14th International Symposium on Process Systems Engineering

Name: 14th International Symposium on Process Systems Engineering
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Published on 24. June 2022

2298 pages

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9780323853668v1_WEB
Front Cover
14th INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING
Copyright
Contents
Preface
International Program Comittee
Invited Papers and Extended Abstracts
1. Actions toward carbon-neutral society with fuel cell technology
Abstract
Keywords
1. The world trend of carbon neutrality and hydrogen energy
2. Fuel cell development for various applications and usages
3. Collaboration for developing fuel cells and expectations for PSE
Conclusions
References
2. Challenges and Opportunities for Process Systems Engineering in a Changed World
Abstract
Keywords
1. Introduction
2. PSE methods and tools
2.1. Methods
2.1.1. Modelling
2.1.2. Numerical solvers
2.1.3. Algorithms
2.2. Computer-aided tools
3. Challenges and roles of PSE
3.1. Sustainable process networks
3.2. Chemical process safety
3.3. Health and pharma sector
3.4. Chemicals based products and their substitution
4. Perspectives (Opportunities)
5. Conclusions
References
3. PSE Tools and Challenges in the Development of Advanced Pharmaceutical Manufacturing
Abstract
Keywords
1. Introduction
2. Application in solid-based drug and biologics manufacturing
Acknowledgement
References
4. Experience and Perspectives on our Journey towards Deep Decarbonization
Abstract
Keywords
1. Introduction
2. Reduce
3. Recycle / Reuse
4. Replace
5. Conclusions
Acknowledgements
References
5. Surrogate Modeling and Surrogate-Based Optimization with Stochastic Simulations
Abstract
Keywords
1. Introduction
2. Framework for Training Surrogate Models for Stochastic Simulations
2.1. PRESTO - Predictive REcommendations of Surrogate models To approximate and Optimize
2.2. PARIN - PARameter as INput-variable: A novel approach for surrogate modeling of stochastic simulations
3. Computational Experiments
3.1. Metric for evaluating framework's performance
3.2. Stochastic kriging
4. Results and Discussion
4.1. Selected Surrogate Modeling Techniques by PRESTO
4.2. Surrogate modeling of stochastic simulations using PARIN
5. Conclusions
References
6. Application of PSE into social changes: biomass-based production, recycling systems, and regional systems design and assessment
Abstract
Keywords
1. Introduction
2. Reviews on application of PSE
2.1. CNFRP production from lignocellulosic biomass (Kanematsu et al., 2021)
2.2. LiB recycling systems (Kikuchi et al., 2021)
2.3. Regional systems design in Tanegashima (Kikuchi et al., 2020)
3. Application of PSE into social changes
3.1. Arguments for social changes
3.1.1. Design and assessment considering TRL
3.1.2. Prospective LCA for emerging technology
3.1.3. Technoeconomic, socioeconomic, and sociotechnical analyses
3.1.4. Social changes with process systems design and assessments
4. Conclusions
Acknowledgement
References
7. Q-MPC: Integration of Reinforcement Learning and Model Predictive Control for Safe Learning
Abstract
Keywords
1. Introduction
2. Q-model predictive control
3. Simulation studies
4. Conclusions
References
8. Presentation abstract: Optimization formulations for machine learning surrogates
Abstract
Keywords
1. Main Text
References
9. Pharma PSE: a multiscale approach for reimagining pharmaceutical manufacturing
Abstract
Keywords
1. Introduction
2. Multiscale research viewpoint
3. Research example on cryopreservation of hiPS cells
3.1. Molecule/cell level: computational screening of cryoprotective agents
3.2. Process level: model-based assessment of temperature profiles in slow freezing
3.3. Society level: cost-effectiveness analysis in the manufacture of allogeneic hiPS cells in Japan
4. Lessons learnt towards future research
5. Conclusions
Acknowledgement
References
10. Artificial Intelligence and Process Systems Engineering
Abstract
Keywords
Contributed Papers: Process and Product Design/Synthesis
11. Reinventing the Chemical/Materials Company: Transitioning to a Sustainable Circular Enterprise
Abstract
Keywords
1. The Chemicals and Materials Industry (CMI)
2. GHG and Materials Emissions from CMI
3. Towards the Circularization of CMI
4. The Research Scope of Sustainable Circular CMI (S-CCMI)
5. Conclusions
Acknowledgements
References
12. Value Chain Optimization of a Xylitol Biorefinery with Delaunay Triangulation Regression Models
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Mechanistic Process Models
2.2. Delaunay Triangulation Regression
2.3. Gaussian Process Regression
2.4. Value Chain Optimization
3. Application
3.1. Case Study
3.2. Optimization Problem
3.3. Results
4. Conclusion
Acknowledgments
References
13. Evaluating the Impact of Model Uncertainties in Superstructure Optimization to Reduce the Experimental Effort
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Superstructure optimization under uncertainty
2.2. Linear discrimination analysis
2.3. Optimal design of experiments
3. Case study
3.1. Application of the integrated methodology
4. Conclusion and Outlook
Acknowledgement
References
14. Retrosynthesis Pathway Design Using Hybrid Reaction Templates and Group Contribution-Based Thermodynamic Models
