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You searched for: Publication Year 2019 Remove constraint Publication Year: 2019 Subject process design Remove constraint Subject: process design Subject case studies Remove constraint Subject: case studies
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1. 110th Anniversary: A Case Study on Developing Accurate and Reliable Excess Gibbs Energy Correlations for Industrial Application

Author:
Paul M. Mathias
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.28 pp. 12465-12477
ISSN:
1520-5045
Subject:
Gibbs free energy; alcohols; algorithms; automation; case studies; chemistry; computer software; industrial applications; process design; theoretical models
Abstract:
... Excess Gibbs energy (Gᴱ) or activity-coefficient models have a strong niche in applied thermodynamics since they provide an effective method to correlate and estimate phase equilibrium for nonideal systems. The history of their development is well represented by many papers in the technical literature, and notably in the five score and ten years of publications in Industrial & Engineering Chemistr ...
DOI:
10.1021/acs.iecr.9b01624

2. 110th Anniversary: Modeling and Optimization of a Butyl Glycol Ether Plant Based on an Experimental Kinetic Study

Author:
Seonghwan Choi; Junkyo Jeong; Chan Yeong Yun; Sora Hwang; Jay H. Lee
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.29 pp. 13260-13273
ISSN:
1520-5045
Subject:
case studies; diethylene glycol; econometric models; economic feasibility; manufacturing; process design; reaction kinetics; simulation models; triethylene glycol
Abstract:
... A simulation model is developed to estimate the production of four products (butyl monoethylene glycol ether, butyl diethylene glycol ether, butyl triethylene glycol ether, and butyl polyethylene glycol ether) in a glycol ether plant and to predict the amount of utilities consumed by the manufacturing units. To ensure the broad applicability of the developed model, a reaction kinetics model is req ...
DOI:
10.1021/acs.iecr.9b02490

3. Bioethanol Production From Turkish Hazelnut Husk Process Design and Economic Evaluation

Author:
Nihat Alpagu Sayar; Orkun Pinar; Dilek Kazan; Ahmet Alp Sayar
Source:
Waste and biomass valorization 2019 v.10 no.4 pp. 909-923
ISSN:
1877-2641
Subject:
Corylus colurna; agricultural wastes; biocatalysts; bioethanol; bioprocessing; case studies; economic evaluation; economic incentives; economic investment; environmental impact; ethanol; ethanol production; evaporation; hazelnuts; hulls; lignocellulose; nitrogen; operating costs; prices; process design; risk factors; sales; uncertainty analysis; Turkey (country)
Abstract:
... The main objective of the current study is to develop and assess the preliminary synthetic design steps of an innovative and unprecedented bioprocess plant converting Turkish hazelnut husk into lignocellulosic ethanol with an emphasis on economic evaluation. Valorization of this agricultural waste would provide a promising economic potential and long-term sustainability with acceptable environment ...
DOI:
10.1007/s12649-017-0103-y

4. Cavitationally Driven Transformations: A Technique of Process Intensification

Author:
Chandrakant R. Holkar; Ananda J. Jadhav; Dipak V. Pinjari; Aniruddha B. Pandit
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.15 pp. 5797-5819
ISSN:
1520-5045
Subject:
case studies; cost effectiveness; crystallization; depolymerization; disinfection; emulsifying; energy; heat transfer; mixing; process design; product quality; wastes; wastewater treatment
Abstract:
... The process intensification (PI) can significantly improve energy and process efficiency by enhancing mixing, mass, and heat transfer as well as driving forces. There are several benefits of such improvements, which include energy and cost savings, enhanced safety, smaller reactor size, less waste generation, and higher product quality. This review article focuses on the PI, discussion about its d ...
DOI:
10.1021/acs.iecr.8b04524

5. Comparison between multiresponse‐robust process design and numerical optimization: A case study on baking of fermented chickpea flour‐based wheat bread

Author:
Snehasis Chakraborty; Chandrima Shrivastava
Source:
Journal of food process engineering 2019 v.42 no.3 pp. e13008
ISSN:
0145-8876
Subject:
algorithms; bakery industry; baking; breads; case studies; chickpeas; color; cost effectiveness; hardness; loaves; neural networks; principal component analysis; process design; relative humidity; response surface methodology; staple foods; temperature; texture
Abstract:
... The baking conditions (relative humidity, baking time, and temperature) for a fermented chickpea flour‐based wheat bread were optimized considering multiple responses: crumb hardness, specific loaf volume, color change in crust and crumb. Rotatable central composite design was applied within the baking domain of 175–225 °C/13–22 min/45–95% RH. An intelligent and robust technique based on Taguchi f ...
DOI:
10.1111/jfpe.13008

6. The Complex Way to Sustainability: Petroleum-Based Processes versus Biosynthetic Pathways in the Formation of C4 Chemicals from Syngas

