. The impact of magnetic field types on micromixing was further examined at low and moderate Re numbers using the Villermaux‐Dushman reaction and IEM micromixing model. The IEM‐inferred micromixing times were remarkably shorter by nearly 4 orders of magnitude in comparison with OMF and SMF excitations, and without magnetic field. The proposed mixing strategy is foreseen to complement innovative microfluidic devices with valuable mixing tools and methods for the diagnosis of the coupling between transport and intrinsic kinetics. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-17T17:50:49.083019-05:
      DOI: 10.1002/aic.15456
  • Thermo‐hydraulic analysis of refinery heat exchangers undergoing
    • Abstract: A complete, systematic approach is presented for the analysis and characterization of fouling and cleaning in refinery heat exchangers. Bringing together advanced thermo‐hydraulic dynamic models, some new formulations, and a method for dynamic analysis of plant data, it allows: extracting significant information from the data; evaluating the fouling state of the units based on thermal measurements and pressure drops, if available; identifying the range of deposit conductivity leading to realistic pressure drops, if pressure measurements are unavailable; estimating key fouling and ageing parameters; estimating the effectiveness of cleaning and surface conditions after a clean; and predicting thermal and hydraulic performance with good accuracy for other periods/exchangers operating in similar conditions. An industrial case study demonstrates the performance prediction in seamless simulations that include partial and total cleanings for over 1000 days operation. The risks of using thermal effects alone and the significant advantages of including pressure drop measurements are highlighted. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-17T17:50:46.204889-05:
      DOI: 10.1002/aic.15457
  • Effect of Bed Characteristics on Local Liquid Spreading in a Trickle Bed
    • Authors: Arpit Jindal; Vivek V. Buwa
      Abstract: Trickle bed reactors are important to several chemical process applications. While the available CFD models can predict overall liquid volume fraction, the prediction of spatial liquid distribution continues to be a challenging task. In the present work, Eulerian multi‐fluid simulations were performed to investigate the effects of particle size, gas and liquid flow rates and bed structure on local liquid spreading and the predictions were validated using measured liquid spreading. It was found that the capillary pressure force caused liquid to spread in the lateral direction and that the interphase interaction forces pushed it in the downward direction and the relative magnitudes of these forces governed the local liquid distribution. While the use of existing capillary pressure force model led to satisfactory prediction of the observed trends of dynamic and steady state local liquid spreading, the modified capillary pressure force led to quantitatively correct predictions of local liquid spreading. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-17T17:50:41.640295-05:
      DOI: 10.1002/aic.15455
  • Current distribution in a rectangular flow channel manufactured by
    • Abstract: The characterization and improvement of the rectangular channel electrolyte flow compartment used in an iron‐air flow battery was carried out by using an arrangement of copper electrodes to measure the current density distribution employing the limiting current technique. The present work addresses the hydrodynamics and mass transport distribution in the compartment and their improvement by an improved electrolyte compartment that results in a more uniform current distribution. The current distribution was evaluated as the ratio between the local and the averaged limiting current densities during the reduction of copper ions over a range of mean linear flow velocity across the electrode surface (2‐30 cm s−1). The initial compartment, showed larger differences between the minimum and maximum currents than the electrolyte compartment that resulted as part of the design process and showed a higher pressure drop at a given mean linear flow velocity. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-17T03:30:39.51741-05:0
      DOI: 10.1002/aic.15454
  • Issue information
    • Abstract: Cover illustration. On the left is the Sargent‐Gaminibandara superstructure for the synthesis of a thermally integrated columns for the separation of four components: A,B,C,D. Below is the general mathematical formulation of a nonlinear optimization problem (nonlinear programming) that was used to optimize such a superstructure. On the right is a diagram of the State‐Task‐Network by Kondili, Pantelides and Sargent for the scheduling of batch operations. Above are the differential‐algebraic equations for modeling the dynamics of one of the units. Below are mixed‐integer linear equations that are part of the optimization model for the scheduling problem. Credit for design of the cover: Andrew Grossmann. 10.1002/aic.15423
      PubDate: 2016-08-15T13:48:51.362568-05:
      DOI: 10.1002/aic.14997
  • Aerosol Analysis of Residual and Nanoparticle Fractions from Spray
           Pyrolysis of Poorly Volatile Precursors
    • Abstract: The quality of aerosol‐produced nanopowders can be impaired by micron‐sized particles formed due to non‐uniform process conditions. Methods to evaluate the quality reliably and fast, preferably on‐line, are important at industrial scales. Here, aerosol analysis methods are used to determine the fractions of nanoparticles and micron‐sized residuals from poorly volatile precursors. This is accomplished by using aerosol instruments to measure the number and mass size distributions of Liquid Flame Spray‐generated alumina and silver particles produced from metal nitrates dissolved in ethanol and 2‐ethylhexanoic acid (EHA). The addition of EHA had no effect on silver, whereas, 5\% EHA concentration was enough to shift the alumina mass from the residuals to nanoparticles. The size‐resolved aerosol analysis proved to be an effective method for determining the product quality. Moreover, the used on‐line techniques alone can be used to evaluate the process output when producing nanopowders, reducing the need for tedious off‐line analyses. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-11T23:40:36.689005-05:
      DOI: 10.1002/aic.15449
  • A Positron Emission Particle Tracking investigation of the scaling law
           governing free surface flows in tumbling mills
    • Authors: I. Govender; M. C. Richter, D. N. De Klerk, A. N. Mainza
      Abstract: Positron Emission Particle Tracking (PEPT) measurements are used to track the flow of d = 5mm glass beads within a rotating drum fitted with (and without) lifter bars and operated in the cascading and cataracting Froude regimes. After converting the Lagrangian trajectories of a representative radio‐labelled glass bead (the tracer) into Eulerian fields under the ergodic assumption, the bed shape and kinematics are extracted for steady, fully developed flow conditions. Notwithstanding the azimuthal wall effects introduced by the lifter bars, we show a linear scaling 〈v〉∝h of the local flowing layer thickness h with local depth‐averaged velocity 〈 v 〉and a constant average shear 〈γ̇〉∼0.6gd for direct measurements spanning the entire flowing layer (not just the central region), and high Froude regimes (cascading and cataracting) not previously investigated by scaling analysis in the literature. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-11T23:40:34.187218-05:
      DOI: 10.1002/aic.15453
  • Thermodynamic Analysis and Optimization of RWGS Processes for Solar Syngas
           Production from CO2
    • Abstract: Process systems were investigated for syngas production from CO2 and renewable energy (solar) by the reverse water‐gas shift (RWGS) and the reverse water‐gas shift chemical looping (RWGS‐CL) process. Thermodynamic analysis and optimization was performed to maximize the solar‐to‐syngas (StS) efficiency ηStS. Special emphasis was laid on product gas separation. For RWGS‐CL, a maximum StS efficiencies of 14.2 and 14.4% were achieved without and with heat integration, respectively. The StS efficiency is dictated by the low overall efficiency of H2 production. RWGS‐CL is most beneficial for the production of pure CO, where the StS efficiency is one percent point higher compared to that of the RWGS process with heat integration. Heat integration leads to significant reductions in external heat demand since most of the gas phase process heat can be integrated. The StS efficiencies for RWGS and RWGS‐CL achieve the same level as the reported values for solar thermochemical syngas production. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-11T03:45:57.466224-05:
      DOI: 10.1002/aic.15445
  • Engineering the outermost layers of TiO2 nanoparticles using in situ Mg
           doping in a flame aerosol reactor
    • Authors: Yanjie Hu; Yang Wang, Hao Jiang, Yunfeng Li, Theodore Cohen, Yi Jiang, Binqi Wang, Ling Zhang, Pratim Biswas, Chunzhong Li
      Abstract: Titanium dioxide nanoparticles with disordered outermost layer sturctures have significantly enhanced light absorption and photocatalytic properties and thus receiving enhanced attention in recent years. Engineering the outermost layers using in situ magnesium doping to tailor the band‐edge of TiO2 nanoparticles was achieved via a flame aerosol reactor (FLAR). We proposed that the distribution of doped elements in nanoparticles could be controlled in a high temperature flame process, and which could be predicted by the comparison of different characteristic time scales, such as reaction time, coagulation time, and sintering time. In situ magnesium doping on the outermost layers effectively tailored the conduction band and electron structure of the TiO2 nanoparticles, and simultaneously improved the maximum photocurrent as well as the maximum photovoltage in dye‐sensitized solar cells (DSSCs). These improvements were largely attributed to red‐shifted light absorption, and rapid photoelectron injection into the conduction band. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-10T18:20:29.866949-05:
      DOI: 10.1002/aic.15451
  • Understanding and Optimization of Chemical Reactor Performance for Bimodal
           Reaction Sequences
    • Authors: J. Poissonnier; J.W. Thybaut, G.B. Marin
      Abstract: The relative contributions of heterogeneously catalyzed and homogeneous bulk phase reactions in bimodal reaction sequences have been assessed via 1D reactor simulations. Starting from a reaction network only comprising 2 parallel, irreversible heterogeneously catalyzed and homogeneous bulk phase steps, complementary consecutive steps were included with the option of being reversible. The final product formed after a minimum number of homogeneous bulk phase reactions is obtained with high yields in continuous flow fixed bed reactors. The products obtained after a higher number of homogeneous bulk phase reactions generally dominate in slurry reactors. Yields of the latter may exhibit an optimum as a function of the catalyst amount in the reactor. The adsorption enthalpies of the intermediates in the reaction network critically determine the position and shape of this maximum. The reversibility of the homogeneous bulk phase steps provides specific opportunities to tune the product yields in bimodal reaction sequences. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-10T18:07:53.989404-05:
      DOI: 10.1002/aic.15448
  • Novel Operability‐based Approach for Process Design and
           Intensification: Application to a Membrane Reactor for Direct Methane
    • Authors: Juan C. Carrasco; Fernando V. Lima
      Abstract: This paper introduces a novel operability‐based approach for process design and intensification of energy systems described by nonlinear models. This approach is applied to a membrane reactor (MR) for the direct methane aromatization (DMA) conversion to benzene and hydrogen. The proposed method broadens the scope of the traditional path of the operability approaches for design and control, mainly oriented to obtain the achievable output set (AOS) from the available input set (AIS), and compare the computed AOS to a desired output set (DOS). In particular, an optimization algorithm based on nonlinear programming tools is formulated for the calculation of the desired input set (DIS) that is feasible considering process constraints and intensification targets. Results on the application of the operability method as a tool for process intensification show reduction of the DMA‐MR footprint (≈ 77% reactor volume and 80% membrane area reduction) for an equivalent level of performance, when compared to the base case. This case study indicates that the novel approach can be a powerful tool for process intensification of membrane reactors and other complex chemical processes. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:52:37.69587-05:0
      DOI: 10.1002/aic.15439
  • Rheology of Cubic Particles in a Concentrated Colloidal Dispersion
           Suspending Medium
    • Authors: Colin D. Cwalina; Kelsey J. Harrison, Norman J. Wagner
      Abstract: The flow behavior of mixtures of micron‐sized cubic particles suspended in a concentrated colloidal dispersion is investigated across a broad range of cubic particle concentrations. In the semi‐dilute regime, the qualitative shape of the dynamic moduli and flow curves reflect those of the underlying colloidal dispersion medium. These curves are superimposed with the underlying colloidal dispersion using shift factors that are found to be larger than those obtained in a recent study of suspensions of non‐colloidal spherical particles in the same colloidal dispersion medium. At higher concentrations of cubic particles, deviations from this shifting procedure are apparent. Scaling calculations suggest depletion interactions are responsible for the increase in the low shear viscosity and confinement of the underlying colloidal dispersion can be expected to enhance the shear thickening behavior at high shear stresses. The results of this study provide guidance for formulating suspensions through control of particle shape and mixture concentration. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:48:12.810658-05:
      DOI: 10.1002/aic.15443
  • Slot coating flows of non‐colloidal particle suspensions
    • Authors: L. D. Valdez Silva; D. M. Campana, M. S. Carvalho
      Abstract: Slot coating is used in the manufacturing of functional films, which rely on specific particle microstructure to achieve the desired performance. Final structure on the coated film is strongly dependent on the suspension flow during the deposition of the coating liquid and on the subsequent drying process. Fundamental understanding on how particles are distributed in the coated layer enables optimization of the process and quality of the produced films. The complex coating flow leads to shear‐induced particle migration and non‐uniform particle distribution. We study slot coating flow of non‐colloidal suspensions by solving the mass and momentum conservation equations coupled with a particle transport equation using the Galerkin/Finite element method. The results show that particle distribution in the coating bead and in the coated layer is non‐uniform and is strongly dependent on the imposed flow rate (wet thickness). This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:48:11.670722-05:
      DOI: 10.1002/aic.15444
  • Adsorptive Cyclic Purification Process for CO2 Mixtures Captured from Coal
           Power Plants
    • Abstract: CO2 capture technology combined with bulk separation and purification processes has become an attractive alternative to reduce capture costs. Furthermore, the required purity in the application for CO2 conversion and utilization is more stringent than that required from a captured CO2 mixture for geological storage. In this study, an adsorptive cyclic purification process was developed to upgrade a CO2/N2 mixture captured from greenhouse gas emission plants as a feasibility study for a second capture unit or captured CO2 purifier. To purify 90% CO2 with balance N2 as a captured gas mixture, two‐bed PSA and PVSA processes using activated carbon were experimentally and theoretically studied at adsorption pressures of 250 to 650 kPa and a fixed vacuum pressure of 50 kPa. CO2 with higher than 95% purity was produced with more than 89% recovery. However, a four‐bed PVSA process could successfully produce CO2 with greater than 98% purity and 90% recovery. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:48:10.55249-05:0
      DOI: 10.1002/aic.15440
  • Review of the Important Challenges and Opportunities related to Modeling
           of Mammalian Cell Bioreactors
    • Authors: Parham Farzan; Biren Mistry, Marianthi G. Ierapetritou
      Abstract: Industrialization of mammalian cell culture has been achieved by integrating knowledge from several applying core concepts of chemical engineering, cellular and molecular biology, and biochemistry. Modeling has been applied to biological and physical processes to gain additional insights into such processes. This paper covers modeling of the bioreactor and metabolic processes as it applies to bioprocess. Hydrodynamics of a bioreactor is briefly described while additional focus is given to gas‐liquid mass transfer. Biological modeling is presented in the order of increasing complexity. First steady state models are presented followed by dynamic models, cybernetic models and finally bioreactor integrated models. The closing discussion summarizes challenges of implementation of model‐based approaches in the biopharmaceutical industry. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:48:04.40111-05:0
      DOI: 10.1002/aic.15442
  • In‐situ adaptive tabulation for the CFD simulation of heterogeneous
           reactors based on operator‐splitting algorithm
    • Authors: Mauro Bracconi; Alberto Cuoci, Matteo Maestri
      Abstract: We apply the In‐Situ Adaptive Tabulation algorithm to efficiently solve the chemical sub‐step in the context of the simulation of heterogeneous reactors. A numerical strategy ‐ specifically conceived for unsteady simulation of catalytic devices ‐ has been developed and interfaced in the context of the operator splitting technique with the solution of the chemical sub‐step, which requires 70%‐90% of the total computational time. The algorithm performances have been illustrated by considering a single channel of a honeycomb reactor operating the catalytic partial oxidation of methane and a methane steam reforming packed bed reactor. We found out that the application of ISAT resulted in a speed‐up of the chemical step up to ∼500 times with an overall speed‐up of ∼5‐15 times for the whole simulation. Such reduction of the computation effort is key to make affordable fundamental CFD simulations of chemical reactors at a level of complexity relevant to technological applications. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:47:40.601711-05:
      DOI: 10.1002/aic.15441
  • Continuous Reactive Crystallization of Pharmaceuticals Using Impinging Jet
    • Authors: Wen J. Liu; Cai Y. Ma, Jing J. Liu, Yang Zhang, Xue Z. Wang
      Abstract: For reactive crystallization of pharmaceuticals that show a rapid reaction rate, low solubility of active pharmaceutical ingredient and hence a large supersaturation, it was found in a recent study that a process design which integrates an impinging jet mixer and batch stirred tank produces high quality crystals. The current investigation examines if the short processing time of reactive crystallization permits the impinging jet mixer ‐ stirred tank design to be modified to operate in a continuous mode. The new design combines an impinging jet mixer for feed introduction and reaction with a continuous stirred tank reactor (CSTR) and tubular reactor for crystal growth. A study of reactive crystallization of sodium cefuroxime (an antibiotic), using firstly a 1L CSTR then scaling to a 50L CSTR, found that the new design produces crystals of higher crystallinity, narrower particle size, and improved product stability, than batch crystallizers. This article is protected by copyright. All rights reserved.