Abstract
Keywords
1. Introduction
2. Retrosynthetic analysis framework using hybrid reaction templates and GC-based thermodynamic models
2.1. Step 1: Generate virtual routes
2.2. Step 2: Verify virtual routes
3. Case studies
4. Conclusions
References
15. Optimization-based Design of Product Families with Common Components
Abstract
Keywords
1. Introduction
2. Product Family Design Formulation
3. Process Case Study
4. Conclusion
References
16. Economic evaluation and analysis of electricity and nano-porous silica productions from rice husk
Abstract
Keywords
1. Introduction
2. Process description
3. Methodology of techno-economic analysis
4. Results
4.1. Process performance
4.2. Economic values (TCI, TPC, POI, and PBP)
5. Conclusions
References
17. Future biofuels: A Superstructure-Based Optimization Framework Integrating Catalysis, Process Synthesis, and Fuel Properties
Abstract
Keywords
1. Introduction
2. Superstructure description
3. Mathematical model
4. Results
5. Conclusions
References
18. Superstructure Optimization of Biodiesel Production from Continuous Stirred Tank and Membrane Reactors
Abstract
Keywords
1. Introduction
2. Superstructure development
2.1. Problem statement
2.2. Superstructure topology
2.3. Mathematical model
3. Results and discussion
4. Conclusions
References
19. Process Design and Techno-Economic Analysis of Biomass Pyrolysis By-Products in the Ontario and Aichi Steel Industries
Abstract
Keywords
1. Introduction
2. Methods
3. Results
4. Conclusions
References
20. Optimal design of solar-aided hydrogen production process using molten salt with CO2 utilization ethylene glycol production
Abstract
Keywords
1. Introduction
2. Problem description
3. Mathematical formulation
4. Solution algorithm
5. Computational studies
6. Conclusion
References
21. Design of a novel hybrid process for membrane assisted clean hydrogen production with CO² capture through liquefaction
Abstract
Keywords
1. Background
2. Hybrid process concepts
3. Modelling approach and design basis
4. Key performance indicators (KPIs)
5. Results and discussion
6. Conclusions
Acknowledgements
References
22. Analysis and design of integrated renewable energy and CO² capture, utilization, and storage systems for low-cost emissions reduction
Abstract
Keywords
1. Introduction
2. Methods
3. Case Study
4. Conclusions
References
23. Techno-economic-environmental assessment for optimal utilisation of CO² in the Fischer-Tropsch gas-to-liquid process
Abstract
Keywords
1. Introduction
2. Methodology
3. Results
4. Conclusions
References
24. Machine Learning-based Hybrid Process Design for the Recovery of Ionic Liquids
Abstract
Keywords
1. Introduction
2. Design method
2.1. ANN-GC model
2.2. Optimal salting-out agent design
2.3. Hybrid recovery process scheme
3. Case studies
4. Conclusions
References
25. A Short-Cut Method for Synthesis of Solvent-based Separation Processes
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Solvent short-cut evaluation method
2.2. Validation model
3. Results and Discussion
4. Conclusions
References
26. Modeling and Optimization of Ionic-Liquid-Based Carbon Capture: Impact of Thermal Degradation Kinetics
Abstract
Keywords
1. Introduction
2. Flowsheet description
3. Process economic optimization
4. Conclusions
5. Acknowledgments
References
27. Process Design of Formic Acid and Methanol Production from CO² Promoted by Ionic Liquid: Techno-Economic Analysis
Abstract
Keywords
1. Introduction
2. Process Description
3. Process Simulation
4. Techno-Economic Assessment
5. Results and Discussion
5.1. Process Simulation Results
5.2. Economic Result
6. Conclusions
Acknowledgments
References
28. Synthesis of Distillation Sequence with Thermally Coupled Configurations Using Reinforcement Learning
Abstract
Keywords
1. Introduction
2. Distillation sequence
2.1. Thermally coupled configuration
2.2. Fenske-Underwood-Gilliland method
2.3. Total annual cost
3. Reinforcement learning
3.1. State
3.2. Action
3.3. Reward
4. Results and discussion
4.1. Case study
5. Conclusion
Acknowledgements
References
29. Optimal Design of Heat Integrated Reduced Vapor Transfer Dividing Wall Columns
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Study
4. Conclusions
References
30. A Model-Data Driven Chemical Analysis System for Products and Associated Processes
Abstract
Keywords
1. Introduction
2. Database and Methodology
3. Case studies
3.1. Mosquito Repellent
3.2. Textile finishing agent
4. Conclusions
References
31. Construction of Database and Data-driven Statistical Models for the Solubility of Nanomaterials in Organic Solvents
Abstract
Keywords
1. Introduction
2. Solubility database for nanomaterials
2.1. Data collection
2.2. Features of the database
2.3. Data quality and discussions
3. Selection of solvent features and data-driven solubility models
3.1. Feature selection
3.2. Data-driven modeling for solubility of nanomaterial
4. Conclusions
Acknowledgement
References
32. Fast, efficient and reliable problem solution through a new class of systematic and integrated computer aided tools
Abstract
Keywords
1. Introduction
2. Methodology & Associated Tools
2.1 ProCAFD-Sustainable process design
2.2 ProCAPD-Chemical product design
3. Case Studies
3.1 Sustainable process design
3.2 Chemical Product Design - Substitution Issues