Author:
I. Katharina Stoll; Nikolaos Boukis; Anke Neumann; Katrin Ochsenreither; Thomas A. Zevaco; Jörg Sauer
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.35 pp. 15863-15871
ISSN:
1520-5045
Subject:
biochemical pathways; biomass; carbon dioxide; case studies; chemical industry; environmental impact; environmental law; feedstocks; greenhouse gas emissions; petroleum; process design; synthesis gas; wastes
Abstract:
... The environmental impact of the increasing anthropogenic CO₂ emissions and the depletion of essential resources, once subjects of concern only for a minority of specialists, are now in the focus of many institutions and are de facto top priorities in many agendas. The ensuing environmental regulations, improved safety requirements, and growing critical public view on the chemical industry are the ...
DOI:
10.1021/acs.iecr.9b01123

7. Computer-Generated Kinetics for Coupled Heterogeneous/Homogeneous Systems: A Case Study in Catalytic Combustion of Methane on Platinum

Author:
Katrin Blondal; Jelena Jelic; Emily Mazeau; Felix Studt; Richard H. West; C. Franklin Goldsmith
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.38 pp. 17682-17691
ISSN:
1520-5045
Subject:
case studies; catalysts; catalytic activity; combustion; databases; density functional theory; gases; methane; platinum; prediction; process design; thermodynamics
Abstract:
... The automatic microkinetic mechanism generator for heterogeneous catalysis, RMG-Cat, has been extensively updated. Density functional theory calculations were performed for 69 adsorbates on Pt(111), and the resulting thermodynamic properties were added to RMG-Cat. The thermo database is significantly more accurate; it includes nitrogen-containing adsorbates for the first time as well as better cap ...
DOI:
10.1021/acs.iecr.9b01464

8. Constrained Version of the Dynamic Response Surface Methodology for Modeling Pharmaceutical Reactions

Author:
Yachao Dong; Christos Georgakis; Jason Mustakis; Joel M. Hawkins; Lu Han; Ke Wang; Jonathan P. McMullen; Shane T. Grosser; Kevin Stone
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13611-13621
ISSN:
1520-5045
Subject:
case studies; data collection; experimental design; models; prediction; process design; response surface methodology
Abstract:
... The Dynamic Response Surface Methodology (DRSM; Klebanov, N.; Georgakis, C. Ind. Eng. Chem. Res2016, 55, 4022) is a data-driven modeling methodology for time-resolved measurements from Design of Experiments data sets. To extend its use to semi-infinite domains, a second version was proposed (Wang, Z. Y.; Georgakis, C. Ind. Eng. Chem. Res2017, 56, 10770), which uses an exponential transformation of ...
DOI:
10.1021/acs.iecr.9b00731

9. Data-Driven Plant-Wide Control Performance Monitoring

Author:
David Zumoffen; Lautaro Braccia; Patricio Luppi
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.16 pp. 6576-6591
ISSN:
1520-5045
Subject:
case studies; issues and policy; least squares; models; monitoring; process design; systems engineering
Abstract:
... In this work a new data-driven plant-wide control performance monitoring methodology is proposed. The main constitutive parts of the suggested method are based on three well-known research areas from process systems engineering (PSE): (1) the sum of squared deviations (SSD) concepts from the plant-wide control design topic, (2) the partial least-squares (PLS) modeling technique from the multivaria ...
DOI:
10.1021/acs.iecr.8b06293

10. A Debottlenecking Study of an Industrial Pharmaceutical Batch Plant

Author:
Franz D. Bähner; Jakob K. Huusom
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.43 pp. 20003-20013
ISSN:
1520-5045
Subject:
algorithms; business enterprises; case studies; equipment; information processing; models; process design; process monitoring; systems engineering
Abstract:
... Operational complexity in batch-operated plants is large, and companies struggle to produce at high equipment utilization. Owing to high fixed costs, capacity utilization is an important operational directive. Many current plants are not in a state that allows the application of rigorous process systems engineering tools due to modeling challenges. This work proposes identifying the right engineer ...
DOI:
10.1021/acs.iecr.9b03134

11. A Deep Learning Approach for Process Data Visualization Using t-Distributed Stochastic Neighbor Embedding

Author:
Wenbo Zhu; Zachary T. Webb; Kaitian Mao; José Romagnoli
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.22 pp. 9564-9575
ISSN:
1520-5045
Subject:
artificial intelligence; case studies; process design; pyrolysis; stochastic processes
Abstract:
... A generic process visualization method is introduced, which visualizes real-time process information and correlations among variables on a 2D map using parametric t-SNE. As an unsupervised learning method, it learns the mapping by minimizing the Kullback–Leibler divergence between the original high-dimensional space and the latent space using a deep neural network. In practice, it is observed that ...
DOI:
10.1021/acs.iecr.9b00975

12. Design of Spherical Crystallization for Drugs Based on Thermal-Induced Liquid–Liquid Phase Separation: Case Studies of Water-Insoluble Drugs