      PubDate: 2016-08-02T03:41:22.836284-05:
      DOI: 10.1002/aic.15438
  • Particle Dynamics and Relaxation in Bimodal Suspensions during Drying
           Using Multi‐speckle Diffusing Wave Spectroscopy
    • Authors: Gwi Jeong Oh; Ji Won Hwang, Seong Jae Lee, Ki Wan Bong, Hyun Wook Jung
      Abstract: The motion of polystyrene particles in a bimodal suspension drop during drying was characterized via multi‐speckle diffusing wave spectroscopy. The fast and slow dynamics of bimodal particles, which were expressed in terms of autocorrelation function data from two kinds of cameras, were well connected in short and long lag time regimes. Characteristic time of β‐relaxation, representing the rapid movement of bimodal particles, became lower in the short lag time region as the portion of small particles increased, reflecting their fast Brownian motion. The difference in the relaxation features between bimodal suspension with large and small particles and unimodal suspension with only large particles became more evident as the size ratio between particles was high. Drying temperature could encourage the particle movement at the early stages of drying, leading to lower relaxation time, and inversely retard the relaxation behavior when drying time further elapsed, due to the structural rearrangement of particles. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-23T03:25:32.064819-05:
      DOI: 10.1002/aic.15437
  • A Water Droplet Size Distribution Dependent Modeling of Hydrate Formation
           in Water/Oil Emulsion
    • Abstract: Experimental data on chord length distributions and growth rate during methane hydrate formation in water‐in‐oil emulsions were obtained in a high pressure stirring reactor using FBRM and PVM. The experiments were carried out at 274.2 K for 10%‐30% water cuts and agitation rates ranging from 200 to 500 rpm initially at 7.72 MPa. Rapid growth was accompanied by gradually decrease in rate. Free water was observed to become depleted during rapid growth while some water remained encapsulated inside hydrate layers constituting a mass transfer barrier. The apparent kinetic constants of methane hydrate formation and free‐water fractions were determined using a newly developed kinetic model independent of the dissolution rate at the gas‐oil interface. It was illustrated that continued growth depends on distribution and transfer of water in oil‐dominated systems. This perception accords with observations of hydrate film growth on suspended water droplet in oil and clarifies transfer limits in kinetics. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-23T03:25:31.068071-05:
      DOI: 10.1002/aic.15436
  • Identification of Cell‐Nucleation Mechanism in Foam Injection
           Molding with Gas‐counter Pressure via Mold Visualization
    • Authors: Vahid Shaayegan; Guilong Wang, Lun Howe Mark, Chul B. Park
      Abstract: The mechanisms of cell nucleation and growth are investigated in foam injection molding using gas‐counter pressure (GCP). An in‐situ mold visualization technique is employed. The application of GCP suppresses cell nucleation, and prevents the blowing agent from escaping during mold‐filling. The inherent structural heterogeneity in the regular foam injection molding can be improved because of the uniform cavity pressure when employing GCP. The cavity pressure profiles show much faster pressure‐drop rates using GCP, because the single‐phase polymer/gas mixture has a lower compressibility than the two‐phase polymer/bubble mixture. Therefore, both the cell nucleation and growth rates are significantly increased through a higher pressure‐drop rate upon the removal of the GCP. The effect of GCP magnitude on the cell morphology is explored. When the GCP is lower than the solubility pressure, bimodal foaming occurs. As the GCP increases above the solubility pressure, the cell density increases because of the higher pressure‐drop rate. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-23T02:50:38.033947-05:
      DOI: 10.1002/aic.15433
  • Experimental operation of a reactive dividing wall column and comparison
           with simulation results
    • Authors: Christoph Ehlers; Torben Egger, Georg Fieg
      Abstract: Reactive dividing wall columns (RDWC) are a special type of distillation column that allow for the targeted realization of chemical reactions and the separation into multiple product fractions in one shell. However, despite their huge economical and ecological potentials for certain fields of application, this innovative technology has not found its way into industrial production processes yet. The very limited availability of experimental research studies verifying the prediction capabilities of respective modeling concepts for this type of distillation column might be one decisive reason for that. Therefore, the present study puts its focus on the detailed comparison between experimental operation of RDWC and the corresponding simulation results for steady‐state. For the first time, the mentioned comparison is carried out for a chemical system with non‐negligible side reactions. It is shown that even for this highly complex system, the mathematical model is capable of predicting the column operation. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-20T18:10:23.105795-05:
      DOI: 10.1002/aic.15435
  • Krypton‐Xenon Separation Properties of SAPO‐34 Zeolite
           Materials and Membranes
    • Authors: Yeon Hye Kwon; Christine Kiang, Emily Benjamin, Phillip Crawford, Ramesh Bhave, Sankar Nair
      Abstract: Separation of the radioisotope 85Kr from 136Xe is an important target during used nuclear fuel recycling. We report a detailed study on the Kr and Xe adsorption, diffusion, and membrane permeation properties of the silicoaluminophosphate zeolite SAPO‐34. Adsorption and diffusion measurements on SAPO‐34 crystals indicate their potential for use in Kr‐Xe separation membranes, but also highlight competing effects of adsorption and diffusion selectivity. SAPO‐34 membranes are synthesized on α−alumina disk and tubular substrates via steam assisted conversion (SAC) seeding and hydrothermal growth, and are characterized in detail. Membrane transport measurements reveal that SAPO‐34 membranes can separate Kr from Xe by molecular sieving, with Kr permeabilities around 50 Barrer and mixture selectivity of 25‐30 for Kr at ambient or slight sub‐ambient conditions. The membrane transport characteristics are modeled by the Maxwell‐Stefan equations, whose predictions are in very good agreement with experiment and confirm the minimal competing effects of adsorption and diffusion. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-20T10:30:37.513337-05:
      DOI: 10.1002/aic.15434
  • Adsorption of iodine on hydrogen‐reduced silver‐exchanged
           mordenite: Experiments and modelling
    • Authors: Yue Nan; David W. DePaoli, Lawrence L. Tavlarides
      Abstract: The adsorption process of iodine, a major volatile radionuclide in the off‐gas streams of spent nuclear fuel reprocessing, on hydrogen‐reduced silver‐exchanged mordenite (Ag0Z) was studied at the micro‐scale. The gas‐solid mass transfer and reaction involved in the adsorption process were investigated and evaluated with appropriate models. Optimal conditions for reducing the silver‐exchanged mordenite (AgZ) in a hydrogen stream were determined. Kinetic and equilibrium data of iodine adsorption on Ag0Z were obtained by performing single‐layer adsorption experiments with experimental systems of high precision at 373 – 473 K over various iodine concentrations. Results indicate approximately 91% to 97% of the iodine adsorption was through the silver‐iodine reaction. The effect of temperature on the iodine loading capacity of Ag0Z was discussed. The Shrinking Core model describe the data well, and the primary rate controlling mechanisms were macro‐pore diffusion and silver‐iodine reaction. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-14T18:32:20.989268-05:
      DOI: 10.1002/aic.15432
  • A Tribute to Roger Sargent
    • Authors: Ignacio E. Grossmann; Michael F. Doherty, Michael P. Harold
      PubDate: 2016-07-14T09:05:39.440547-05:
      DOI: 10.1002/aic.15423
  • Synthesizing bromobutyl rubber by a microreactor system
    • Authors: Pei Xie; Kai Wang, Peijian Wang, Yang Xia, Guangsheng Luo
      Abstract: Bromobutyl rubber (BIIR) is an important synthetic rubber with better vulcanizing behavior than traditional butyl rubber (IIR). It is hard to synthesize for the high reactant viscosity and strong corrosion caused by Br2 and HBr. A microreactor platform was developed to solve the corrosion problem with cheap materials and obtain high quality BIIR based on microscaled mixing. The results showed that low reaction temperature and quickly eliminating HBr from the reacting solution were crucial to obtain high selectivity of demanded molecule structure and prevent polymer from decomposition. Owing to the corrosion resistance ability, a water assistant technology was successfully implemented in the microreactor system, which produced high quality BIIR with almost 100% selectivity and less reduced molecule weight. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T18:45:24.516304-05:
      DOI: 10.1002/aic.15431
  • A new optimization model and a customized solution method for natural gas
           production network design and operation
    • Authors: Dan Li; Xiang Li
      Abstract: This paper proposes to tackle integrated design and operation of natural gas production networks under uncertainty, using a new two‐stage stochastic programming model, a novel reformulation strategy, and a customized global optimization method. The new model addresses material balances for multiple key gas components, pressure flow relationships in gas wells and pipelines, and compressor performance. This model is a large‐scale nonconvex mixed‐integer nonlinear programming problem that cannot be practically solved by existing global optimization solvers or decomposition‐based optimization methods. With the new reformulation strategy, the reformulated model has a better decomposable structure, and then a new decomposition‐based global optimization method is developed for efficient global optimization. In the case study of an industrial naturals production system, it is shown that the proposed modeling and optimization methods enable efficient solution, and the proposed optimization method is faster than a state‐of‐the‐art decomposition method by at least an order of magnitude. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T17:55:52.225316-05:
      DOI: 10.1002/aic.15428
  • Error‐triggered on‐line model identification for
           model‐based feedback control
    • Authors: Anas Alanqar; Helen Durand, Panagiotis D. Christofides
      Abstract: In industry, it may be difficult in many applications to obtain a first‐principles model of the process, in which case a linear empirical model constructed using process data may be used in the design of a feedback controller. However, linear empirical models may not capture the nonlinear dynamics over a wide region of state‐space and may also perform poorly when significant plant variations and disturbances occur. In the present work, an error‐triggered on‐line model identification approach is introduced for closed‐loop systems under model‐based feedback control strategies. The linear models are re‐identified on‐line when significant prediction errors occur. A moving horizon error detector is used to quantify the model accuracy and to trigger the model re‐identification on‐line when necessary. The proposed approach is demonstrated through two chemical process examples using a model‐based feedback control strategy termed Lyapunov‐based economic model predictive control (LEMPC). The chemical process examples illustrate that the proposed error‐triggered on‐line model identification strategy can be used to obtain more accurate state predictions to improve process economics while maintaining closed‐loop stability of the process. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T17:55:49.258028-05:
      DOI: 10.1002/aic.15430
  • Improving the operational stability of the multi‐chamber
           spout‐fluid bed via the insertion of a submerged partition plate
    • Authors: Shiliang Yang; Yuhao Sun, Liangqi Zhang, Jia Wei Chew
      Abstract: The effect of a submerged partition plate on improving the gas‐solid flow robustness and stability in a three‐dimensional spout‐fluid bed with multiple inter‐connected chambers is numerically investigated by means of computational fluid dynamics coupled with discrete element method (CFD‐DEM). Notably, multiple‐chamber beds are necessary in scaling up the spout‐fluid bed. The influence of plate height on gas‐solid distribution, spout‐annulus interaction and chamber interaction are also studied to optimize the design. The results demonstrate that inserting a partition plate with height above a certain threshold can effectively improve the stability of spouting and uniformly re‐distribute the flux load in each chamber, giving rise to parallel fountains and lower circulation flux of the solid phase. Results indicate that the plate height should be at least 80% of the packed bed height investigated, with the most optimal being about 92% based on steady spouting, and the maximum solid and gas exchanging fluxes between the chambers. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T17:55:47.909722-05:
      DOI: 10.1002/aic.15427
  • Structure‐based model for prediction of electrical conductivity of
           pure ionic liquids
    • Abstract: A structure‐based method was proposed to estimate the electrical conductivity of ionic liquids covering wide ranges of temperature (238.15‐484.1 K) and electrical conductivity (0.0001524‐19.3 S/m) based on experimental data collect from literature from 1998 to 2015. The influences of temperature and ion structure on electrical conductivity were also discussed. The mean absolute percentage error between the calculated and literature data was 6.02%, with 6.12% for the training set (1978 data points, 177 ILs) and 5.10% for the test set (217 data points, 11 ILs). This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T17:55:45.298651-05:
      DOI: 10.1002/aic.15429
  • Simulation of dry powder inhalers: Combining micro‐scale,
           meso‐scale and macro‐scale modeling
    • Abstract: The flow of carrier particles, coated with active drug particles, is studied in a prototype dry powder inhaler. A novel, multi‐scale approach consisting of a discrete element model (DEM) to describe the particles coupled with a dynamic large eddy simulation (LES) model to describe the dynamic nature of the flow is applied. The model consists of three different scales: the micro‐scale, the meso‐scale and the macro‐scale. At the micro‐scale, the interactions of the small active drug particles with larger carrier particles, with the wall, with the air flow, and with each other is thoroughly studied using discrete element modelling and detailed computational fluid dynamics (CFD), i.e resolving the flow structures around the particles. This has led to the development of coarse‐grained models, describing the interaction of the small active drug particles at the larger scales. At the meso‐scale the larger carrier particles, and all of their interactions are modelled individually using DEM and CFD‐LES. Collisions are modeled using a visco‐elastic model to describe the local deformation at each point of particle‐particle contact in conjunction with a model to account for cohesion. At the macro‐scale, simulations of a complete prototype inhaler are carried out. By combining the relevant information of each of the scales, simulations of the inhalation of one dose from a prototype inhaler using a patient relevant air flow profile show that fines leave the inhaler faster than the carrier particles. The results also show that collisions are not important for particle‐particle momentum exchange initially but become more important as the particles accelerate. It is shown that for the studied prototype inhaler the total release efficiency of the fine particles is between 10% and 30%, depending on the Hamaker constant, using typical settings for the properties of both particles. The results are also used to study regions of recirculation, where carrier particles can become trapped, and regions where fines adhere to the wall of the device. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-13T17:55:41.430245-05:
      DOI: 10.1002/aic.15424
  • A tribute to professor roger sargent: Intellectual leader of process
           systems engineering
    • Authors: Michael F. Doherty; Ignacio E. Grossmann, Costas Pantelides
      PubDate: 2016-07-12T21:25:22.189365-05:
      DOI: 10.1002/aic.15425
  • Mathematical Simulation of Wet Spinning Coagulation Process: Dynamic
           Modeling and Numerical Results
    • Authors: Nan Xu; Yongsheng Ding, William E. Schiesser, Mayuresh V. Kothare
      Abstract: In this paper, a dynamic model of polymer wet spinning coagulation process is proposed. The model is built based on the double diffusion phenomenon, phase separation process, continuity balance, and momentum balance of the entire coagulation process. The uniqueness of the model lies in its dynamic feature. The model can simulate the system's dynamic response to any variation in system inputs/parameters. Steady‐state system solutions can also be produced as the long‐time solutions of the dynamic model; a settling time can be observed at the same time. This paper employs a computationally efficient method of lines (MOL) numerical algorithm for solving the dynamic model. A simulation experiment on a selected non‐solvent‐solvent‐polymer ternary system is carried out to verify the model as well as the numerical method. The dynamic simulation results are analyzed and discussed. At the end of the paper, h‐refinement and p‐refinement are used to confirm the spatial convergence of the numerical solutions. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-12T21:20:22.948584-05:
      DOI: 10.1002/aic.15426
  • Experimentally‐based constitutive relations for co‐current
           gas‐liquid flow in randomly packed beds
    • Authors: Paul Salgi; Vemuri Balakotaiah
      Abstract: Experimental Observations on average pulse velocity and frequency in concurrent gas‐liquid (down) flow through randomly packed beds are used to extract constitutive relations for the gas‐liquid interaction and mean curvature terms that appear in a recently proposed volume‐averaged two‐fluid model for bubbly flow. The proposed closures lead to a reasonably quantitative prediction of the average pressure drop and liquid saturation under bubbly flow conditions and in the near pulse regime. In addition, the proposed closures provide realistic estimates for the location of the bubble‐to‐pulse transition in microgravity and in 1g down‐flow and predict the disappearance of the bubbly flow pattern at low liquid fluxes in 1g down‐flow. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-07-11T09:40:32.956248-05:
      DOI: 10.1002/aic.15377
  • Physical mixtures as simple and efficient alternative to alloy carriers in
           chemical looping processes
    • Abstract: Chemical looping combustion is a clean combustion technology for fossil or renewable fuels. In a previous demonstration, chemical looping was applied to CO2 activation via reduction to CO with concurrent production of synthesis gas (CO + H2) from CH4 via rationally designed Fe‐Ni alloys. Here, it is demonstrated that that a simple physical mixture can even outperform the equivalent alloy based on an intricate gas phase mediated coupling between the two metals: Ni cracks methane to carbon and H2. The latter then reduces iron oxide carrier, forming steam, which gasifies the carbon deposits on Ni to produce a mixture of CO + H2, thus regenerating the active Ni surface. It was suggested that the principle demonstrated here—the gas phase‐mediated coupling of two solid reactants with distinct functionalities—should be applicable broadly toward oxidation reactions and hence opens a new avenue for rational design of chemical looping processes. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-07-11T09:30:25.029797-05:
      DOI: 10.1002/aic.15380
  • Modeling Study for the Effect of Particle Size on Char Gasification with
    • Authors: Zhongjie Shen; Jianliang Xu, Haifeng Liu, Qinfeng Liang
      Abstract: This study applied a high temperature stage microscope to investigate the temperature effect caused by particle size on char gasification. Experiments were carried out with different particle sizes for raw chars and chars on molten slag surface, respectively. Heat transfer models were built for the raw char of two temperature distributions and char particle on molten slag, respectively. Results showed that reaction layer temperature of raw char decreased in the reaction dominant while char on molten slag had higher temperature. Temperature difference between two distributions increased with the initial particle size, indicating the temperature effect on large particles was obvious. Shrinking core model was applied and modified herein coupled with the modification of reaction layer temperature and reaction area. Model prediction and experimental data showed good agreements of carbon conversion and reactivity index for raw char and char on molten slag, respectively. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:30:56.517164-05:
      DOI: 10.1002/aic.15417
  • Improved predictions of alarm and safety system performance through
           process and operator response‐time modeling
    • Authors: Ian H. Moskowitz; Warren D. Seider, Jeffrey E. Arbogast, Ulku G. Oktem, Ankur Pariyani, Masoud Soroush
      Abstract: Dynamic risk analysis (DRA) has been used widely to analyze the performance of alarm and safety interlock systems of manufacturing processes. Because the most critical alarm and safety interlock systems are rarely activated, little or no data from these systems are often available to apply purely‐statistical DRA methods. Moskowitz et al. (2015)1 introduced a repeated‐simulation, process‐model‐based technique for constructing informed prior distributions, generating low‐variance posterior distributions for Bayesian analysis1, and making alarm‐performance predictions. This paper presents a method of quantifying process model quality, which impacts prior and posterior distributions used in Bayesian Analysis. The method uses higher‐frequency alarm and process data to select the most relevant constitutive equations and assumptions. New data‐based probabilistic models that describe important special‐cause event occurrences and operators' response‐times are proposed and validated with industrial plant data. These models can be used to improve estimates of failure probabilities for alarm and safety interlock systems. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:26:08.315423-05:
      DOI: 10.1002/aic.15419
  • Resolved‐particle Fixed Bed CFD with Microkinetics for Ethylene
    • Authors: Behnam Partopour; Anthony G. Dixon
      Abstract: The incorporation of an ethylene oxidation microkinetic model into fixed‐bed CFD is studied using two different approaches. The first is based on mapping pre‐calculated reaction rates into quadratic splines under steady‐state conditions without any further assumptions or simplification of the elementary steps. The second approach uses conventional reaction engineering assumptions such as quasi‐equilibrium (QE) and hybrid steady state (HSS) to reduce the kinetic model and generate lumped rate expressions. Both kinetic models are implemented for illustrative resolved‐particle CFD simulations in a randomly packed bed of 120 spheres. It is shown that the QE and HSS assumptions are not valid throughout the range of reacting conditions. Comparison of the temperature and species profiles for these two approaches shows that the strong gradients inside the bed cause significant deviations in the reduced model compared to using the splines method with full microkinetics, which produces accurate results without increasing the computational time. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:25:38.199862-05:
      DOI: 10.1002/aic.15422
  • Bicriteria Optimization Approach to Analyze Incorporation of Biofuel and
           Carbon Capture Technologies
    • Abstract: Environmental considerations has become a central issue in the process industries. The energy sector attracts the majority of attention, since it is responsible from 83% of anthropogenic greenhouse gas emissions. Although the renewable energy technologies are surging, fossil fuels are expected to continue dominating the sector for the next decades. Therefore, it is important to analyze the performance of emerging technologies that can be integrated into existing facilities, such as biofuels and carbon capture and storage technologies. In this paper, we present a multi‐period bicriteria optimization model that represents traditional cogeneration processes and integrate biodiesel and CCS technologies. Then, the efficient set for the problem is obtained by using a novel two‐phase solution method. The results show that the modeling approach is effective in identifying the set of efficient solutions for the integration strategies of biodiesel and CCS technologies. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:25:29.129296-05:
      DOI: 10.1002/aic.15421
  • Influence of Catalyst Pore Network Structure on the Hysteresis of
           Multiphase Reactions
    • Abstract: The effects of the catalyst pore network structure on multiphase reactions in catalyst pellets are investigated by using the experimentally validated pore network model proposed in our recent work (AIChE J. 2016, 62, 451). The simulations display hysteresis loops of the effectiveness factor. The hysteresis loop area becomes significantly larger, when having small volume‐averaged pore radius, wide pore size distribution, and low pore connectivity; however, the loop area is insensitive to pellet size, even though it affects the value of the effectiveness factor. The hysteresis loop area is also strongly affected by the spatial distribution of the pore size, in particular for a bimodal pore size distribution. The pore network structure directly influences mass transfer, capillary condensation, and pore blocking, and subsequently passes these influences on to the hysteresis loop of the effectiveness factor. Recognizing these effects is essential when designing porous catalysts for multiphase reaction processes. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:20:53.108119-05:
      DOI: 10.1002/aic.15415
  • A Simple Model for Predicting Solid Concentration Distribution in
           Binary‐solid Liquid Fluidised Beds
    • Authors: Zhengbiao Peng; Behdad Moghtaderi, Elham Doroodchi
      Abstract: A simple mathematical model for predicting the solid concentration profile in binary‐solid liquid fluidised beds is presented. The main assumption is that the solid concentration distribution follows the logistic function, which is supported by the literature. Various equations have been derived to solve key system quantities (e.g., bed expansion height, length and position of the transition zone). In contrast to previous models that often involve adjustable parameters and strongly rely on the availability of experimental data, the present model only requires inputs of fluid and particle properties, operating conditions and correlations for dispersion and slip velocity. The results showed that the model is applicable to different binary‐solid systems that have size and/or density differences. The model's capability of predicting the layer inversion phenomenon has also been demonstrated. The model is simple but proves capable of accurately predicting key information for the design, operation and scale up of liquid fluidised beds. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:20:37.772202-05:
      DOI: 10.1002/aic.15420
  • Operational Strategy and Planning for Raw Natural Gas Refining Complexes:
           Process Modeling and Global Optimization
    • Authors: B. J. Zhang; Q. L. Chen, Jie Li, C. A. Floudas
      Abstract: Optimal operational strategy and planning of a raw natural gas refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this paper, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple gas feedstocks and different product specifications. Then, we develop a large‐scale nonconvex mixed‐integer nonlinear programming (MINLP) optimization model. The model incorporates rigorous process models for input and output relations based on fundamentals of thermodynamics and unit operations and accurate models for utility systems. To reduce the noncovex items in the proposed MINLP model, equivalent reformulation techniques are introduced. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:20:36.307135-05:
      DOI: 10.1002/aic.15416
  • An Experimental and Theoretical Study of Glycerol Oxidation to
           1,3‐Dihydroxyacetone over Bimetallic Pt‐Bi Catalysts
    • Abstract: It is important to utilize glycerol, the main by‐product of biodiesel, to manufacture value‐added chemicals such as 1,3‐dihydroxyacetone (DHA). In the present work, the performance of five different catalysts (Pt‐Bi/AC, Pt‐Bi/ZSM‐5, Pt/MCM‐41, Pt‐Bi/MCM‐41 and Pt/Bi‐doped‐MCM‐41) was investigated experimentally, where Pt‐Bi/MCM‐41 was found to exhibit the highest DHA yield. To better understand the experimental results and to obtain insight into the reaction mechanism, density functional theory (DFT) computations were conducted to provide energy barriers of elementary steps. Both experimental and calculated results show that for high DHA selectivity, Bi should be located in an adatom‐like configuration Pt, rather than inside Pt. A favorable pathway and catalytic cycle of DHA formation were proposed based on the DFT results. A cooperative effect, between Pt as the primary component and Bi as a promoter, was identified for DHA formation. Both experimental and theoretical considerations demonstrate that Pt‐Bi is efficient to convert glycerol to DHA selectively. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-11T03:20:25.989465-05:
      DOI: 10.1002/aic.15418
  • Computing MOSCED Parameters of Nonelectrolyte Solids with Electronic
           Structure Methods in SMD and SM8 Continuum Solvents
    • Authors: Jeremy R. Phifer; Kimberly J. Solomon, Kayla L. Young, Andrew S. Paluch