4. Conclusions
References
33. Design of Bio-Oil Solvents using Multi-Stage Computer-Aided Molecular Design Tools
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Problem Definition
2.2. Consistency Rules
2.3. Verification and Miscibility Analysis
3. Case Study
3.1. Problem Definition
3.2. Results and Discussion
4. Conclusion
Acknowledgements
References
34. Synthesis of azeotropic distillation processes without using a decanter
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical formulation
4. Case Study
5. Results and Discussions
5.1. Reference designs
5.2. Optimization results
6. Conclusions
References
35. Reduce Environmental Impact and Carbon Footprint for Cost Competitive Process Plant Design: Integrating AVEVA Process Simulation with modeFRONTIER®
Abstract
Keywords
1. Introduction
2. Simulation model and Design condition
2.1. Base model for the case study
2.2. Design conditions summary
3. Objective function
3.1. Environmental impact
3.2. Total annual cost (TAC)
4. Optimization-driven design
4.1. Design exploration
4.2. Process Automation
5. Case Study
5.1. Preliminary investigation using pilOPT
5.2. Detailed study based on the above study
6. Result
7. Conclusions
References
36. Reliability incorporated optimal process pathway selection for sustainable microalgae-based biorefinery system: P-graph approach
Abstract
Keywords
1. Introduction
2. Methodology
3. Development of P-graph model
4. Results and discussion
5. Conclusions
Acknowledgements
References
37. Framework for Designing Solid Drug Product Manufacturing Processes Based on Economic and Quality Assessment
Abstract
Keywords
1. Introduction
2. Developed assessment tools
2.1. A superstructure for process synthesis
2.2. Economic assessment
2.3. Product quality assessment
3. Design framework
4. Conclusions
Acknowledgment
References
38. Marine flue gas desulfurization processes: recent developments, challenges, and perspectives
Abstract
Keywords
1. Introduction
2. SWFGD systems in a coastal area
3. Maritime SWFGD systems
4. Improvement of water and SWFGD systems
5. Challenges
6. Conclusion
7. Acknowledgement
8. References
39. A Novel Process Synthesis of a Dehydrating Unit of Domestic Natural Gas Using TEG Contactor and TEG Regenerator
Abstract
Keywords
1. Introduction
2. Process Description
3. Method
4. Proposed Configurations
4.1. General
4.2. Coldfinger Model
5. Results and Discussion
6. Conclusions
Acknowledgements
References
40. A new trust-region approach for optimization of multi-period heat exchanger networks with detailed shell-and-tube heat exchanger designs
Abstract
Keywords
1. Introduction
2. Heat Exchanger Model
2.1. DAE Model
3. Trust Region Algorithm
3.1. Trust-region filter and update
4. Case Study
4.1. Results
5. Conclusions
References
41. A mathematical technique for utility exchanger network synthesis and total site heat integration
Abstract
Keywords
1. Introduction
2. Problem statement
3. Model formulation
4. Case study
5. Conclusions
References
42. Synthesis and Assessment of NOx to Ammonia Conversion Process in Combined Cycle Power Generation Systems
Abstract
Keywords
1. Introduction
2. Analysis for introducing two-stage NTA process system to CCGT system
3. Design of CCGT system with single-stage NTA process system
4. Conclusions
Acknowledgement
References
43. Knowledge integrated, deep neural network-based prediction of stress-strain curves of polymer composites for AI-assisted materials design
Abstract
Keywords
1. Introduction
2. Background
2.1. Challenge
2.2. Theoretical background
3. Prediction of mechanical behavior based on chemical/mechanical information of components
3.1. Data collection
3.2. Data preprocessing
3.3. Model construction and training
4. Predicting mechanical behaviour based on structural information of components
4.1. Data collection
4.2. Data preprocessing
4.3. Model construction and training
5. Results
6. Conclusion
References
44. Evaluation of Economic Performance of Co² Separation Process Using Mixed Matrix Membrane
ABSTRACT
Keywords
1. Introduction
2. Modelling
3. Result and discussion
3.1 Effect of CO² Permeance and CO²/N² Selectivity on CO² concentration for CCS, required energy, and membrane area
3.2 Evaluate the economic performance for CO² capture process for CCS
3.3 Configuring membranes with appropriate separation performance
4 Conclusions
Acknowledgment
References
45. Nature vs engineering: Production of methanol from CO² capture
Abstract
Keywords
1. Introduction
2. Process description
3. Modelling approach
4. Optimization procedure
5. Results
5.1. Process analysis
5.2. Process economics
6. Conclusions
Acknowledgment
References
46. Superstructure Optimization for the Design of an Algae Biorefinery Producing Added Value Products
Abstract
Keywords
1. Introduction
2. Methodology
2-1 Process description and superstructure development
2-2 Problem statement
2-3 mathematical model
3. Results
4. Conclusion
References
47. Process simulation of biodiesel production catalyzed by a high stability solid in a reactive distillation
Abstract
Keywords
1. Introduction
2. Description of RD and methodology
3. Results and Discussion
3.1 Effects of operating pressure and molar reflux ratio
3.2 Effects of methanol to oil molar ratio as feed
4. Conclusions
5. References