Author:
Mengmeng Sun; Du Shichao; Weiwei Tang; Lina Jia; Junbo Gong
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.44 pp. 20401-20411
ISSN:
1520-5045
Subject:
agitation; case studies; cooling; crystallization; crystals; droplet size; droplets; ibuprofen; oils; process design; separation; solvents; surfactants
Abstract:
... Spherical crystallization of water-insoluble drugs was investigated based on thermal-induced liquid–liquid phase separation (TILLPS) without the use of organic solvent. The phase diagram of the drug in water was constructed first, consisting of solid–liquid and liquid–liquid equilibrium regions. Within the liquid–liquid phase region, droplets of the solute-rich phase were formed and dispersed unde ...
DOI:
10.1021/acs.iecr.9b03795

13. Development of a Refined RTD-Based Efficiency Prediction Model for Cross-Flow Trays

Author:
Vineet Vishwakarma; Markus Schubert; Uwe Hampel
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.8 pp. 3258-3268
ISSN:
1520-5045
Subject:
case studies; fluid mechanics; liquids; model validation; models; process design; vapors
Abstract:
... The present work describes the mathematical formulation of a new tray efficiency model through refinement of the conventional residence time distribution (RTD) approach [Foss et al. AIChE J.1958, 4(2), 231−239]. Geometrical partitioning of a tray into compartments along the main liquid flow direction is a prerequisite in the new model. This partitioning allows computation of the tray efficiency th ...
DOI:
10.1021/acs.iecr.8b04672

14. Distributed Estimation and Nonlinear Model Predictive Control Using Community Detection

Author:
Davood B. Pourkargar; Manjiri Moharir; Ali Almansoori; Prodromos Daoutidis
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13495-13507
ISSN:
1520-5045
Subject:
alkylation; benzene; case studies; ethylene; graphs; nonlinear models; process design
Abstract:
... A combined distributed moving horizon estimation and distributed model predictive control architecture is proposed to address the distributed output–feedback control problem for nonlinear process systems. Community detection based on modularity maximization is used to generate separate optimal decompositions for the estimation and control problems on the basis of suitable graphs. The process of be ...
DOI:
10.1021/acs.iecr.9b00820

15. Economic and Environmental Assessment of Gas Supply Chains Incorporating Shale Gas

Author:
Josselin Colin-Robledo; Sergio Iván Martínez-Guido; Roberto Guerra-González; Luis Fernando Lira-Barragán; José María Ponce-Ortega
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.41 pp. 19122-19134
ISSN:
1520-5045
Subject:
case studies; energy costs; environmental assessment; environmental impact; hydraulic fracturing; income; markets; natural gas; process design; profits and margins; shale; shale gas; supply chain; transportation; Mexico
Abstract:
... This paper presents a mathematical programing formulation for synthesizing natural gas supply chains incorporating shale gas. The proposed formulation maximizes the profits and at the same time deals with the minimization of the overall environmental impact. The objective function is aimed at the maximization of the total profit, which accounts for the income obtained by selling shale, conventiona ...
DOI:
10.1021/acs.iecr.9b03157

16. Evaluation Methods of Adsorbents for Air Purification and Gas Separation at Low Concentration: Case Studies on Xenon and Krypton

Author:
Arnaud Monpezat; Sylvain Topin; Ludovic Deliere; David Farrusseng; Benoit Coasne
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.11 pp. 4560-4571
ISSN:
1520-5045
Subject:
adsorbents; adsorption; air; carbon; case studies; krypton; pollutants; process design; uncertainty; xenon; zeolites
Abstract:
... The development of gas separation processes dealing with very low concentration ranges is a rapidly growing domain with key applications such as trace detection, air purification from harmful pollutants, etc. Yet, the design of efficient technologies in this field is hampered by the lack of robust strategies to predict the gas selectivity of optimal adsorbents from simple pure gas adsorption data. ...
DOI:
10.1021/acs.iecr.8b04866

17. Experimental Design for Batch-to-Batch Optimization under Model-Plant Mismatch

Author:
Rubin Hille; Hector M. Budman
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13599-13610
ISSN:
1520-5045
Subject:
algorithms; case studies; experimental design; issues and policy; models; prediction; process design
Abstract:
... Model errors in model-based optimization procedures can result in suboptimal policies. In that regard, structural mismatch is of particular concern since it results in inaccurate model predictions even when a large amount of data is available for model calibration. The method of simultaneous identification and optimization, proposed in our previous work, addresses the structural model mismatch by ...
DOI:
10.1021/acs.iecr.9b00105