      Abstract: An efficient method to predict MOSCED parameters for nonelectrolyte solids using electronic structure calculations in SMD and SM8 continuum solvents is proposed and applied to acetanilide, acetaminophen, and phenacetin. The resulting parameters are ultimately used to predict the equilibrium solubility in a range of solvents over a range of temperatures. By combining MOSCED with SMD and SM8, we are able to leverage the strengths of both methods while eliminating shortcomings that would prevent their use alone for solvent selection in design processes involving nonelectrolyte solid solutes. Comparing to 77 non‐aqueous experimental solubilities of acetaminophen over the range 10 to 30 $^\circ$C, the proposed method has an average absolute error of 0.03 and 0.04 mol fracs for SMD and SM8 regressed parameters, respectively. Aqueous solubilities of acetaminophen over this temperature range are predicted with an average error of 0.030 and 0.0023 mol fracs, respectively. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-08T04:26:29.035354-05:
      DOI: 10.1002/aic.15413
  • Power consumption and form drag of regular and fractal‐shaped
           turbines in a stirred tank
    • Authors: K. Steiros; P. J. K. Bruce, O. R. H. Buxton, J. C. Vassilicos
      Abstract: Previous wind‐tunnel measurements have shown that fractal shaped plates have increased drag compared to square plates of the same area. In this study we measure the power consumption and drag of turbines with fractal and rectangular blades in a stirred tank. Power number decreases from rectangular to fractal impellers by over 10\%, increasingly so with fractal iteration number. Our results suggest that this decrease is not caused by the wake interaction of the blades, nor solely by the wake interaction with the walls either. Pressure measurements on the blades' surface show that fractal blades have lower drag than the rectangular ones, opposite to the wind tunnel experiment results. All tested blades' centre of pressure radius increases with Re, while their drag coefficient decreases, a possible effect of the solid body rotation increase with Re. Spectral analysis of the pressure signal reveals two peaks possibly connected to the blades' roll vortices. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-08T04:26:27.930102-05:
      DOI: 10.1002/aic.15414
  • Outer approximation algorithm with physical domain reduction for
           computer‐aided molecular and separation process design
    • Authors: Smitha Gopinath; George Jackson, Amparo Galindo, Claire S. Adjiman
      Abstract: Integrated approaches to the design of separation systems based on computer‐aided molecular and process design (CAMPD) can yield an optimal solvent structure and process conditions. The underlying design problem, however, is a challenging mixed integer nonlinear problem (MINLP), prone to convergence failure as a result of the strong and nonlinear interactions between solvent and process. To facilitate the solution of this problem, a modified outer‐approximation algorithm is proposed. Tests that remove infeasible regions from both the process and molecular domain are embedded within the outer‐approximation framework. Four tests are developed to remove sub‐domains where constraints on phase behaviour that are implicit in process models or explicit process (design) constraints are violated. The algorithm is applied to three case studies relating to the separation of methane and carbon dioxide at high pressure. The process model is highly nonlinear, and includes mass and energy balances as well as phase equilibrium relations and physical property models based on a group‐contribution version of the statistical associating fluid theory (SAFT‐γ Mie) and the GC+ group contribution method for some pure component properties. A fully automated implementation of the proposed approach is found to converge successfully to a local solution in 30 problem instances. The results highlight the extent to which optimal solvent and process conditions are interrelated and dependent on process specifications and constraints. The robustness of the CAMPD algorithm makes it possible to adopt higher‐fidelity nonlinear models in molecular and process design. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-08T04:26:26.621923-05:
      DOI: 10.1002/aic.15411
  • Surface DEAE Groups Facilitate Protein Transport on Polymer Chains in
    • Authors: Linling Yu; Lingli Gong, Shu Bai, Yan Sun
      Abstract: Sepharose FF was modified with diethylaminoethyl‐dextran (DEAE‐dextran, DexD) and/or DEAE (D) to fabricate three types of ion exchangers FF‐DexD (grafting‐ligand resin), FF‐D (surface‐ligand resin), and FF‐D‐DexD (mixed‐ligand resin), for protein adsorption equilibria and kinetics study. It was found that both adsorption capacity and uptake rate (effective diffusivity, De) were significantly enhanced by grafting DEAE‐dextran. Notably, the De values on FF‐DexD and FF‐D‐DexD (De/D0>1.4) were six times greater than those on FF‐D (De/D0
      PubDate: 2016-07-08T04:26:07.594004-05:
      DOI: 10.1002/aic.15412
  • Optimal processing network design under uncertainty for producing fuels
           and value‐added bioproducts from microalgae: Two‐stage
           adaptive robust mixed integer fractional programming model and
           computationally efficient solution algorithm
    • Authors: Jian Gong; Fengqi You
      Abstract: Fractional metrics, such as return on investment (ROI), are widely used for performance evaluation, but uncertainty in the real market may unfortunately diminish the results that are based on nominal parameters. This article addresses the optimal design of a large‐scale processing network for producing a variety of algae‐based fuels and value‐added bioproducts under uncertainty. We develop by far the most comprehensive processing network with 46,704 alternative processing pathways. Based on the superstructure, a two‐stage adaptive robust mixed integer fractional programming model is proposed to tackle the uncertainty and select the robust optimal processing pathway with the highest ROI. Since the proposed problem cannot be solved directly by any off‐the‐shelf solver, we develop an efficient tailored solution method that integrates a parametric algorithm with a column‐and‐constraint generation algorithm. The resulting robust optimal processing pathway selects biodiesel and poly‐3‐hydroxybutyrate as the final fuel and bioproduct, respectively. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-07-05T11:45:34.979619-05:
      DOI: 10.1002/aic.15370
  • Revealing the role of bromide in the H2O2 direct synthesis with the
           catalyst wet pretreatment method (CWPM)
    • Abstract: A tailor‐made Pd0/K2621 catalyst was subjected to post synthesis modification via a wet treatment procedure. The aim was the understanding of the role of promoters and how—if any—improvements could be qualitatively related to the catalyst performance for the H2O2 direct synthesis. The Catalyst Wet Pretreatment Method was applied in different methanolic solutions containing H2O2, NaBr, and H3PO4, either as single modifiers or as a mixture. The catalyst was characterized by Transmission Electron Microscopy and X‐ray Photoelectron Spectroscopy. It was concluded that the modified catalysts give rise to higher selectivities compared to the pristine reference catalyst thus opening a possibility to exclude the addition of the undesirable selectivity enhancers in the reaction medium. This work provides original evidence on the role of promoters, especially bromide, allowing the formulation of a new reaction mechanism for one of the most challenging reactions recognized by the world. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-07-05T09:35:31.054436-05:
      DOI: 10.1002/aic.15382
  • Moving horizon closed‐loop production scheduling using dynamic
           process models
    • Authors: Richard C. Pattison; Cara R. Touretzky, Iiro Harjunkoski, Michael Baldea
      Abstract: The economic circumstances that define the operation of chemical processes (e.g., product demand, feedstock and energy prices) are increasingly variable. To maximize profit, changes in production rate and product grade must be scheduled with increased frequency. To do so, process dynamics must be considered in production scheduling calculations, and schedules should be recomputed when updated economic information becomes available. In this paper, we address this need by introducing a novel moving horizon closed‐loop scheduling approach. We represent process dynamics explicitly in the scheduling calculation via low‐order models of the closed‐loop dynamics of scheduling‐relevant variables, and build a feedback connection on these variables using an observer structure to update model states. The feedback rescheduling mechanism consists of, i) periodic schedule updates that reflect updated price and demand forecasts, and, ii) event‐driven updates that account for process and market disturbances. The theoretical developments are demonstrated on the model of an industrial‐scale air separation unit. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:46.546883-05:
      DOI: 10.1002/aic.15408
  • Effect of potassium ion on the stability and release rate of hydrogen
           peroxide encapsulated in silica hydrogels
    • Authors: Ezgi Melis Dogan; Fulya Sudur Zalluhoglu, Nese Orbey
      Abstract: Hydrogen peroxide (H2O2) is encapsulated in silica hydrogels using sol‐gel method and the effects of the K+: Na+ ion ratio on gelation time, hydrogel structure, stability, and release rate of H2O2 were investigated. As the amount of K+ ions increased relative to the amount of Na+ ions at the same pH, the gel structure became less compact and the pore diameter increased. Hydrogen peroxide retention values up to 90% and 80% were observed at the end of 7 and 20 days respectively in the presence of K+ ions at low pH values when the initial H2O2 concentration was 19.9 wt% . Release rate of hydrogen peroxide decreased with decreasing pH for the two K+: Na+ ion ratios studied. This work presents an environmentally friendly, low cost, and easy to scale up method to increase the stability of high initial concentrations of H2O2 at room temperature and customize the release rate. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:35.025247-05:
      DOI: 10.1002/aic.15406
  • Loading of fibrous filter media and newly designed filter configurations
           by salt particles: An experimental study
    • Authors: Pengfei Zhao; Peng Cheng, Bruce J. Tatarchuk
      Abstract: Various fibrous filter media, including surface filter media, depth filter media, woven and nonwoven filter media, were tested and particle loading capacity was calculated using bench‐scale setup via a new estimation approach which was proposed and experimentally verified with Novick‐Kozeny model. Multi‐Element Structured Arrays (MESAs) developed by our research group were evaluated as well for particle loading capacity and filter lifetime on 24” × 24” full scale test rig (based on ASHRAE 52.2 Standard). Effects of varying filter media type, filter depth, pleat count and MESAs' element count on salt particle loading performance were experimentally investigated. The experimental studies showed that nonwoven activated carbon fiber (ACF) filter media have allowed significantly higher salt particle loading capacity and longer useful lifetime compared to woven or nanofiber entrapped media. Furthermore, MESAs were able to significantly enhance loading capacity for salt particles and useful lifetime due to higher filtration area and lower filtration velocity. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:32.124745-05:
      DOI: 10.1002/aic.15407
  • Strategy to improve catalytic trend predictions for methane oxidation and
    • Authors: Byeongjin Baek; Abraham Aboiralor, Jacob D. Massa, Shengguang Wang, Purnima Kharidehal, Lars C. Grabow
      Abstract: Computational catalysts screening is an increasingly popular technique, in which the mechanism from a known good catalyst is commonly adopted, parameterized from linear scaling relationships, and then used a microkinetic model to identify other metal alloys with incrementally improved activity. This strategy, however, fails to identify truly novel catalysts that operate under non‐traditional reaction conditions and exhibit alternative dominant reaction pathways. Using methane oxidation and reforming we investigated a series of O* and OH*‐assisted C‐H scission and C‐O bond formation pathways. Notably, for methane oxidation we discovered a second local optimum for O*‐assisted C‐H bond activation near Ag, which is inactive if only the direct C‐H scission route is considered. In light of the significant qualitative difference in the predicted catalytic trends when parallel mechanisms are allowed, we propose a minimum barrier assumption to rapidly screen for potentially important alternative pathways without the need for costly density functional theory simulations. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:31.515331-05:
      DOI: 10.1002/aic.15404
  • Hydrophobic mesoporous acidic resin for hydroxyalkylation/alkylation of
           2‐methylfuran and ketone to high‐density biofuel
    • Abstract: Hydroxyalkylation/alkylation of biomass‐derived 2‐methylfuran (2‐MF) with cyclic ketones (cyclopentanone and cyclohexanone) has great potential in synthesizing high‐density biofuel. But the conversion and selectivity are still unsatisfactory because the in‐situ formed water decreases the acidity of catalyst and induces side reaction. Herein, hydrophobic mesoporous resins with sulfonic acid group (PS) and fluoride sulfonic acid group (PCS) were synthesized by a simple solvothermal reaction and ion exchange treatment, which have good mesoporous structure with surface area of 300‐700 m2/g. Notably, PS and PCS have better hydrophobicity and oleophilicity as compared to widely used sulfonic acid functional amberlyst‐15 and fluoride sulfonic acid functional nafion‐212. In the hydroxyalkylation/alkylation reaction, PS shows higher activity and selectivity than amberlyst‐15 while PCS surpasses nafion‐212. Furthermore, both PS and PCS have good recycling stability in consecutive 5 runs. After hydrodeoxygenation, two high‐density biofuels with density of 0.819 g/ml and 0.825 g/ml were obtained. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:28.514963-05:
      DOI: 10.1002/aic.15410
  • Fluid inhomogeneity within nanoslits and deviation from
           Hagen‐Poiseuille flow
    • Authors: Yuying Wang; Junbo Xu, Chao Yang
      Abstract: Recently, the deviation of nano‐confined flows from classical hydrodynamic theories has been frequently reported. In this work, such a flow is theoretically investigated by means of dissipative particle dynamics (DPD) simulation. The simulation results show that the density and viscosity inhomogeneities near solid/fluid interfaces depends on the slit wettability only. Flow enhancement relative to the Hagen‐Poiseuille flow occurs together with the flow inhomogeneity. Combining of flow inhomogeneity and the Stokes equation, a theoretical model for flux calculation is established. As the slit being widened, the model can be simplified by gradually eliminating the higher order traces, and be simplified into the model with Navier's slip condition and the well‐known Hagen‐Poiseuille relation at last. The theoretical results of flux are in good agreement with the simulations by DPD. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:35:23.851363-05:
      DOI: 10.1002/aic.15409
  • Optimization‐based support for process design under uncertainty: A
           case study
    • Authors: J. Steimel; S. Engell