48. Generatives Approaches for the Synthesis of Process Structures
Abstract
Keywords
1. Introduction
2. Recent prospective works on "Generative Approaches"
3. Discussions on generative aspects
3.1 Generative machine learning models
3.2 Application to process synthesis: concept and challenges
3.2.1 Initial database
3.2.2 Data representation
3.2.3 Generative model architecture
3.2.4 Reward design
3.2.5 Optimization strategy
3.2.6 Post-processing for the engineer
4. Conclusive remarks
References
49. Metal-Organic Framework Targeting for Optimal Pressure Swing Adsorption Processes
Abstract
Keywords
1. Introduction
2. Workflow of Descriptor-based MOF Targeting
3. Descriptor-based MOF Screening
4. Construction of MOF Building Blocks
5. Computational MOF Synthesis and MOF Targeting
5.1. GA-based MOF synthesis
5.2. Optimal MOF targeting
6. Conclusions
References
50. Energy integration through retrofitting of heat exchanger network at Equinor Kalundborg Oil Refinery
Abstract
Keywords
1. Introduction
2. Methodology
3. Results
3.1. Removing cross pinch heat transfer
3.2. Uncertainty analysis
4. Conclusions
References
51. Modeling and Optimization of Ionic Liquid Enabled Extractive Distillation of Ternary Azeotrope Mixtures
Abstract
Keywords
1. Introduction
2. Methods
2.1. HFC Separation Process Development and Modeling
2.2. Sensitivity analysis
3. Economic Performance Evaluation
4. Conclusions
5. Acknowledgments
6. References
52. Optimal Design of Hybrid Distillation/Pervaporation Processes
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Membrane System Superstructure
2.2. Membrane System Superstructure Simultaneous Optimization Strategy
2.3. Hybrid Process Simulation and Optimization
3. Case Study
4. Conclusions
References
53. Design and analysis of a single mixed refrigerant natural gas liquefaction process integrated with ethane recovery and carbon removal using cryogenic distillation
Abstract
Keywords
1. Introduction
2. Process simulation and optimization
2.1. Process description
2.2. Initial settings and assumptions
2.3. Process evaluation and optimization
3. Results and discussion
3.1. Calculation of the maximum allowable CO² content
3.2. Process optimization results
3.3. Process performance
4. Conclusion
Acknowledgement
References
54. A new decomposition approach for synthesis of heat exchanger network with detailed heat exchanger sizing
Abstract
Keywords
1. Introduction
2. Mythologies
2.1. Global optimization for detailed heat exchanger sizing
2.2. HEN superstructure optimiz ation
2.3. Iterative algorithm
3. Case study
4. Conclusions
References
55. A mathematical approach for the synthesis of a wastewater treatment plant using the concept of cirular economy
Abstract
Abstract
1. Introduction
2. Problem statement
3. Circular economy optimization model
3.1. Flowrate of wastewater treatment process
3.2. Contaminant component balance
3.3. Circular economy efficiency index
4. Case study
5. Conclusions
References
Contributed Papers: Process Dynamics and Control
56. Convex Q-learning: Reinforcement learning through convex programming
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
4. Conclusion and F uture Work
Reference
57. Differential Dynamic Programming Approach for Parameter Dependent System Control
Abstract
Keywords
1. Introduction
2. Background
2.1. Problem Formulation
2.2. Differential Dynamic Programming
3. Methodology
3.1. Least Squares Parameter Estimation
3.2. Parameter Dependent Differential Dynamic Programming
4. Simulation Results
5. Conclusions
ACKNOWLEDGEMENT
References
58. Optimization of an air-cooler operation in an industrial distillation column
Abstract
Keywords
1. Introduction
2. Method for optimizing the number of fixed fans in operation
2.1. Fans power consumption
2.2. Optimizing the number of fixed fans in operation
3. Application example using operation data from the process industry
3.1. Identification of air-flow rate and power-consumption equations
3.2. Industrial-data collection
3.3. Application of conventional method
3.4. Application of proposed method
4. Conclusions
References
59. Dynamic Operability Analysis for the Calculation of Transient Output Constraints of Linear Time-Invariant Systems
Abstract
Keywords
1. Introduction
2. Dynamic Operability Problem Background
2.1. Preliminaries
2.2. Dynamic operability sets
3. Calculation of Transient Output Constraints
3.1. Offline computation of transient state funnel at nominal-valued disturbances
3.2. Transient state funnel with process disturbances
3.3. Transient output funnel with process disturbances and measurement noises
4. Numerical Example
5 . Conclusions
References
60. Effective Re-identification of Multivariate Process under Model Predictive Control Using Information from Plant-Model Mismatch Detection
Abstract
Keywords
1. Introduction
2. Problem setting
3. Proposed Method
4. Case study
4.1. Settings
4.2. Procedure
4.3. Results
5. Conclusions
References
61. Model Predictive Control of Grade Transition with Attention Base Sequence-to-Sequence Model
Abstract
Keywords
1. Sequence-to-Sequence Model
2. Attention Mechanism
3. Elastic Net and Systematic Model Improvement
4. A High-Density Polyethylene Reactor
5. Dynamic Modelling
6. Grade Transition Navigation
7. Conclusion
Acknowledgment
References