18. Finding Better Limit Cycles in Semicontinuous Distillation. 2. Extended Back-Stepping Design Methodology

Author:
Pranav Bhaswanth Madabhushi; Thomas A. Adams
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.36 pp. 16667-16675
ISSN:
1520-5045
Subject:
case studies; distillation; methanol; principal component analysis; process design
Abstract:
... In Part 1 [Madabhushi and Adams Ind. Eng. Chem. Res.2019, 10.1021/acs.iecr.9b02639] of this work, we introduced a new design procedure, called the back-stepping design methodology, for the design of zeotropic ternary semicontinuous distillation systems using the aspenONE Engineering suite. The objective of this paper (Part 2) is to present an extended back-stepping design methodology for certain c ...
DOI:
10.1021/acs.iecr.9b03519

19. Finite Adaptability in Data-Driven Robust Optimization for Production Scheduling: A Case Study of the Ethylene Plant

Author:
Wei Feng; Yi Zhang; Gang Rong; Yiping Feng
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.16 pp. 6505-6518
ISSN:
1520-5045
Subject:
case studies; cost effectiveness; ethylene; fuels; process design; system optimization; uncertainty
Abstract:
... A novel adaptive robust optimization methodology called Pareto optimal finite adaptability (POFA) is proposed for production scheduling of the ethylene plant. As an improvement to conventional robust optimization methods, POFA exhibits high efficacy dealing with multiple evolution paths caused by possible decoking decisions. With the introduction of adjustable variables, both continuous and discre ...
DOI:
10.1021/acs.iecr.8b05119

20. Framework for Design Under Uncertainty Including Inherent Safety, Environmental Assessment, and Economic Performance of Chemical Processes

Author:
Andrea P. Ortiz-Espinoza; Vasiliki Kazantzi; Fadwa T. Eljack; Arturo Jiménez-Gutiérrez; Mahmoud M. El-Halwagi; Nikolaos K. Kazantzis
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.29 pp. 13239-13248
ISSN:
1520-5045
Subject:
Monte Carlo method; case studies; economic performance; environmental assessment; ethylene production; models; natural gas; process design; risk; uncertainty
Abstract:
... Typically, analysis and design of chemical processes is carried out considering average values of inherently uncertain data that pertain to key design and process variables that shape its performance. In this work, a methodology that includes uncertainty in process safety, an item commonly addressed after the final design has been achieved, along with environmental and economic metrics of the proc ...
DOI:
10.1021/acs.iecr.9b02349

21. Improvements to the T² Statistic for Multivariate Fault Detection

Author:
Lijia Luo; Man Xu; Shiyi Bao; Jianfeng Mao; Chudong Tong
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.45 pp. 20692-20709
ISSN:
1520-5045
Subject:
case studies; monitoring; process design; product quality; statistics
Abstract:
... Multivariate fault detection has been a requirement in various industrial systems to ensure safe operations and to improve product quality. The T² statistic is a widely used fault detection index for monitoring unusual changes in the mean of multivariate data. In spite of its advantages, the T² statistic also suffers from amplification and masking effects, especially when the number of variables t ...
DOI:
10.1021/acs.iecr.9b04112

22. Integrated Approach of Safety, Sustainability, Reliability, and Resilience Analysis via a Return on Investment Metric

Author:
Kariana Moreno-Sader; Prerna Jain; Luis Carlos Ballestas Tenorio; M. Sam Mannan; Mahmoud M. El-Halwagi
Source:
ACS sustainable chemistry & engineering 2019 v.7 no.24 pp. 19522-19536
ISSN:
2168-0485
Subject:
case studies; costs and returns; decision making; economic factors; process design
Abstract:
... The process design and technology selection are driven by multiple objectives including technical, economic, environmental, safety, and resilience drivers. Traditionally, techno-economic analyses have been used to select and optimize the process design. Subsequently, environmental, safety, and resilience issues have been included in post-design analysis. With the recognition of the importance of i ...
DOI:
10.1021/acssuschemeng.9b04608

23. Integrated Proactive and Reactive Scheduling for Refinery Front-End Crude Movement with Consideration of Unit Maintenance

Author:
Honglin Qu; Sujing Wang; Qiang Xu
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.27 pp. 12192-12206
ISSN:
1520-5045
Subject:
case studies; chemistry; distillation; mixing; models; operating costs; process design; tanks
Abstract:
... A typical front-end crude supply process of refineries encompasses many units, such as vessels, port-side storage tanks, long-distance pipeline, refinery-side charging tanks, and crude distillation units. In reality, the performance of these units will inevitably decay; thus, unit maintenance plans should be well integrated with normal crude movement schedules. In this paper, a novel methodology h ...
DOI:
10.1021/acs.iecr.9b02449

24. Integrated Scheduling of Production and Maintenance for Continuous Plants: Conditional Sequencing and Approximate Modeling of Storage

Author:
Rohit Omar; Munawar A. Shaik
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.41 pp. 19100-19121
ISSN:
1520-5045
Subject:
case studies; inventories; issues and policy; models; process design; tanks
Abstract:
... In this study, we present extensions of earlier models for integrated scheduling of optimal production and planned maintenance for continuous and semicontinuous plants to account for different storage requirements. For handling finite storage, we propose approximate modeling of storage (without loss of generality) based on conditional sequencing without considering storage as a separate task. For ...
DOI:
10.1021/acs.iecr.9b01984