      Abstract: The paper discusses the use of two‐stage stochastic optimization for the support of the solution of process design problems in the early phase of process development where the different potential elements of the production process can only be described with significant uncertainty. The first stage variables are the design decisions which are fixed after the process has been built, while the second stage variables are the operational parameters which can be adapted to the realization of the uncertainties. We demonstrate the application of the approach to the design of a hydroformylation process in a thermomorphic solvent system. The proposed designs which are computed using the software framework FSOpt are analyzed and compared using different graphic representations which provide insight into what the most important design decisions are. Finally, we review our experience with the proposed formulation and solution techniques and point out where further advances are needed. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:30:35.863174-05:
      DOI: 10.1002/aic.15400
  • Efficient synthesis of iron nanoparticles by self‐agglomeration in a
           fluidized bed
    • Authors: Jun Li; Jing Kong, Qingshan Zhu, Hongzhong Li
      Abstract: A two‐stage, fluidized reduction route is proposed to synthesize iron nanoparticles (NPs), with the aim of enhancing the quality of fluidization and preventing sintering activity. At both low and high temperatures, the degree of metallization η is approximately 80% due to the defluidization. Defluidization is mainly caused by the rapid sintering of the newly formed Fe NPs. The proposed two‐stage fluidization approach successfully resolves the defluidization problem through the self‐agglomeration of nanoparticles cultivated at low temperatures. These self‐agglomerated NPs showed an improved resistance to sintering at high temperatures. The high‐purity Fe NPs prepared by this approach exhibited excellent combustion activity, indicative of the potential as oxygen carriers in chemical looping combustion systems. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:30:34.552158-05:
      DOI: 10.1002/aic.15402
  • A smart manufacturing methodology for real time chemical process diagnosis
           using causal link assessment
    • Authors: R. Rathinasabapathy; M. J. Elsass, J.R. Josephson, J.F. Davis
      Abstract: Industrial chemical plant diagnosis is the task of analyzing process data to sufficiently pinpoint the causes of abnormal events as fast and as accurately as possible so corrective action can be taken in a timely manner. The need to identify failures explicitly and support human centered decision making becomes pronounced for enterprises. Qualitative diagnostic models are offer robustness in capturing diagnostic behaviors when there is little or no data on fault conditions. This paper develops, analyzes, and demonstrates a qualitative diagnostic methodology called Causal Link Assessment (CLA). CLA avoids the drawbacks of other methodologies while leveraging several new concepts that include dynamic pattern generation, single time step modeling with multi‐time step interpretation, and discretized, low granularity dynamic modeling. CLA is demonstrated for an existing ethylene production facility. Model building, robustness, reusability, unaccounted for faults and failures and alignment with emerging Smart Manufacturing infrastructure concepts are discussed. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T18:30:32.378472-05:
      DOI: 10.1002/aic.15403
  • A compartmental CFD‐PBM Model of High Shear Wet Granulation
    • Abstract: The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale‐up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab‐scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi‐compartment population balance equations. Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T03:26:05.639092-05:
      DOI: 10.1002/aic.15401
  • Tuning Carbon Molecular Sieves for Natural Gas Separations: A Diamine
           Molecular Approach
    • Authors: Graham B. Wenz; William J. Koros
      Abstract: This paper introduces a new post‐synthetic modification method for tuning the separation properties of carbon molecular sieve (CMS) membranes. Polymeric hollow fibers of 6FDA/BPDA‐DAM were pyrolyzed to 550 °C under inert Argon, and were then exposed to a tetrahydrofuran solution containing PPM levels of paraphenylenediamine dopant. The original goal of the treatment was to modify the morphology in a manner to prevent relaxation of the CMS to suppress physical aging, envisioned to be analogous to that in glassy polymer membranes where reduction of “unrelaxed free volume” causes reduced permeance with a mild increase in selectivity. Results of long‐term CO2 and CH4 permeation experiments of doped fibers showed that aging‐resistant membranes did not result. This fact notwithstanding, results revealed this approach provides a valuable new tuning tool for CMS transport properties. Complementary gas sorption experiments performed suggest the amine dopants tune large ultramicropores, thereby increasing size and shape based diffusion selectivity. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T03:25:44.901652-05:
      DOI: 10.1002/aic.15405
  • Multi‐Enterprise Supply Chain: Simulation and Optimization
    • Authors: Nihar Sahay; Marianthi Ierapetritou
      Abstract: The advancements in connectivity among the entities belonging to industrial supply chain have given rise to more complex, global supply chain networks. These networks are often constituted of entities that belong to multiple such networks. Interactions among the entities in such networks are also influenced by whether they belong to the same enterprise or different ones. This work takes into consideration the effect of such interactions. The entities belonging to different enterprises are assumed to interact through auctions. An agent based simulation model that incorporates such auctions is used to represent multi‐enterprise supply chain networks. The dynamics of the supply chain affected by the auction mechanism are investigated. Also a derivative free optimization methodology is proposed to find the optimal warehouse capacities for the minimization of total cost. This article is protected by copyright. All rights reserved.
      PubDate: 2016-07-04T03:20:28.842616-05:
      DOI: 10.1002/aic.15399
  • A study on hydrodynamic characteristics in a Φ38 pulsed extraction
           column by four‐sensor optical fiber probe
    • Authors: Yukun Yuan; Yang Gao
      Abstract: Accurate prediction of dispersed phase droplet behavior is crucial to the design and scaling‐up of an extraction column. In this article, the dispersed droplet velocity algorithm and the diameter algorithm in a liquid–liquid two‐phase flow have been developed based on the bubble velocity model in gas–liquid two‐phase flow of Lucas [Measurement Science & Technology. 749, 758(2005)] and Shen [International Journal of Multiphase Flow. 593, 617(2005)]. Hydrodynamic characteristics, including droplet diameter, holdup and droplet velocity, were measured using a self‐made four‐sensor optical fiber probe in a 38 mm‐diameter pulsed sieve‐plate extraction column. Water and kerosene were used as continuous and dispersed phases, respectively. The influences of the pulsed intensity, the continuous and dispersed phase superficial velocities on the hydrodynamic characteristics were investigated. The experimental results show that it is reliable to use a four‐sensor optical probe to measure the hydrodynamic characteristics of a pulsed extraction column. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-07-01T09:55:47.507169-05:
      DOI: 10.1002/aic.15328
  • Integrated design of agricultural and industrial processes: A case study
           of combined sugar and ethanol production
    • Authors: Kotaro Ouchida; Yasuhiro Fukushima, Satoshi Ohara, Akira Sugimoto, Masahiko Hirao, Yasunori Kikuchi
      Abstract: Bioethanol production from molasses has advantages in greenhouse gas emissions because of its energy acquisition from bagasse. However, the improvement of bioethanol productivity is challenging; while each elemental technology option can be greatly improved, the trade‐offs between the production of raw sugar and bioethanol are complex. This issue should be addressed through the optimization of the whole system, including both agricultural and industrial processes. In this study, we constructed a model of combined raw sugar and bioethanol production from sugarcane considering agricultural and industrial technology options. Data were acquired through a detailed investigation of actual sugar mills. Case studies on the redesign of combined raw sugar and bioethanol production demonstrated that the simultaneous implementation of both technology options increases production of food, materials, and energy from plant‐derived renewable resources, thus demonstrating the effectiveness of the interdisciplinary approach. © 2016 American Institute of Chemical Engineers AIChE J, 2016
      PubDate: 2016-06-30T11:27:30.926988-05:
      DOI: 10.1002/aic.15374
  • New Materials for Catalysis and Energy Storage Devices
    • Authors: Harold H. Kung
      PubDate: 2016-06-29T09:45:26.377711-05:
      DOI: 10.1002/aic.15386
  • Why Not Try Active Learning?
    • Authors: John L. Falconer
      PubDate: 2016-06-29T09:45:21.50596-05:0
      DOI: 10.1002/aic.15387
  • Explicit Model Predictive Control of Hybrid Systems and Multiparametric
           Mixed Integer Polynomial Programming
    • Authors: Vassilis M. Charitopoulos; Vivek Dua
      Abstract: Hybrid systems are dynamical systems characterized by the simultaneous presence of discrete and continuous variables. Model‐based control of such systems is computationally demanding. To this effect, explicit controllers which provide control inputs as a set of functions of the state variables have been derived, using multi‐parametric programming mainly for the linear systems. In the present work, hybrid polynomial systems are considered resulting in a Mixed Integer Polynomial Programming (MIPP) problem. Treating the initial state of the system as a set of bounded parameters, the problem is reformulated as a multi‐parametric Mixed Integer Polynomial optimization (mp‐MIPOPT) problem. A novel algorithm for mp‐MIPOPT problems is proposed and the exact explicit control law for polynomial hybrid systems is computed. The key idea is the computation of the analytical solution of the optimality conditions while the binary variables are treated as relaxed parameters. Finally, using symbolic calculations exact non‐convex critical regions are computed. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T17:50:28.668756-05:
      DOI: 10.1002/aic.15396
  • Quantitative Evaluation of Mass Transfer near the Edge of Porous Media by
           Absorption Photometry
    • Authors: Taiki Tanikoshi; Ryoko Otomo, Shusaku Harada
      Abstract: This paper reports the intensive investigation of mass transfer near the entrance (edge) of porous media by quantification of the surrounding concentration field. We have adopted a non‐invasive and real‐time system based on light absorption photometry for measurement of the concentration field in a quasi‐two dimensional cell. This system is, in principle, applicable to the measurement of various substances due to the generality of light absorption. This measurement system was applied to a simple model of the gravity‐driven transport of a substance in a fluid near the edge of a porous medium in the presence of a reaction at the surface. The temporal variation of the complicated concentration field is appropriately captured with a spatial resolution of several tens of micrometers to millimeters. Quantitative analyses revealed that the geometry of the porous edge considerably affects the convection flow and invasion of substances into the medium. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T13:30:25.255347-05:
      DOI: 10.1002/aic.15397
  • Visualization and simulation of the transfer process of
           index‐matched silica microparticle inks for gravure printing
    • Authors: A.M.P. Boelens; S. Lim, B.Y. Ahn, L. Francis, J.A. Lewis, J.J. de Pablo
      Abstract: A combined experimental and computational study of the transfer of transparent index‐matched silica‐particle inks between two flat plates is presented for gravure printing applications. The influence of printing speed and initial ink droplet size on the ability to accurately transfer ink during the printing process is explored systematically. Smooth interface Volume Of Fluid simulations are able to capture experimentally observed ink transfer over a wide range of printing speeds for inks having a modest to intermediate content of silica particles. However, for high‐content silica‐particle inks, transfer is structurally underpredicted. Our calculations indicate that for ink droplets with characteristic dimensions in the vicinity of 10, which are of particular interest for gravure printing applications, ink transfer improves due to the diminishing effect of gravity, and the increased importance of capillary forces at small length scales. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T13:25:23.67395-05:0
      DOI: 10.1002/aic.15392
  • Design of Multi‐Actor Distributed Processing Systems: A
           Game‐Theoretical Approach
    • Authors: Ana I. Torres; George Stephanopoulos
      Abstract: The manufacturing of a final product could be the result of a value chain involving several processing plants distributed across several distinct owners; a feature that may prevent the application of classical process design approaches that depend on a centralized treatment of the complete processing network. In this paper we propose and develop a game‐theoretical framework and specific methodologies, which allow the optimal design of distributed processing systems, through the decentralized strategies of independent actors. The resulting process design corresponds to a Nash Equilibrium point among the interacting actors. Its optimality and the justification of the independent strategies that led to it, are theoretically based on (and constrained by) the properties of the 2‐level Lagrangian approach. The paper also discusses the use of penalty‐term approaches, which can extend the applicability of the proposed framework and design methodologies to problems for which the underlying convexity assumptions of the 2‐level Lagrangian approach may not be possible to ascertain. A series of case studies illustrate the application of the proposed ideas to distributed processing networks of various structures. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T12:55:48.723555-05:
      DOI: 10.1002/aic.15395
  • Half Order Plus Time Delay (HOPTD) Models to Tune PI Controllers
    • Authors: Jietae Lee; Yongjeh Lee, Dae Ryook Yang, Thomas F. Edgar
      Abstract: Methods based on the first‐order plus time delay (FOPTD) model are very popular for tuning proportional‐integral (PI) controllers. The FOPTD model‐based methods are simple and their utility has been proved with many successful applications to a wide range of processes in practice. However, even for some overdamped processes where the FOPTD model has been applied successfully, these empirical FOPTD model‐based methods can fail to provide stable tuning results. To remove these drawbacks, a PI controller tuning method based on half‐order plus time delay (HOPTD) model is proposed. Because FOPTD model‐based methods can be applied to higher order processes, the proposed HOPTD model‐based method can be applied to higher order processes as well. It does not require any additional process information compared to the FOPTD model‐based method and hence can be used for overdamped processes in practice, complementing the traditional FOPTD model‐based methods. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T12:55:41.175039-05:
      DOI: 10.1002/aic.15394
  • General optimization model for the energy planning of industries including
           renewable energy: A case study on oil sands
    • Authors: Mohamed Elsholkami; Ali Elkamel
      Abstract: A multi‐period optimization model is developed for the energy procurement planning of industries including renewable energy. The model is developed with the objective of identifying the optimal set of energy supply technologies to satisfy a set of demands (e.g. power, heat, hydrogen, etc.) and emission targets at minimum cost. Time dependent parameters are incorporated in the model formulation, including demands, fuel prices, emission targets, carbon tax, lead time, etc. The model is applied to a case study based on the oil sands operations over the planning period 2015 – 2050. Various production alternatives were incorporated, including renewable, nuclear, conventional and gasification of alternative fuels. The results obtained indicated that the energy optimization model is a practical tool that can be utilized for identifying the key parameters that affect the operations of energy‐intensive industrial operations, and can further assist in the planning and scheduling of the energy for these industries. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T12:55:27.731664-05:
      DOI: 10.1002/aic.15393
  • CFD‐DEM Simulation of Tube Erosion in a Fluidized Bed
    • Authors: Yongzhi Zhao; Lei Xu, Jinyang Zheng
      Abstract: The erosion of the immersed tubes in a bubbling fluidized bed is studied numerically using an Eulerian‐Lagrangian approach coupling with a particle‐scale erosion model. In this approach, the motion of gas and particles is simulated by the CFD‐DEM method, and an erosion model SIEM (shear impact energy model) is proposed to predict the erosion of the tubes. The model is validated by the good agreement of the simulation results and previous experimental data. By analyzing the simulation results, some characteristics of the tube erosion in the fluidized bed are obtained, such as the distribution of the erosion rate around the tube, the variation of the erosion rate with the position of the tube, the effect of the friction coefficient of particles on the erosion, the relationship between the maximum and the average erosion rate, etc. The micro‐scale behavior of particles around the tubes is also revealed and the linear relationship between the erosion and the shear impact energy is confirmed by the simulation results and experiment. The agreement between simulation and experiment proves that the micro‐scale approach proposed in this paper has high accuracy for predicting erosion of the tubes in the fluidized bed, and has potential to be applied to modeling the process in other chemical equipment facing solid particle erosion. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-27T12:10:56.041293-05:
      DOI: 10.1002/aic.15398
  • Designing an Artificial Golgi Reactor to achieve targeted glycosylation of
           monoclonal antibodies
    • Authors: Oleksiy V. Klymenko; Kate E. Royle, Karen M. Polizzi, Nilay Shah, Cleo Kontoravdi
      Abstract: The therapeutic efficacy of monoclonal antibodies (mAbs) is dependent upon their glycosylation patterns. As the largest group of currently approved biopharmaceuticals, the microheterogeneity in mAb oligosaccharide profiles deriving from mammalian cell production is a challenge to the biopharmaceutical industry. Disengaging the glycosylation process from the cell may offer significant enhancement of product quality and allow better control and reproducibility in line with the Quality by Design paradigm. Three potential designs of an Artificial Golgi reactor implementing targeted sequential glycosylation of mAbs are proposed including a (i) microcapillary film reactor, (ii) packed bed reactor with non‐porous pellets, and (iii) packed bed reactor with porous pellets. Detailed mathematical models are developed to predict their performance for a range of design and operational parameters. While all three reactor designs can achieve desired conversion levels, the choice of a particular one depends on the required throughput and the associated cost of enzymes and co‐substrates. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-24T22:25:30.372333-05:
      DOI: 10.1002/aic.15388
  • A Comparative Computational Study of Diesel Steam Reforming in a Catalytic
           Plate Heat‐Exchange Reactor
    • Authors: Harsh Dhingra; Mayur Mundhwa, Rajesh D. Parmar
      Abstract: A two‐dimensional steady‐state model of a catalytic plate reactor for diesel steam reforming is developed. Heat is provided indirectly to endothermic reforming sites by flue gas from a SOFC tail‐gas burner. Two experimentally‐validated kinetic models on diesel reforming on platinum (Pt) catalyst were implemented for a comparative study; the model of Parmar et al.19 for a Pt/Al2O3 and the model of Shi et al.20 for a Pt/Gd‐CeO2 (GDC). The kinetic models were compared for: species concentration, approach to equilibrium, gas hourly space velocity and effectiveness factor. Co‐current flow showed better heat transfer compared to counter‐current flow arrangement. The comparison between the two kinetic models showed that different supports plays significant role in the final design of a reactor. The study also determined that initial 20% of the plate reactor has high diffusion limitation suggesting to use graded catalyst to optimize the plate reactor performance. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-24T22:25:28.431356-05:
      DOI: 10.1002/aic.15391
  • Reaction Mechanism and Kinetics for Hydrolytic Dehydrogenation of Ammonia
           Borane on a Pt/CNT Catalyst
    • Authors: Wenyao Chen; Dali Li, Zijun Wang, Gang Qian, Zhijun Sui, Xuezhi Duan, Xinggui Zhou, Isaac Yeboah, De Chen
      Abstract: A reaction mechanism is proposed for hydrolytic dehydrogenation of ammonia borane on a Pt/CNT catalyst. A combination of thermodynamic analysis and FTIR measurement reveals that B‐containing byproducts are mainly in the form of an NH4B(OH)4‐B(OH)3 mixture rather than NH4BO2 reported previously. The revised main reaction is NH3BH3+4H2O→NH4++B(OH)4‐+3H2↑, involving the B‐H, B‐N and O‐H bond cleavages. Isotopic experiments using D2O instead of H2O as reactant or introducing D2 into the reaction atmosphere suggest the O‐H bond cleavage being in the rate‐determining step, and an unfavorable occurrence of the chemisorbed H2O dissociation (i.e., the direct O‐H bond cleavage), respectively. Different reaction pathways with indirect O‐H bond cleavages are analyzed, and then NH3BH2*+H2O*→NH3BH2(OH)*+H* is suggested as the rate‐determining step. Subsequently, a Langmuir‐Hinshelwood kinetic model is developed, which fits well with the experimental data. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-24T22:25:27.442625-05:
      DOI: 10.1002/aic.15389
  • A High‐Throughput Assay for Screening Modifiers of Calcium Oxalate
    • Authors: Jun Ha Kwak; Sriram Ramamoorthy, Sahar Farmanesh, Jeffrey D. Rimer, Pankaj Karande
      Abstract: Controlling crystal habit using growth modifiers provides novel avenues for tailoring properties of crystalline materials. Here, we report on the design of a high‐throughput screening assay for rapid identification of growth modifiers using calcium oxalate monohydrate crystallization as a model system. We conducted a systematic study of assay parameters (sample volume, shaking and temperature) on crystallization kinetics. Crystallization half‐time (CHT, t1/2), defined as the time at which crystallization is 50% complete, was obtained from the logistic fit of kinetic data and used as a measure of growth modifier potency. A test library of 13 peptides composed of aspartic acid and alanine residues was screened to determine their growth promotion or inhibition potentials. Leads identified from this study are in good agreement with ion‐selective electrode (ISE) measurements and a single time point measurement of free calcium ion concentration is an excellent end‐point for evaluating modifier potency. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-24T22:25:25.910689-05:
      DOI: 10.1002/aic.15390
  • Cohesive grains: Bridging micro‐level measurements to
           macro‐level flow behavior via surface roughness
    • Authors: Peiyuan Liu; Casey Q. LaMarche, Kevin M. Kellogg, Stuart Leadley, Christine M. Hrenya
      Abstract: Understanding fine‐particle flows relies on van der Waals cohesion modeling, requiring a method to consider measured surface roughness. We propose a robust scheme to extract roughness parameters from AFM surface maps, achieving accurate predictions of micro‐scale measured cohesion. Macro‐scale quantitative agreement is demonstrated by comparing defluidization predictions to measurements, which are sensitive to cohesion and system‐size independent. Agreement in both micro‐ and macro‐scale comparisons highlights the role of individual particle properties on bulk granular systems. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-18T10:21:02.002845-05:
      DOI: 10.1002/aic.15383
  • Kinetic study of hydrogen peroxide decomposition at high temperatures and
           concentrations in two capillary microreactors
    • Abstract: On the background of the direct adipic acid synthesis from cyclohexene and H2O2, a kinetic model was derived for the H2O2 decomposition catalyzed by sodium tungstate at high H2O2 concentrations and high temperatures. A perfluoroalkoxy (PFA) and a stainless steel micro‐flow capillary match commonly used microreactor materials. In the PFA capillary, the decomposition of hydrogen peroxide increased with residence time, reaction temperature and catalyst loading. The reaction order with respect to hydrogen peroxide and sodium tungstate was zero and one, respectively. Simulated data fit well with experimental data in the PFA capillary. While showing a similar trend as that in the PFA capillary, the stainless steel capillary exhibited much higher reaction rates. The steel surface participated in the decomposition process as a heterogeneous catalyst. Key influencing factors of the H2O2 decomposition provided some clues on the reaction mechanism of the adipic acid synthesis and its process optimization. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-18T10:20:41.93671-05:0
      DOI: 10.1002/aic.15385
  • Catalytic membrane reactor for Suzuki‐Miyaura C‐C
           cross‐coupling: Explanation for its high efficiency via modeling
    • Abstract: A polymeric catalytic membrane was previously prepared that showed remarkable efficiency for Suzuki‐Miyaura C‐C cross‐coupling in a flow‐through configuration. A mathematic model was developed and fitted to the experimental data to understand the significant apparent reaction rate increase exhibited by the catalytic membrane reactor compared to the catalytic system under batch reaction conditions. It appears that the high palladium nanoparticles concentration inside the membrane is mainly responsible for the high apparent reaction rate achieved. In addition the best performance of the catalytic membrane could be achieved only in the forced flow‐through configuration, that, conditions permitting to the reactants be brought to the catalytic membrane by convection. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-17T06:55:29.011669-05:
      DOI: 10.1002/aic.15379
  • Erratum to “An Integrated Framework for Scheduling and Control Using
           Fast Model Predictive Control”
    • Authors: Lisia S. Dias; Jinjun Zhuge, Marianthi G. Ierapetritou
      PubDate: 2016-06-15T03:40:48.164693-05:
      DOI: 10.1002/aic.15375
  • Macro‐Economic Multi‐Objective Input‐Output Model for
           Minimizing CO2 Emissions: Application to the U.S. Economy
    • Abstract: Designing effective environmental policies for mitigating global warming is a very challenging task that requires detailed knowledge of the international channels through which goods are traded. This work presents a decision‐support tool that minimizes the impact at a global macroeconomic scale by performing changes in the economic sectors of an economy. Our tool combines multi‐objective optimization, environmentally extended input‐output tables and life cycle assessment within a unified framework. Our results on the US economy to minimize CO2 emissions identify sectors that should be regulated first to reach a given environmental target while maximizing the demand satisfaction. The impact of shale gas is also studied. Our findings show that the application of process systems engineering tools at a macroeconomic level can provide valuable insight for public policy makers into problems of general interest. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-15T03:40:40.611982-05:
      DOI: 10.1002/aic.15376
  • Oxidative dehydrogenation of butenes over Bi‐Mo and Mo‐V based
           catalysts in a two‐zone fluidized bed reactor
    • Authors: Julius Rischard; Robert Franz, Claudia Antinori, Olaf Deutschmann
      Abstract: The oxidative dehydrogenation of a 1‐butene/trans‐butene (1:1) mixture to 1,3‐butadiene was carried out in a two‐zone fluidized bed reactor using a Mo‐V‐MgO and a γ‐Bi2MoO6 catalyst. The significant operating conditions temperature, oxygen/butene molar ratio, butene inlet height and flow velocity were varied to gain high 1,3‐butadiene selectivity and yield. Furthermore, axial concentration profiles were measured inside the fluidized bed to gain insight into the reaction network in the two zones. For optimized conditions and with a suitable catalyst, the two‐zone fluidized bed reactor makes catalyst regeneration and catalytic reaction possible in a single vessel. In the lower part of the fluidized bed, the oxidation of coke deposits on the catalyst as well as the filling of oxygen vacancies in the lattice can occur. The oxidative dehydrogenation reaction takes place in the upper zone. Thorough particle mixing inside fluidized beds causes permanent particle exchange between both zones. This article is protected by copyright. All rights reserved.
      PubDate: 2016-06-13T11:21:37.507966-05:
      DOI: 10.1002/aic.15368
  • Modeling bread baking with focus on overall deformation and local porosity
    • Authors: Vincent Nicolas; Fernanda Vanin, Christophe Doursat, David Grenier, Tiphaine Lucas, Denis Flick
      Abstract: A two dimensional model of bread baking was developed including, for the first time, the dependence of dough viscosity on both temperature and moisture content, the carbon dioxide dissolved from liquid water together with gas generation from yeast at the beginning of baking and the shrinkage due to dough drying. Particular attention was paid to experimental validation of both overall and local variables such as local temperature, overall mass loss and local moisture content, overall CO2 released into the oven, and overall deformation and local expansion or shrinkage. Sensitivity studies on generation of carbon dioxide, gravity and shrinkage are presented to discuss their influences on bread geometry, porosity (reflecting the alveolar structure) and gas pressure. This article is protected by copyright. All rights reserved.