62. Real Time Optimization of series of fixed bed catalytic reactors
Abstract
Keywords
1. Introduction
2. Digital Twin Development
3. Online Implementation
4. Results
5. Conclusions
References
63. Self-triggered MPC for Perturbed Continuous-time Nonlinear Systems
Abstract
Keywords
1. Introduction
2. Preliminary
3. Description for OCP and Triggering Mechanism
3.1. OCP
3.2. Self-triggered Strategy
4. Simulation
5. Conclusions
References
64. A comparative study between MPC and selector-based PID control for an industrial heat exchanger
Abstract
Keywords
1. Introduction
2. Heat exchanger system
3. Simulation studies
3.1. Simulation results for nominal mode
3.2. Simulation results for bypass model
4. Conclusions and future work
References
65. MILP Formulation for Dynamic Demand Response of Electrolyzers
Abstract
Keywords
1. Introduction
2. MILP Formulation for Electrolyzer Scheduling
2.1. Assumptions
2.2. Reformulation
3. Case Study
4. Results
5. Conclusion
Acknowledgements
References
66. Real-Time Optimal Operation of a Chlor-Alkali Electrolysis Process under Demand Response
Abstract
Keywords
1. Introduction & Motivation
2. Methodology
2.1. Optimal Process Control
2.2. Approximate Control Law
3. Case Study
3.1. Optimal Process Control
3.2. Approximate Control Law
3.3. Quality of the Approximation
4. Conclusions & Outlook
5. Acknowledgements
References
67. Explicit Multi-Objective and Hierarchical Model Predictive Control
Abstract
Keywords
1. Main Text
2. Multi-Objective Model Predictive Control Structure
2.1. Problem Formulation
2.2. Solution Strategy
3. Hierarchical Model Predictive Control Structure
3.1. Problem Formulation
3.2. Solution Strategy
4. Case-study: Continuous Stirred Tank Reactor
4.1. System Definition
4.2. Controller Development - PAROC Framework
4.2.1. High-fidelity Model
4.2.2. Model Approximation
4.2.3. Controller Formulation
4.3. Closed-loop Validation
5. Conclusion
Acknowledgements
References
68. A Robust Optimization Strategy for Explicit Model Predictive Control
Abstract
Keywords
1. Introduction
2. Problem Formulation
3. Methodology
4. Results
5. Conclusions
6. Acknowledgements
7. References
69. Data-driven Design of a Feed-forward Controller for Rejecting Measurable Disturbance
Abstract
Keywords
1. Introduction
2. Design Scheme of Disturbance Rejection Controller
2.1. Feed-forward Controller
2.2. Data-driven controller tuning
3. Numerical examples
4. Conclusions
References
70. Optimal Operation of Heat Exchanger Networks with Changing Active Constraint Regions
Abstract
Keywords
1. Introduction
2. Case study modeling
3. Proposed control structure
4. Simulation results and discussion
5. Conclusion
References
71. Iterative Feedback Tuning for Regulatory Control Systems Using Estimate of Sensitivity Function
Abstract
Keywords
1. Introduction
2. IFT for regulatory control
2.1. Process description and regulatory control Systems
2.2. Control objective
3. Controller parameter tuning via IFT
3.1. Gradient estimate
4. Estimate of sensitivity function
4.1. Rough estimate of sensitivity function
4.2. Correction of the roughly estimated sensitivity function
5. Numerical Example
6. Conclusions
References
72. D-RTO as Enabler for Green Chemical Processes - Systematic Application and Challenges in Reactive Liquid Multiphase Systems
Abstract
Keywords
1. Introduction and Motivation
2. System Information and Technical Application
2.1. Separation Behavior of the Microemulsion System
2.2. Mini-Plant Configuration
2.3. Operational Challenges and Requirements for D-RTO Application
3. Model Development and D-RTO Framework
3.1. Dynamic Mini-Plant Model
3.2. D-RTO Framework
4. Case Study
5. Conclusion and Outlook
Acknowledgements
References
73. Design of PID controllers using semi-infinite programming
Abstract
Keywords
1. Introduction
1.1. System
1.2. Objective
1.3. Robustness
1.4. Noise attenuation
1.5. Optimisation problem
2. Numerical examples
2.1. First order process with time delay
2.2. Third order process with inverse response
2.3. Discussion
3. Conclusions
4. Acknowledgments
References
74. Safe Chance Constrained Reinforcement Learning for Batch Process Optimization and Control
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Study
3.1. A Fed-batch Lutein Photo-production process
3.2. Case Study Design and Benchmarks
3.3. Process Constraints, Objective and Key Performance Indicators
4. Results and Discussion
5. Conclusions
References
Contributed Papers: Scheduling and Planning
75. Combining Machine Learning with Mixed Integer Linear Programming in Solving Complex Scheduling Problems
Abstract
Keywords
1. Introduction
2. Modeling
3. Solution efficiency
4. Main Challenges
5. Conclusions
References
76. Knowledge-guided Hybrid Approach for Scheduling Multipurpose Batch Plants
Abstract
Keywords
1. Introduction
2. Sequence-based MILP formulation
3. Genetic algorithm
4. Hybrid algorithm
5. Computational Results
6. Conclusions
Acknowledges
References
77. Scheduling of Electrical Power Systems under Uncertainty using Deep Reinforcement Learning
Abstract
Keywords
1. Introduction
2. MDP Formulation and Safety
3. Actor-Critic Method for Policy Learning
4. Case Study: IEEE 39-Bus System
5. Conclusion
References
78. A Reinforcement Learning Approach to Online Scheduling of Single-Stage Batch Chemical Production Processes