25. Integrating Mass and Energy through the Anchor-Tenant Approach for the Synthesis of Carbon-Hydrogen-Oxygen Symbiosis Networks

Author:
Kevin Topolski; Luis Fernando Lira-Barragán; Marc Panu; José María Ponce-Ortega; Mahmoud M. El-Halwagi
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.36 pp. 16761-16776
ISSN:
1520-5045
Subject:
carbon; case studies; energy; heat; hydrogen; infrastructure; natural resources conservation; oxygen; pollution; pollution control; process design; symbiosis
Abstract:
... The concept of eco-industrial parks (EIPs) for integrating resources and infrastructure among several adjacent plants offers synergistic opportunities that can lead to enhanced profit, reduced pollution, and increased conservation of natural resources. A special class of EIPs, carbon-hydrogen-oxygen symbiosis networks (CHOSYNs), has been recently introduced for integrating hydrocarbon processing p ...
DOI:
10.1021/acs.iecr.9b02622

26. Internal Modifier Adaptation for the Optimization of Large-Scale Plants with Inaccurate Models

Author:
Aris Papasavvas; Gregory Francois
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13568-13582
ISSN:
1520-5045
Subject:
case studies; models; process design
Abstract:
... Modifier adaptation (MA) methods are iterative model-based real-time optimization (RTO) methods with the proven ability to reach, upon converge, the unknown optimal steady-state operating conditions of a plant despite plant–model mismatch and disturbances. So far, MA has been applied to small-scale but never—to the best of the authors’ knowledge—to large-scale systems, the optimization of which be ...
DOI:
10.1021/acs.iecr.9b00246

27. Investigation of Inherently Safer Design Through Process Intensification: Novel Safety Assessment Methodology and Case Study in C₃–Alkyne Hydrogenation Distillation Process

Author:
Meng Qi; Jiayong Zhu; Jiaming Xu; Dongfeng Zhao; Yi Liu
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.12 pp. 4866-4880
ISSN:
1520-5045
Subject:
accidents; case studies; cost effectiveness; distillation; economic impact; hydrogenation; process design; quantitative risk assessment; risk; safety assessment
Abstract:
... Inherently Safer Design (ISD) describes a strategy that reduces and even eliminates inherent hazards in processes. However, ISD principles improving inherent safety always involves tradeoffs between these two competing factors: safety and costs. In inherent safety aspects, process intensification (PI), one of the methodologies in ISD, aims to eliminate units and simplify the process. Therefore, sy ...
DOI:
10.1021/acs.iecr.8b04854

28. Involving Acceptability in the Optimal Synthesis of Water Networks in Eco-Industrial Parks

Author:
Guillermo Aguilar-Oropeza; Eusiel Rubio-Castro; José María Ponce-Ortega
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.6 pp. 2268-2279
ISSN:
1520-5045
Subject:
case studies; equations; equipment; industry; mathematical models; process design; wastewater; water requirement; water reuse; water treatment
Abstract:
... This paper proposes a superstructure that considers the recycling and reuse of water in an eco-industrial park, where different industries share wastewater as well as a treatment system to meet their water needs in their process units. The involved flows as well as the treatment system are optimization variables, and the objective is to synthesize the network that allows satisfying water requireme ...
DOI:
10.1021/acs.iecr.8b04419

29. Joint Structure Preserving Embedding Model and Its Application for Process Monitoring

Author:
Yuanjian Fu; Chaomin Luo
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.45 pp. 20667-20679
ISSN:
1520-5045
Subject:
case studies; geometry; learning; models; principal geodesic analysis; process design; process monitoring
Abstract:
... Currently, dimensionality reduction methods based on manifold learning are widely applied to industrial process monitoring. However, considering that a number of manifold-based monitoring methods extract only the global geometric information of the original data or the local manifold structure of the neighboring data points, in this article, a novel dimensionality reduction method called joint str ...
DOI:
10.1021/acs.iecr.9b03077

30. Key issues and novel optimization approaches of industrial waste heat recovery in district heating systems

Author:
Jingyi Wang; Zhe Wang; Ding Zhou; Kaiyu Sun
Source:
Energy 2019 v.188 pp. 116005
ISSN:
0360-5442
Subject:
case studies; exergy; heat pumps; industrial wastes; process design; system optimization; waste heat recovery
Abstract:
... Large amount of low-grade waste heat is discharged into the environment during industrial processes. This part of waste heat can be collected to serve district heating systems as an important heat source. In most studies of industrial waste heat recovery, the proposed system simulations were unsophisticated in terms of analyzing the real processes. For this reason, the tangency analysis has recent ...
DOI:
10.1016/j.energy.2019.116005