      PubDate: 2016-05-09T10:35:27.788138-05:
      DOI: 10.1002/aic.15301
  • Issue information ‐ table of contents
    • Pages: 2949 - 2949
      PubDate: 2016-08-15T13:48:40.715112-05:
      DOI: 10.1002/aic.14996
  • Effect of needle‐like crystal shape on measured particle size
    • Authors: Ian de Albuquerque; Marco Mazzotti, David R. Ochsenbein, Manfred Morari
      Pages: 2974 - 2985
      Abstract: The effect crystal morphology has on measured particle size distributions (PSDs) is explored, with a focus on particles exhibiting a needle‐like habit. An idealized in silico study was performed, targeted at modeling the measurement principles of various particle sizing devices, namely laser diffraction, Coulter counter, focused beam reflectance measurement, a single and a dual projection imaging devices. The evolution of a crystal population is measured, allowing for an evaluation of the introduced biases. Further, the consequences of these biases are highlighted by demonstrating how the real growth mechanism may be incorrectly interpreted depending on the chosen particle sizing technique. It is found that techniques which utilize a one‐dimensional PSD are incapable of simultaneously describing the concentration profile and average length; in contrast, imaging techniques are able to reproduce both quantities. Finally, the dual projection imaging device is shown to be the only instrument to yield a nearly bias‐free measurement. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2974–2985, 2016
      PubDate: 2016-05-16T09:05:27.565711-05:
      DOI: 10.1002/aic.15270
  • Experiment design for control‐relevant identification of partially
           known stable multivariable systems
    • Authors: Shyam Panjwani; Michael Nikolaou
      Pages: 2986 - 3001
      Abstract: Design of experiments for identification of control‐relevant models is at the heart of robust controller design. In a number of prior publications, experiment designs have been developed that generate input/output data for efficient identification of models satisfying the integral controllability (IC) condition. The design of process inputs for such experiments is often, but not always, based on the concept of independent random rotated inputs, with appropriately proportioned amplitudes. However, prior publications do not account for models that may already be partially known before identification. In this work, this issue is addressed by developing a general experiment design framework for efficient identification of partially known models that must satisfy the IC condition. This framework produces optimal designs by solving appropriately formulated optimization problems, based on a number of rigorous theoretical results. Numerical simulations illustrate the proposed approach and potential future extensions are suggested. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2986–3001, 2016
      PubDate: 2016-03-21T13:24:26.770236-05:
      DOI: 10.1002/aic.15212
  • A cost‐effective model for the gasoline blend optimization problem
    • Pages: 3002 - 3019
      Abstract: Gasoline blending is a critical process with a significant impact on the total revenues of oil refineries. It consists of mixing several feedstocks coming from various upstream processes and small amounts of additives to make different blends with some specified quality properties. The major goal is to minimize operating costs by optimizing blend recipes, while meeting product demands on time and quality specifications. This work introduces a novel continuous‐time mixed‐integer linear programming (MILP) formulation based on floating time slots to simultaneously optimize blend recipes and the scheduling of blending and distribution operations. The model can handle non‐identical blenders, multipurpose product tanks, sequence‐dependent changeover costs, limited amounts of gasoline components, and multi‐period scenarios. Because it features an integrality gap close to zero, the proposed MILP approach is able to find optimal solutions at much lower computational cost than previous contributions when applied to large gasoline blend problems. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3002–3019, 2016
      PubDate: 2016-03-25T13:15:59.491084-05:
      DOI: 10.1002/aic.15208
  • Data‐driven mathematical modeling and global optimization framework
           for entire petrochemical planning operations
    • Authors: Jie Li; Xin Xiao, Fani Boukouvala, Christodoulos A. Floudas, Baoguo Zhao, Guangming Du, Xin Su, Hongwei Liu
      Pages: 3020 - 3040
      Abstract: In this work we develop a novel modeling and global optimization‐based planning formulation, which predicts product yields and properties for all of the production units within a highly integrated refinery‐petrochemical complex. Distillation is modeled using swing‐cut theory, while data‐based nonlinear models are developed for other processing units. The parameters of the postulated models are globally optimized based on a large data set of daily production. Property indices in blending units are linearly additive and they are calculated on a weight or volume basis. Binary variables are introduced to denote unit and operation modes selection. The planning model is a large‐scale non‐convex mixed integer nonlinear optimization model, which is solved to ε‐global optimality. Computational results for multiple case studies indicate that we achieve a significant profit increase (37–65%) using the proposed data‐driven global optimization framework. Finally, a user‐friendly interface is presented which enables automated updating of demand, specification, and cost parameters. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3020–3040, 2016
      PubDate: 2016-03-27T21:35:54.107652-05:
      DOI: 10.1002/aic.15220
  • Optimal supply chain design and operations under multi‐scale
           uncertainties: Nested stochastic robust optimization modeling framework
           and solution algorithm
    • Authors: Dajun Yue; Fengqi You
      Pages: 3041 - 3055
      Abstract: Although strategic and operational uncertainties differ in their significance of impact, a “one‐size‐fits‐all” approach has been typically used to tackle all types of uncertainty in the optimal design and operations of supply chains. In this work, we propose a stochastic robust optimization model that handles multi‐scale uncertainties in a holistic framework, aiming to optimize the expected economic performance while ensuring the robustness of operations. Stochastic programming and robust optimization approaches are integrated in a nested manner to reflect the decision maker's different levels of conservativeness toward strategic and operational uncertainties. The resulting multi‐level mixed‐integer linear programming model is solved by a decomposition‐based column‐and‐constraint generation algorithm. To illustrate the application, a county‐level case study on optimal design and operations of a spatially‐explicit biofuel supply chain in Illinois is presented, which demonstrates the advantages and flexibility of the proposed modeling framework and efficiency of the solution algorithm. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3041–3055, 2016
      PubDate: 2016-04-14T09:25:53.342856-05:
      DOI: 10.1002/aic.15255
  • Control structure selection based on economics: Generalization of the
           back‐off methodology
    • Authors: Ioannis K. Kookos; John D. Perkins
      Pages: 3056 - 3064
      Abstract: The back‐off methodology has been extensively developed and refined in the last 20 years and offers a systematic tool for solving the simultaneous design and control problem. Previous work has been based on linear process and control models that ensure quick determination of the optimal solution at the expense of potential loss in the accuracy due to nonlinear process characteristics. In this work a new formulation is proposed where use is made of a nonlinear process model that ensures improved accuracy and also offers an improved opportunity for the simultaneous consideration of process design and process control. Two case studies are studied in detail and demonstrate the advantages of the new formulation. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3056–3064, 2016
      PubDate: 2016-05-05T09:29:23.306057-05:
      DOI: 10.1002/aic.15284
  • TeCSMART: A hierarchical framework for modeling and analyzing systemic
           risk in sociotechnical systems
    • Authors: Venkat Venkatasubramanian; Zhizun Zhang
      Pages: 3065 - 3084
      Abstract: Recent systemic failures in different domains continue to remind us of the fragility of complex sociotechnical systems. Although these failures occurred in different domains, there are common failure mechanisms that often underlie such events. Hence, it is important to study these disasters from a unifying systems engineering perspective so that one can understand the commonalities as well as the differences to prevent or mitigate future events. A new conceptual framework that systematically identifies the failure mechanisms in a sociotechnical system, across different domains is proposed. Our analysis includes multiple levels of a system, both social and technical, and identifies the potential failure modes of equipment, humans, policies, and institutions. With the aid of three major recent disasters, how this framework could help us compare systemic failures in different domains and identify the common failure mechanisms at all levels of the system is demonstrated. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3065–3084, 2016
      PubDate: 2016-05-24T10:00:40.904548-05:
      DOI: 10.1002/aic.15302
  • Using functional programming to recognize named structure in an
           optimization problem: Application to pooling
    • Authors: Francesco Ceccon; Georgia Kouyialis, Ruth Misener
      Pages: 3085 - 3095
      Abstract: Branch‐and‐cut optimization solvers typically apply generic algorithms, e.g., cutting planes or primal heuristics, to expedite performance for many mathematical optimization problems. But solver software receives an input optimization problem as vectors of equations and constraints containing no structural information. This article proposes automatically detecting named special structure using the pattern matching features of functional programming. Specifically, we deduce the industrially‐relevant nonconvex nonlinear Pooling Problem within a mixed‐integer nonlinear optimization problem and show that we can uncover pooling structure in optimization problems which are not pooling problems. Previous work has shown that preprocessing heuristics can find network structures; we show that we can additionally detect nonlinear pooling patterns. Finding named structures allows us to apply, to generic optimization problems, cutting planes or primal heuristics developed for the named structure. To demonstrate the recognition algorithm, we use the recognized structure to apply primal heuristics to a test set of standard pooling problems. © 2016 The
      Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: 3085–3095, 2016
      PubDate: 2016-05-24T09:36:05.153421-05:
      DOI: 10.1002/aic.15308
  • Early‐stage evaluation of biorefinery processing pathways using
           process network flux analysis
    • Pages: 3096 - 3108
      Abstract: With growing interest in the biomass value chain, a multitude of reactions are proposed in literature for the conversion of biomass into a variety of biofuels. In the early design stage, data for a detailed design is scarce rendering an in‐depth analysis of all possibilities challenging. In this contribution, the screening methodology process network flux analysis (PNFA) is introduced assessing systematically the cost and energy performance of processing pathways. Based on the limited data available, a ranking of biorefinery pathways and a detection of bottlenecks is achieved by considering the reaction performance as well as the feasibility and energy demand of various separation strategies using thermodynamic sound shortcut models. PNFA is applied to a network of six gasoline biofuels from lignocellulosic biomass. While 2‐butanol is ruled out due to a lack in yield and selectivity, iso‐butanol and 2‐butanone are identified as economically promising fuels beyond ethanol. Topical area: Process Systems Engineering. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3096–3108, 2016
      PubDate: 2016-05-29T17:55:29.280849-05:
      DOI: 10.1002/aic.15305
  • On the relation between flexibility analysis and robust optimization for
           linear systems
    • Authors: Qi Zhang; Ignacio E. Grossmann, Ricardo M. Lima
      Pages: 3109 - 3123
      Abstract: Flexibility analysis and robust optimization are two approaches to solving optimization problems under uncertainty that share some fundamental concepts, such as the use of polyhedral uncertainty sets and the worst‐case approach to guarantee feasibility. The connection between these two approaches has not been sufficiently acknowledged and examined in the literature. In this context, the contributions of this work are fourfold: (1) a comparison between flexibility analysis and robust optimization from a historical perspective is presented; (2) for linear systems, new formulations for the three classical flexibility analysis problems—flexibility test, flexibility index, and design under uncertainty—based on duality theory and the affinely adjustable robust optimization (AARO) approach are proposed; (3) the AARO approach is shown to be generally more restrictive such that it may lead to overly conservative solutions; (4) numerical examples show the improved computational performance from the proposed formulations compared to the traditional flexibility analysis models. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3109–3123, 2016
      PubDate: 2016-05-31T14:55:44.987283-05:
      DOI: 10.1002/aic.15221
  • A trust region filter method for glass box/black box optimization
    • Authors: John P. Eason; Lorenz T. Biegler
      Pages: 3124 - 3136
      Abstract: Modern nonlinear programming solvers can be utilized to solve very large scale problems in chemical engineering. However, these methods require fully open models with accurate derivatives. In this article, we address the hybrid glass box/black box optimization problem, in which part of a system is modeled with open, equation based models and part is black box. When equation based reduced models are used in place of the black box, NLP solvers may be applied directly but an accurate solution is not guaranteed. In this work, a trust region filter algorithm for glass box/black box optimization is presented. By combining concepts from trust region filter methods and derivative free optimization, the method guarantees convergence to first‐order critical points of the original glass box/black box problem. The algorithm is demonstrated on three comprehensive examples in chemical process optimization. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3124–3136, 2016
      PubDate: 2016-06-03T09:31:33.460171-05:
      DOI: 10.1002/aic.15325
  • Systematic integrated process design and control of binary element
           reactive distillation processes
    • Pages: 3137 - 3154
      Abstract: Integrated process design and control of reactive distillation processes is considered through a computer‐aided framework. First, a set of simple design methods for reactive distillation column (RDC) that are similar in concept to nonreactive distillation design methods are extended to design‐control of RDCs. These methods are based on the element concept where the reacting system of compounds is represented as elements. When only two elements are needed to represent the reacting system of more than two compounds, a binary element system is identified. It is shown that the same design‐control principles that apply to a nonreacting binary system of compounds are also valid for a reactive binary system of elements for distillation columns. Application of this framework shows that designing the reactive distillation process at the maximum driving force results in a feasible and reliable design of the process as well as the controller structure. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3137–3154, 2016
      PubDate: 2016-06-07T09:40:55.868365-05:
      DOI: 10.1002/aic.15322
  • Superstructure optimization of integrated fast
    • Authors: Zhihong Yuan; Mario R. Eden
      Pages: 3155 - 3176
      Abstract: Motivated by the apparent advantages of fast pyrolysis and gasification, a novel integrated biorefinery plant is systematically synthesized for coproducing premium quality liquid fuels and propylene. The required heat and fluidization promotion of the fast pyrolyzer are provided by hot syngas from the gasifier. Light gas and syngas from the fast pyrolyzer are finally converted to hydrocarbons via Fischer‐Tropsch synthesis. Multiple syngas production technologies, hydrocarbon production and downstream upgrading routes are incorporated within a superstructure optimization based process synthesis framework. This is the first article to investigate the benefits associated with the introduction of conventional catalytic cracking and dewaxing from a systems engineering perspective. Surrogate models describing the gasifiers and rigorous equations for Fischer‐Tropsch effluents validated by our experimental collaborator are introduced. Through investigation of five scenarios the primary parameters affecting overall economic performance are identified through ranking of the relevant candidates. Comparisons of the hybrid conversion route and stand‐alone routes are made. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3155–3176, 2016
      PubDate: 2016-06-08T09:12:50.554547-05:
      DOI: 10.1002/aic.15337
  • Control‐relevant decomposition of process networks via
           optimization‐based hierarchical clustering
    • Authors: Seongmin Heo; Prodromos Daoutidis
      Pages: 3177 - 3188