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Study
4. Results and Discussion
5. Conclusions
References
79. An adaptive multi-cut decomposition based algorithm for integrated closed loop scheduling and control
Abstract
Keywords
1. Main Text
2. Problem formulation and decomposition
2.1. Scheduling problem
2.2. Dynamic model
2.3. Integrated problem
3. Decomposition based solution algorithm
4. Adaptive multicut algorithm
5. Case study
6. Conclusions
References
80. Uncertainty Evaluation of Biorefinery Supply Chain's Economic and Environmental Performance Using Stochastic Programming
Abstract
Keywords
1. Introduction
2. Modular Biorefinery Supply Chain Model
2.1. Stochastic programming formulation of distributed biorefinery supply chain
2.2. Life cycle assessment for each scenario of the stochastic programming
2.3. Case study of distributed modular biorefinery operation
3. Results and discussion
4. Conclusions
Acknowledgements
References
81. An Improved Optimization Model for Scheduling of an Industrial Formulation Plant based on Integer Linear Programming
Abstract
Keywords
1. Introduction
2. Indutrial Formulation Plant
3. Solution Approach
3.1. Integer Linear Programming Model
3.2. Decomposition
4. Results
5. Conclusion and Outlook
Acknowledgements
References
82. Optimal Sourcing, Supply and Development of Carbon Dioxide Networks for Enhanced Oil Recovery in CCUS Systems
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical Formulation
4. Results
5. Conclusions
6. References
83. Production scheduling in multiproduct multistage semicontinuous processes. A constraint programming approach
Abstract
Keywords
1. Introduction
2. Methodology
3. CP model
4. Results
5. Conclusions and future work
References
84. Maintenance scheduling optimization for decaying performance nonlinear dynamic processes
Abstract
Keywords
1. Introduction
2. Maintenance scheduling of decaying performance processes
3. Maintenance scheduling of reverse osmosis networks (RONs)
3.1. Mathematical model
3.2. Results and discussion
4. Future directions for maintenance scheduling optimization
5. Conclusions
References
85. Cleaning schedules for heat exchanger networks subjected to maintenance constrains
Abstract
Keywords
1. Introduction
2. MILP problem formulation description
3. Case study
4. Conclusion and future work
Acknowledgement
References
86. Estimating Energy Market Schedules using Historical Price Data
Abstract
Keywords
1. Introduction
2. Methods
2.1. Sets and Variables
2.2. Lookup Dispatch Algorithm
2.3. MILP Optimization Problem
3. Results and Discussion
4. Conclusions and Future Work
Acknowledgements
References
87. Scheduling of Material and Information Flows in the Manufacturing of Chemicals for the Order-to-Cash Process of a Digital Supply Chain
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical Model
4. Illustrative Example
5. Conclusions
References
88. Optimization of Maximum Completion Time of Polymerization Section Based on Improved Estimation of Distribution Algorithm
Abstract
Keywords
1. Introduction
2. Scheduling model of PVC polymerization section
2.1. Modeling hypotheses
2.2. Mathematical model
3. Improved estimation of distribution algorithm
3.1. Improvement strategy
3.1.1. The elitism strategy
3.1.2. Constructing probability model
3.1.3. Binary search strategy
3.2. IEDA
4. Case analysis
4.1. Case parameters
4.2. Analysis of simulation results
5. Conclusions
Reference
89. Evolutionary Algorithm-based Optimal Batch Production Scheduling
Abstract
Keywords
1. Introduction
2. Case Study
3. Methodology
3.1. Encodings
3.2. Genetic operators
4. Results
5. Summary, Conclusion and Outlook
Acknowledgements
References
90. Cream Cheese Fermentation Scheduling
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Scheduling framework
2.1.1 pH prediction model
2.1.2 Scheduling formulation
3. Results
3.1. Industrial scale scheduling
4. Conclusions
References
Contributed Papers: Supply Chain Management and Logistics
91. Multi-Objective Optimization of Production Cost and Carbon Loss in the U.S. Petrochemicals Industry
Abstract
Keywords
1. Introduction
2. Background and Problem Definition
3. Solution Strategies
4. Case Study
5. Conclusions
Acknowledgement
References
92. Mapping Anthropogenic Carbon Mobilization through Chemical Process and Manufacturing Industries
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
4. Conclusions
5. Acknowledgments
References
93. Optimal Design and Planning of Ethiopia's Biomass-to-Biofuel Supply Chain Considering Economic and Environmental Dimensions under Strategic and Tactical Levels
Abstract
Keywords
1. Introduction
2. Methodologies
2.1. Life cycle environmental assessment
2.2. Model formulation
2.3. Case Study
2.4. Solution method for multi-objective optimization
3. Result and Discussion
3.1. Environmental impact
3.2. Multi-objective optimiz ation results
3.3. Optimum strategic decisions
4. Conclusions
References
94. A Novel Integrated Optimal Scheduling Framework for Holistic Refinery Supply Chain Management
Abstract
Keywords
1. Introduction
2. CM&RM&MOPD model
2.1. CM&RM joint sub-model
2.2. RM&MOPD joint sub-model
2.3. Objective function
3. Case study
3.1. Computational performance and economic analysis
3.2. Results of crude-oil management scheduling
3.3. Results of refinery manufacturing scheduling