31. Model Learning Predictive Control for Batch Processes: A Reactive Batch Distillation Column Case Study

Author:
Alejandro Marquez-Ruiz; Marco Loonen; M. Bahadır Saltık; Leyla Özkan
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13737-13749
ISSN:
1520-5045
Subject:
batch systems; case studies; distillation; models; process design
Abstract:
... In this paper, we present the control of batch processes using model predictive control (MPC) and iterative learning control (ILC). Existing combinations of MPC and ILC are based on learning of the inputs of the process from previous batches for a fixed linear time-invariant model (LTI). However, batch processes are inherently time varying; therefore, LTI models are limited in capturing the releva ...
DOI:
10.1021/acs.iecr.8b06474

32. Modeling and Simulation of a Piston-Type Work Exchanger for Mechanical Energy Recovery

Author:
Aida Amini-Rankouhi; Yinlun Huang
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.39 pp. 18292-18300
ISSN:
1520-5045
Subject:
case studies; energy recovery; gases; heat; industry; models; process design; thermal energy
Abstract:
... Heat and work are two common forms of energy. Over past decades, thermal energy recovery via heat integration has been very successful in the process industry. Recovery of mechanical energy, however, has not drawn sufficient attention until recently. It is shown that mechanical energy can be recovered systematically through integrating work exchange networks in plants. It is conceived that the pre ...
DOI:
10.1021/acs.iecr.9b03446

33. A New Method for Alarm Monitoring of Equipment Start-Up Operations with Applications to Pumps

Author:
Boyuan Zhou; Wenkai Hu; Tongwen Chen
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.26 pp. 11251-11260
ISSN:
1520-5045
Subject:
algorithms; case studies; chemistry; monitoring; process design; pumps
Abstract:
... In practice, alarms configured for steady operating states often become a nuisance during the start-up operation of industrial equipment. As a result, they not only distract plant operators, but may also cause worse consequences, such as pump trips. Motivated by such as a practical problem, this paper presents a new alarm monitoring method for equipment start-up operations. The proposed method is ...
DOI:
10.1021/acs.iecr.8b05940

34. Novel Distributed Alarm Visual Analysis Using Multicorrelation Block-Based PLS and Its Application to Online Root Cause Analysis

Author:
Qun-Xiong Zhu; Yi Luo; Yan-Lin He
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.45 pp. 20655-20666
ISSN:
1520-5045
Subject:
alarm systems; case studies; least squares; models; process design; process monitoring
Abstract:
... Process monitoring and alarm systems play an important role in production safety. Distributed alarm systems have been utilized to effectively reduce the burden of data calculations, contributing to fast-track root causes of alarms. However, the traditional distributed contribution analysis method cannot be well applied to online monitoring in time. In addition, the correlation-based variable recon ...
DOI:
10.1021/acs.iecr.9b02963

35. Online Model Maintenance via Output Modifier Adaptation

Author:
José Matias; Johannes Jäschke
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13750-13766
ISSN:
1520-5045
Subject:
algorithms; case studies; models; oil fields; process design
Abstract:
... This paper describes a method for selecting and adapting the model structure online while running together with a real-time optimization algorithm using Output Modifier Adaptation. The method chooses, among several knowledge-based models, the model structure that is most consistent with the current process data. By allowing the model to change over time, its structure and complexity are able to ad ...
DOI:
10.1021/acs.iecr.9b00267

36. Online Process Optimization with Active Constraint Set Changes using Simple Control Structures

Author:
Dinesh Krishnamoorthy; Sigurd Skogestad
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13555-13567
ISSN:
1520-5045
Subject:
case studies; models; process design
Abstract:
... The purpose of this paper is to show that online process optimization can be achieved using simple control structures without the need for solving numerical optimization problems online. In particular, we show that changes in active constraint regions can be handled using simple logics such as selectors, without needing to identify the exact location of the active constraint regions a priori, nor ...
DOI:
10.1021/acs.iecr.9b00308

37. Process Monitoring Based on Orthogonal Locality Preserving Projection with Maximum Likelihood Estimation

Author:
Jingxin Zhang; Maoyin Chen; Hao Chen; Xia Hong; Donghua Zhou
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.14 pp. 5579-5587
ISSN:
1520-5045
Subject:
algorithms; case studies; process design; process monitoring; statistical analysis
Abstract:
... By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP–MLE (orthogonal locality preserving projection-maximum likelihood estimation), is introduced for process monitoring. OLPP is utilized for dimensionality reduction, which provides better locality preserving power than locality preserving projection. Then, t ...
DOI:
10.1021/acs.iecr.8b05875

38. Real-Time Semisupervised Predictive Modeling Strategy for Industrial Continuous Catalytic Reforming Process with Incomplete Data Using Slow Feature Analysis