      Abstract: A systematic method is proposed for control‐relevant decomposition of complex process networks. Specifically, hierarchical clustering methods are adopted to identify constituent subnetworks such that the components of each subnetwork are strongly interacting while different subnetworks are loosely coupled. Optimal clustering is determined through the solution of integer optimization problems. The concept of relative degree is used to measure distance between subnetworks and compactness of subnetworks. The application of the proposed method is illustrated using an example process network. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3177–3188, 2016
      PubDate: 2016-06-13T13:30:34.366581-05:
      DOI: 10.1002/aic.15323
  • Study on dynamic behavior adjustment of nonlinear chemical processes
    • Authors: Hao Jiang; Bingzhen Chen
      Pages: 3189 - 3198
      Abstract: In nonlinear chemical processes, many economically desirable operating conditions are located in unstable regions, leading to product quality degradation and safety problems. Therefore, determining how to adjust the dynamic behavior to make the process stable within its desired operational range is a topic of common interest within industrial and academic communities. This article presents a dynamic behavior adjustment method based on a washout filter‐aided controller with an improved parameter‐tuning algorithm to stabilize parts of the equilibrium manifold of chemical processes. In addition, applying this method to industrial toluene liquid‐phase catalytic oxidation shows that, by combining a conventional proportional‐integral (PI) controller with the proposed improved washout filter‐aided controller, the performance of set‐point tracking is improved for cases with parameter uncertainty. In general, the proposed dynamic behavior adjustment method will be effective for most chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3189–3198, 2016
      PubDate: 2016-06-13T14:10:29.614353-05:
      DOI: 10.1002/aic.15342
  • A superstructure representation, generation, and modeling framework for
           chemical process synthesis
    • Authors: WenZhao Wu; Carlos A. Henao, Christos T. Maravelias
      Pages: 3199 - 3214
      Abstract: We present a framework for the efficient representation, generation, and modeling of superstructures for process synthesis. First, we develop a new representation based on three basic elements: units, ports, and conditioning streams. Second, we present four rules based on “minimal” and “feasible” component sets for the generation of simple superstructures containing all feasible embedded processes. Third, in terms of modeling, we develop a modular approach, and formulate models for each basic element. We also present a canonical form of element models using input/output variables and constrained/free variables. The proposed methods provide a coherent framework for superstructure‐based process synthesis, allowing efficient model generation and modification. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3199–3214, 2016
      PubDate: 2016-06-16T09:51:38.217582-05:
      DOI: 10.1002/aic.15300
  • Global optimization of an industrial gas network operation
    • Pages: 3215 - 3224
      Abstract: Air Liquide operates several industrial gas pipeline networks around the world, connecting air separation plants to customers of industrial gases. The operation of such a network of plants, pipelines, and customers is complicated due to fluctuating electricity prices and customer demands. We describe a complex industrial problem for real‐time optimization of network operations in the presence of these challenges. We then summarize a concerted modeling and algorithmic effort toward global optimization of this model. The resulting advances include development of a regression‐based fully‐deterministic nonconvex optimization model, a tool for diagnosing infeasibilities during model development, reformulations and scaling to make the model more amenable for optimization, and development of strengthened relaxations for its efficient solution. We provide details on the development of these tools and techniques that facilitated the solution of this model in a reasonable computational time with the global solver BARON. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3215–3224, 2016
      PubDate: 2016-06-16T09:56:18.777785-05:
      DOI: 10.1002/aic.15344
  • On optimal sensing and actuation design for an industrial scale steam
           methane reformer furnace
    • Authors: Ankur Kumar; Michael Baldea, Thomas F. Edgar
      Pages: 3225 - 3237
      Abstract: The spatial temperature distribution in the highly energy‐intensive furnace unit in a steam reforming‐based hydrogen manufacturing plant determines the energy efficiency of the plant. While the fuel distribution among the burners can be manipulated to control the furnace temperature distribution, adequate temperature measurements is a prerequisite. Typical furnaces have hundreds of tubes and burners, and economic considerations dictate that the number of temperature sensors and flow actuators required for automatic temperature optimization be minimized. In this article, we investigate several formulations for the design of the optimal sensor and actuation configurations for an industrial furnace. We initially formulate the optimal sensor placement problem as a bi‐level optimization problem, and exploit the problem structure to obtain an equivalent mixed‐integer linear program formulation. We then provide an extension to the combined sensor and actuator placement. We demonstrate the efficacy of our approach through simulation case studies based on industrial data. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3225–3237, 2016
      PubDate: 2016-06-17T14:50:37.14297-05:0
      DOI: 10.1002/aic.15333
  • Optimal design of solvents for extractive reaction processes
    • Authors: Teng Zhou; Jiayuan Wang, Kevin McBride, Kai Sundmacher
      Pages: 3238 - 3249
      Abstract: It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3238–3249, 2016
      PubDate: 2016-06-21T10:40:32.919941-05:
      DOI: 10.1002/aic.15360
  • A mathematical optimization framework for the design of nanopatterned
    • Authors: Christopher L. Hanselman; Chrysanthos E. Gounaris
      Pages: 3250 - 3263
      Abstract: The recent explosion of capabilities to fabricate nanostructured materials to atomic precision has opened many avenues for technological advances but has also posed unique questions regarding the identification of structures that should serve as targets for fabrication. One material class for which identifying such targets is challenging are transition‐metal crystalline surfaces, which enjoy wide application in heterogeneous catalysis. The high combinatorial complexity with which patterns can form on such surfaces calls for a rigorous design approach. In this article, we formalize the identification of the optimal periodic pattern of a metallic surface as an optimization problem, which can be addressed via established algorithms. We conduct extensive computational studies involving an array of crystallographic lattices and structure‐function relationships, validating patterns that were previously known to be promising but also revealing a number of new, nonintuitive designs. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3250–3263, 2016
      PubDate: 2016-06-22T14:55:48.520376-05:
      DOI: 10.1002/aic.15359
  • Multi‐scenario robust online optimization and control of
           fed‐batch systems via dynamic model‐based scenario selection
    • Pages: 3264 - 3284
      Abstract: The manuscript proposes a novel robust methodology for the model‐based online optimization/optimal control of fed‐batch systems, which consists of two different interacting layers executed asynchronously. The first iteratively computes robust control actions online via multi‐scenario stochastic optimization while the second iteratively re‐estimates the optimal scenario map after every single/every certain number of control action/actions. The novelty of the approach is twofold: (I) the scenario map is optimally computed/updated based on probabilistic information on the process model uncertainty as well as the sensitivity of the controlled system to the uncertain parameters; and (II) the scenario set is dynamically re‐estimated, thus accounting for the effect of disturbances and changes in the operating conditions of the target process. The proposed approach is applied to a fed‐batch Williams‐Otto process and compared to an existing multi‐scenario optimization/control algorithm as well as a non‐robust optimization/control strategy to draw conclusions about which method is more effective. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3264–3284, 2016
      PubDate: 2016-06-24T14:50:39.863025-05:
      DOI: 10.1002/aic.15346
  • Liver function as an engineering system
    • Pages: 3285 - 3297
      Abstract: Process Systems Engineering has tackled a wide range of problems including manufacturing, the environment, and advanced materials design. Here we discuss how tools can be deployed to tackle medical problems which involve complex chemical transformations and spatial phenomena looking in particular at the liver system, the body's chemical factory. We show how an existing model has been developed to model distributed behavior necessary to predict the behavior of drugs for treating liver disease. The model has been used to predict the effects of suppression of de novo lipogenesis, stimulation of β‐oxidation and a combination of the two. A reduced model has also been used to explore the prediction of behavior of hormones in the blood stream controlling glucose levels to ensure that levels are kept within safe bounds using interval methods. The predictions are made resulting from uncertainty in two key parameters with oscillating input resulting from regular feeding. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3285–3297, 2016
      PubDate: 2016-06-30T11:00:35.142821-05:
      DOI: 10.1002/aic.15292
  • A controllability analysis of a pilot‐scale CO2 capture plant using
           ionic liquids
    • Pages: 3298 - 3309
      Abstract: Nowadays there is a world concern on the impact and effect of large CO2 atmospheric concentrations on human health. Fossil‐fuel combustion processes in power plants are among the major contributors to this issue. Hence, it becomes important to develop new clean and sustainable processes aimed to reduce the amount of CO2 released to atmosphere by combustion processes in power plants. One of the best feasible manners to achieve this purposes lies in the use of a closed‐loop control system able to keep the amount of green‐house gases under specification even in the presence of unexpected scenarios. Of course, CO2 capture has been extensively researched in the past. However, in this regard the industrial practice has consisted in using Amines leading to sustainability and safety issues. Hence, it makes sense to seek for new and potentially environmental friendly process design to address CO2 reduction from power plants but applying a new type of sustainable stripping solvents. In this work we address the sustainable CO2 reduction issue from a process control point of view applying a previous design proposed by our research team based on the deployment of Ionic Liquids (IL) as potential green solvents and developing an efficient and decentralized multiloop control system. We demonstrate that the closed‐loop system is able to maintain the CO2 concentration levels under specification by testing in presence of several demanding scenarios. Overall, from an economic, sustainable and control point of view it looks feasible to replace the traditional amines‐based CO2 capture process by other alternatives based on the application of IL as potential green solvents. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3298–3309, 2016
      PubDate: 2016-06-30T11:05:49.910703-05:
      DOI: 10.1002/aic.15371
  • Polynomial chaos‐based robust design of systems with probabilistic
    • Authors: Dongying E. Shen; Richard D. Braatz
      Pages: 3310 - 3318
      Abstract: A new algorithm is proposed for the design of nonlinear dynamical systems with probabilistic uncertainties. The dependence of the design objective and constraints on uncertainties is quantified by the polynomial chaos expansions (PCEs), while the relationships between the design parameters and the design objective/constraints are parameterized by Legendre polynomials. In two case studies, the polynomial chaos‐based algorithm reduces the number of system evaluations required by optimization by an order of magnitude. Quantifying the dependence on uncertain parameters via the PCEs and including the quantification in design optimization simultaneously improved the distribution of the performance index and the probability of constraint fulfillment. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3310–3318, 2016
      PubDate: 2016-06-30T10:55:31.677725-05:
      DOI: 10.1002/aic.15373
  • Assessing the capacity of local ecosystems to meet industrial demand for
           ecosystem services
    • Authors: Varsha Gopalakrishnan; Bhavik R. Bakshi, Guy Ziv
      Pages: 3319 - 3333
      Abstract: Despite the importance of ecosystems, engineering activities continue to ignore or greatly undervalue their role. Consequently, engineered systems often overshoot nature's capacity to support them, causing ecological degradation. Such systems tend to be inherently unsustainable, and they often fail to benefit from nature's ability to provide essential goods and services. This work explores the idea of including ecosystems in chemical processes, and assesses whether such a techno‐ecological synergistic system can operate within ecological constraints. The demand for ecosystem services is quantified by emissions and resources used, while the supply is provided by ecosystems on the manufacturing site. Application to a biodiesel manufacturing site demonstrates that ecosystems can be economically and environmentally superior to conventional technologies for making progress toward zero emissions and net positive impact manufacturing. These results highlight the need for shifting the paradigm of engineering from that of dominating nature to embracing nature and respecting its limits. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3319–3333, 2016
      PubDate: 2016-07-05T11:40:29.060177-05:
      DOI: 10.1002/aic.15340
  • Nonsmooth model for dynamic simulation of phase changes
    • Authors: Ali M. Sahlodin; Harry A. J. Watson, Paul I. Barton
      Pages: 3334 - 3351
      Abstract: Dynamic modeling of processes involving phase changes can be challenging due to changes in the model equations caused by appearance and disappearance of equilibrium phases. Dynamic simulation of these processes requires the ability to detect the change in the number of phases and adapt the model to the new phase regime on the fly. In this work, an easy‐to‐use nonsmooth model for dynamic simulation of processes with vapor‐liquid equilibrium is presented. The presented model does not introduce any auxiliary variables or equations, nor does it require solution of an optimization problem to determine the new phase regime during the dynamic simulation. It can therefore be used for comprehensive simulation of, e.g., distillation columns, where the number of phases present can change during startup and shutdown. The nonsmooth model is illustrated through examples of an evaporator and a distillation column. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3334–3351, 2016
      PubDate: 2016-07-05T11:30:40.013405-05:
      DOI: 10.1002/aic.15378
  • Uncertainty quantification via bayesian inference using sequential monte
           carlo methods for CO2 adsorption process
    • Authors: Jayashree Kalyanaraman; Yoshiaki Kawajiri, Ryan P. Lively, Matthew J. Realff
      Pages: 3352 - 3368
      Abstract: This work presents the uncertainty quantification, which includes parametric inference along with uncertainty propagation, for CO2 adsorption in a hollow fiber sorbent, a complex dynamic chemical process. Parametric inference via Bayesian approach is performed using Sequential Monte Carlo, a completely parallel algorithm, and the predictions are obtained by propagating the posterior distribution through the model. The presence of residual variability in the observed data and model inadequacy often present a significant challenge in performing the parametric inference. In this work, residual variability in the observed data is handled by three different approaches: (a) by performing inference with isolated data sets, (b) by increasing the uncertainty in model parameters, and finally, (c) by using a model discrepancy term to account for the uncertainty. The pros and cons of each of the three approaches are illustrated along with the predicted distributions of CO2 breakthrough capacity for a scaled‐up process. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3352–3368, 2016
      PubDate: 2016-07-05T11:35:33.247043-05:
      DOI: 10.1002/aic.15381
  • Polymorph selection by continuous crystallization
    • Authors: Thomas C. Farmer; Corinne L. Carpenter, Michael F. Doherty
      Pages: 3505 - 3514
      Abstract: This article is motivated by a remarkable observation reported recently by Myerson, Trout, and co‐workers that continuous crystallization is capable of producing metastable polymorphs in stable steady‐state operation. We explain why this phenomenon occurs and give simple design rules for reproducing it in other polymorphic systems. A linear stability analysis gives simple functions of parameters for which one can continuously produce thermodynamically metastable products based only on the relative polymorph dynamics. We demonstrate agreement with two sets of experimental data; L‐glutamic acid grown from aqueous solution and p‐aminobenzoic acid also grown from aqueous solution. For many polymorphic compounds, engineering a process to produce a desired polymorph is as simple as finding a reasonable operating point for the continuous mixed‐suspension mixed‐product removal crystallization process (temperature, residence time, initial supersaturation, etc.) according to the rules reported in this article. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3505–3514, 2016
      PubDate: 2016-06-24T14:45:31.749533-05:
      DOI: 10.1002/aic.15343
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016