3.4. Results of multi oil-product pipeline distribution scheduling
4. Conclusions
Acknowledgements:
References
95. Roadmap to digital supply chain resilience
Abstract
Keywords
1. Introduction
2. Stages towards the digital transformation
2.1. First stage: SIPOC (suppliers-input-process-outcome-customer) integration
2.2. Second stage: SIPOC autonomy
3. Continuous evolution towards the digital supply chain resilience
4. Conclusions
References
96. Development of Flexible Framework for Biomass Supply Chain Optimization
Abstract
Keywords
1. Introduction
2. Assumptions during model development
3. Generalised representation of the supply chain elements
4. Concept of site and path
5. Formulation of the optimisation problem
6. System development
7. Conclusions
Acknowledgements
References
97. Lagrangean Decomposition for Integrated Refinery - Petrochemical Short-Term Planning
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Reformulation of problem P
2.2. Lagrangean relaxation of problem P'
2.3. Decomposition of
3. Case study
4. Conclusions
Acknowledgments
References
98. Green Ammonia Supply Chain Design for Maritime Transportation
Abstract
Keywords
1. Introduction
2. Mathematical Formulation
3. Computational Case Study
4. Conclusions
References
99. Optimal agriculture residues revalorization as a biofuel alternative in electric power grids
Abstract
Keywords
1. Introduction
2. Problem statement
3. Methodology
4. Results
5. Conclusions
Acknowledgements
References
100. Global Supply Chain Optimization for COVID-19 Vaccine under COVAX initiative
Abstract
Keywords
1. Introduction
2. Challenges faced by COVAX
3. Problem Statement
4. Supply chain optimization
5. Case study
6. Results
7. Conclusions
References
101. Optimal Liquefied Natural Gas (LNG) Annual Delivery Program Reflecting both Supplier and Customer Perspectives
Abstract
Keywords
1. Introduction
1.1. Literature Survey
2. Problem Description
3. Mathematical Model
3.1. Modelling inventory and berth management at the customer terminals
3.2. Objective Function
4. Results
4.1. Illustrative Example
4.2. Computational Results
5. Conclusions
References
102. The Waste-to-Resource Game: Informed Decision-Making for Plastic Waste Transformers
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Bargaining Game
4. Pyrolysis Model
5. Case Study
6. Results and Discussion
7. Conclusions
Acknowledgements
References
103. Implications of Optimal BECCS Supply Chains on Absolute Sustainability
Abstract
Keywords
Introduction
Methods
Results
Conclusions
References
104. A Multi-disciplinary Assessment of Innovations to Improve Grocery Bag Circularity
Abstract
Keywords
1. The need for more circular grocery bags
2. Baseline model
3. Life cycle assessment
4. Policy
5. Economics
6. Supply chain management
7. Conclusion
References
Acknowledgements
105. Process Sustainable Supply Chain: integrating monetization strategies in the design and planning
Abstract
Keywords
1. Introduction
2. Environmental and social monetization methodologies
3. Problem description and model characterization
4. Case study
4.1. Results
5. Conclusions
Acknowledgements
References
Contributed Papers: Process Intensification
106. Systematically Identifying Energy-Efficient and Attractive Multicomponent Distillation Configurations
Abstract
Keywords
1. Introduction
2. Optimization Model
2.1. Base Model
2.2. Estimating Better Relative Volatilities
2.3. Relaxing Constant Molar Overflow
2.4. Heat Integration to Reduce Energy Consumption
3. Case Study
4. Conclusions
Acknowledgments
References
107. Synthesis of Advanced Reactive Distillation Technologies: Early-Stage Assessment Based on Thermodynamic Properties and Kinetics
Abstract
Keywords
1. Introduction
2. Advanced reactive distillation technologies
3. Research approach, conceptual framework and scope
3.1. Research approach
3.2. Conceptual framework and scope
4. Decision-making methodology applied to two case studies
5. Results and discussion
5.1. Concentration and purification of lactic acid
5 .2 . Production of dimethyl ether (DME)
6. Conclusions
Acknowledgements
References
108. Process Synthesis and Intensification for Upgrading Natural Gas Liquids in Shale Gas
Abstract
Keywords
1. Introduction
2. Base Case Flowsheet
3. Systematic Analysis and Evolution of Process Configurations
4. Conclusions
References
109. Energy-Efficient Direct Cyclohexene to Cyclohexanol Process by Heat Pump Assisted Reactive Distillation
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Reaction kinetics and phase equilibrium model
4. Process Simulation
4.1. Aqueous-phase-refluxed reactive distillation with a stripper (ARDS)
4.2. Organic-phase-refluxed reactive distillation with a stripper (ORDS)
4.3. Heat-pump-assisted reactive distillation (HPRD)
5. Process Evaluation
5.1. Evaluation method
5.2. Evaluation results
6. Conclusion
Acknowledgements
References
110. Sustainable Process Intensification of Refrigerant Mixture Separation and Management: A Multiscale Material Screening and Process Design Approach
Abstract
Keywords
1. Introduction
2. Problem Representation
3. Extractive Distillation Process Synthesis for R-410A Separation
3.1. Base Design
3.2. Process Optimization
3.3. Mapping of IL Selectivity, Separation Energy and Cost
4. Conclusions