Author:
Chao Jiang; Weimin Zhong; Zhi Li; Xin Peng; Minglei Yang
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.37 pp. 17406-17423
ISSN:
1520-5045
Subject:
Bayesian theory; algorithms; aromatic hydrocarbons; case studies; catalytic activity; chemical reactions; data collection; gasoline; mixing; models; octane; oil and gas industry; petroleum; prediction; principal component analysis; process design; temporal variation; variance
Abstract:
... The catalytic naphtha reforming process is one of the most significant processes in the petrochemical industry. This process is notable for its function of transforming petroleum refinery naphtha from crude oil with low octane ratings into high-octane premium blending stocks, namely, gasoline or aromatic hydrocarbons. This process consists of many units along with complicated chemical reactions, w ...
DOI:
10.1021/acs.iecr.9b03119

39. Recursive Gaussian Mixture Models for Adaptive Process Monitoring

Author:
Junhua Zheng; Qiaojun Wen; Zhihuan Song
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.16 pp. 6551-6561
ISSN:
1520-5045
Subject:
Bayesian theory; batch systems; case studies; models; probability; process design; process monitoring; variance covariance matrix
Abstract:
... Gaussian mixture models (GMM) have recently been introduced and widely used for process monitoring. This paper intends to develop a new recursive GMM model for adaptive monitoring of processes under time-varying conditions. Two model updating schemes with/without forgetting factors are both proposed. Bayesian inference probability index is used as the monitoring statistic in both of the continuous ...
DOI:
10.1021/acs.iecr.8b06101

40. Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection

Author:
Agustín Bottari; Pablo A. Marchetti; Alejandro G. Marchetti
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13699-13717
ISSN:
1520-5045
Subject:
case studies; economic performance; financial economics; process design
Abstract:
... The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off f ...
DOI:
10.1021/acs.iecr.8b06296

41. Simultaneous Estimation of Hidden State and Unknown Input Using Expectation Maximization Algorithm

Author:
Mohammad Aminul Islam Khan; Syed Ahmad Imtiaz; Faisal Khan
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.26 pp. 11553-11565
ISSN:
1520-5045
Subject:
Bayesian theory; algorithms; case studies; chemistry; probability; process design
Abstract:
... An expectation maximization (EM) algorithm-based simultaneous state and input estimator for nonlinear systems is developed. This study uses a Bayesian solution to estimate the states and unknown inputs simultaneously. It was assumed that a joint distribution between states and inputs exists. The joint distribution was estimated sequentially using an EM algorithm. The EM algorithm has two steps: ex ...
DOI:
10.1021/acs.iecr.8b06091

42. Sparse Robust Principal Component Analysis with Applications to Fault Detection and Diagnosis

Author:
Lijia Luo; Shiyi Bao; Chudong Tong
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.3 pp. 1300-1309
ISSN:
1520-5045
Subject:
case studies; models; principal component analysis; process design; process monitoring; variance covariance matrix
Abstract:
... Principal component analysis (PCA) is a popular method for modeling and analysis of high-dimensional data. In spite of its advantages, classical PCA also has two drawbacks. First, it is very sensitive to outliers in the data. Second, it cannot yield interpretable PCs because most of the loadings are nonzero. To overcome these drawbacks, we propose a new PCA method that has the properties of robust ...
DOI:
10.1021/acs.iecr.8b04655

43. Unified Heat Exchanger Network Synthesis via a Stageless Superstructure

Author:
Sajitha K. Nair; Iftekhar A. Karimi
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.15 pp. 5984-6001
ISSN:
1520-5045
Subject:
algorithms; case studies; cold; heat exchangers; models; process design
Abstract:
... The existing mathematical programming-based methods for simultaneous heat exchanger network synthesis (HENS) have used either match-centric or stage-centric superstructures. Most works over the past four decades have primarily used various modifications of essentially two superstructures whose configurational limitations are well established. We revisit a novel, promising, but unsuccessful, exchan ...
DOI:
10.1021/acs.iecr.8b04490

44. Application of Fuzzy Optimization to Bioenergy-Supply-Chain Planning under Epistemic Uncertainty: A New Approach

Author:
Reza Babazadeh
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.16 pp. 6519-6536
ISSN:
1520-5045
Subject:
biodiesel; case studies; combustion; decision making; fossil fuels; models; planning; process design; social problems; supply chain; transportation industry; uncertainty; Iran
Abstract:
... Recently, finding sustainable solutions to deal with the environmental and social problems emerging from the combustion of fossil fuels in the transportation sector has attracted much interest. This paper proposes an integrated, multiperiod, mixed-integer, nonlinear programming model to design a biodiesel supply-chain network under uncertainty. To deal with the uncertainty of the parameters of the ...
DOI:
10.1021/acs.iecr.8b05617

45. Applications of Advanced Analytics at Saudi Aramco: A Practitioners’ Perspective

Author:
Rohit S. Patwardhan; Hamza A. Hamadah; Kalpesh M. Patel; Rayan H. Hafiz; Majid M. Al-Gwaiz
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.26 pp. 11338-11351
ISSN:
1520-5045
Subject:
artificial intelligence; assets; case studies; chemistry; neural networks; process design; spectral analysis; time series analysis
Abstract:
... The well-instrumented process industry collects vast amounts of structured and unstructured data from its assets in real time. Some of this data gets stored as conventional time series data, while some is processed to generate alarms, alerts, and other types of unstructured data. Managing this big data which is rich in diversity, volume, veracity, and velocity, to generate actionable insights is a ...
DOI:
10.1021/acs.iecr.8b06205

46. Centralized and distributed food manufacture: A modeling platform for technological, environmental and economic assessment at different production scales

Author:
A. Almena; P.J. Fryer; S. Bakalis; E. Lopez-Quiroga
Source:
Sustainable Production and Consumption 2019 pp. -
ISSN:
2352-5509
Subject:
case studies; economic analysis; food storage; food transport; infant foods; manufacturing; models; process design; social benefit; supply chain; transportation; United Kingdom
Abstract:
... Centralized manufacturing methods have been increasingly implemented in the food manufacturing sector. Proving to be more efficient in terms of production, centralization also involve rigid and lengthy supply chains with high both environmental and cost impacts. Distributed manufacturing, based on local production at small scale, represents an alternative that could provide flexibility to the curr ...
DOI:
10.1016/j.spc.2019.03.001

47. Computer-Aided Polymer Design: Integrating Group Contribution and Molecular Dynamics

Author:
Xinyuan Liang; Xiang Zhang; Lei Zhang; Linlin Liu; Jian Du; Xiuling Zhu; Ka Ming Ng
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.34 pp. 15542-15552
ISSN:
1520-5045
Subject:
algorithms; case studies; manufacturing; models; molecular dynamics; molecular weight; polymers; prediction; process design; system optimization; tires
Abstract:
... Polymers are widely used to manufacture many chemical products. Often, polymers are designed by trial-and-error, which is expensive and time-consuming. In this work, a new optimization-based computer-aided polymer design (CAPD) framework with a tailored algorithm is proposed to facilitate the design of polymers with desired properties. Considering the inaccuracy of traditional group contribution m ...
DOI:
10.1021/acs.iecr.9b02769

48. Decision-Making for Sustainability Enhancement of Chemical Systems under Uncertainties: Combining the Vector-Based Multiattribute Decision-Making Method with Weighted Multiobjective Optimization Technique

Author:
Di Xu; Weichen Li; Weifeng Shen; Lichun Dong
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.27 pp. 12066-12079
ISSN:
1520-5045
Subject:
case studies; chemistry; decision making; process design; uncertainty
Abstract:
... The identification of the best solution for improving the sustainability of chemical systems is quite challenging because multiple objectives have to be considered and the trade-offs among the objectives must be addressed. This study aims to develop a novel framework to simplify multiobjective optimization (MOO) problems by incorporating a vector-based multiattribute decision-making (MADM) method. ...
DOI:
10.1021/acs.iecr.9b01531

49. Developing stakeholder-driven scenarios on land sharing and land sparing – Insights from five European case studies

Author:
Katrin Karner; Anna F. Cord; Nina Hagemann; Nuria Hernandez-Mora; Annelie Holzkämper; Bernard Jeangros; Nele Lienhoop; Heike Nitsch; David Rivas; Erwin Schmid; Catharina J.E. Schulp; Michael Strauch; Emma H. van der Zanden; Martin Volk; Barbara Willaarts; Nina Zarrineh; Martin Schönhart
Source:
Journal of environmental management 2019 v.241 pp. 488-500
ISSN:
0301-4797
Subject:
biodiversity; case studies; ecosystem services; empirical research; land use; landscapes; process design; socioeconomics; stakeholders; uncertainty; Austria; Germany; Netherlands; Spain; Switzerland
Abstract:
... Empirical research on land sharing and land sparing has been criticized because preferences of local stakeholders, socio-economic aspects, a bundle of ecosystem services and the local context were only rarely integrated. Using storylines and scenarios is a common approach to include land use drivers and local contexts or to cope with the uncertainties of future developments. The objective of the p ...
DOI:
10.1016/j.jenvman.2019.03.050

50. Dual-Control-Based Approach to Batch Process Operation under Uncertainty Based on Optimality-Conditions Parametrization

Author:
Radoslav Paulen; Miroslav Fikar
Source:
Industrial & engineering chemistry process design and development 2019 v.58 no.30 pp. 13508-13516
ISSN:
1520-5045
Subject:
batch systems; case studies; microfiltration; models; prediction; prices; process design; uncertainty
Abstract:
... This paper presents a scheme for dual robust control of batch processes under parametric uncertainty. The dual-control paradigm arises in the context of adaptive control. A trade-off should be decided between the control actions that (robustly) optimize the plant performance and between those that excite the plant such that unknown plant model parameters can be learned precisely enough to increase ...
DOI:
10.1021/acs.iecr.9b00638