5. Acknowledgment
References
111. A systematic methodology for the optimisation, control and consideration of uncertainty of reactive distillation
Abstract
Keywords
1. Introduction
2. Methodology
3. Case study
4. Results and Discussion
5. Conclusions
References
112. Equation Oriented Optimization of Multi Stream Heat Exchanger Design and Operation in Natural Gas Liquefaction Process
Abstract
Keywords
1. Introduction
2. Model
2.1 MHEX DAE model
2.2 Heat Equation
2.3 Phase Change
2.4 Flowsheet
3. Methodology
4. Optimization Results
5. Conclusions
Reference
113. Optimal Design of Extractive Dividing-Wall Column Using an Improved Sequential Least Squares Programming Algorithm
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical Model
4. Solution method
4.1. SLSQP-based feasible path algorithm
5. Case study
6. Conclusions
Acknowledgements
References
114. Biphasic Dehydration of Sugars to 5-Hydroxymethylfurfural and Furfural-Multiscale Modeling for Easier Optimization and More Accurate Solvent Selection
Abstract
Keywords
1. Introduction
2. Multiscale modeling approach
3. Biphasic system
4. Results and discussion
4.1. Steady state properties of the system
4.2. Extractive ability of the solvent candidates
5. Current limitations
6. Conclusions
References
115. Study of Mass Transfer Coefficient of CO² Capture in different Solvents using Microchannel: A Comparative Study
Abstract
Keywords
1. Introduction
2. Selection of system
2.1 Conventional, Mini, and Micro-channels
2.2 Physical/Chemical Absorption
2.3 Solvents
2.4 Concentration
2.5 Sherwood number
3. Results and discussion
4. Conclusions
References
116. Techno-Economic Study of Intensified Ethylene Oxide Production Using High Thermal Conductivity Microfibrous Entrapped Catalyst
Abstract
Keywords
1. Introduction
2. Process Description and Design
2.1 Process description
2.2. Feed conditioning and conversion
2.3. EO Purification
2.4. Carbon dioxide removal
2.5. Tube burnout inside EO reactor
3. Optimization Algorithm
4. Results and Discussion
5. Conclusions
References
Contributed Papers: Integration of Process Operation and Design/Synthesis
117. Power Systems Infrastructure Planning with High Renewables Penetration
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Transmission Expansion Formulation
4. Proposed Algorithms
4.1. Nested Benders decomposition
4.2. Benders decomposition
5. Results
6. Conclusions
References
118. An Optimization Model for the Design and Operation of Reliable Power Generation Systems
Abstract
Keywords
1. Introduction
2. Problem statement
3. Model formulation
4. Illustrative example
5 . Sensitivity analysis
6 . Conclusions
Acknowledgement
References
119. Rule-based Method for Retrofitting Conventional Processes with Integrated Units
Abstract
Keywords
1. Introduction
2. Method
3. Case Studies
3.1. Application of RDC (replacement and/or retrofit of base case)
3.2 Application of DWC (replacement of base case)
3.3. Application of HDS (retrofit of base case)
4. Conclusion
References
120. Integration of Design and Operation for the CO²-based Methanol Synthesis
Abstract
Keywords
1. Introduction
2. Framework
3. Model
3.1. Balance equations
3.2. Cost functions
3.3. Initial conditions
3.4. Path constraints
3.5. Implementation and framework
4. Results and discussion
4.1. Initialization
4.2. Comparison of steady-state and dynamic results
4.3. Computational times
5. Conclusion and outlook
References
121. Blue Syngas Synthesis via the Integration of Gasification and Reforming Processes
Abstract
Keywords
1. Introduction
2. Process description
2.1. Series integration
2.2. Parallel integration
3. Results
3.1. Energy analysis
3.2. Economic analysis
4. Conclusions
References
122. Network optimization of the electrosynthesis of chemicals from CO²
Abstract
Keywords
1. Introduction
2. Modeling and techno-economic assessment of ECO2R processes
3. Optimization model
3.1. Problem statement
3.2. Mathematical formulation
4. Case study
5. Results
6. Conclusions
References
123. A robust design of heat exchanger network for high temperature electrolysis systems
Abstract
Keywords
1. Introduction
2. Process description
3. Result and discussion
4. Conclusions
References
124. Techno-economic Assessment of Upstream and Downstream ProcessAlternatives for the Production of Monoclonal Antibodies
Abstract
Keywords
1. Introduction
2. Simulation of process alternatives
2.1. Main cultivation unit
2.2. Downstream capture chromatography
3. Results and discussion
3.1. Cultivation unit
3.2. Capture chromatography
4. Conclusions
Acknowledgements
References
125. Biomethane liquefaction followed by CO² solidification based biogas upgrading process
Abstract
Keywords
1. Introduction
2. Process design and simulation
2.1. Process description
2.2. Process simulation
3. Process optimization
4. Results and discussion: Process analysis
4.1. Energy analysis
4.2. Exergy analysis
5. Conclusions
Acknowledgements
References
126. Importance of interannual renewable energy variation in the design of green ammonia plants
Abstract
Keywords
1. Introduction
2. Methodology
3. Results
3.1. Comparison of performance
3.2. Comparison of speed
4. Historical Data Analysis
5. Conclusions
References
127. Integrating Carbon Negative Technologies in Industrial Clusters
Abstract
Keywords
1. Introduction
2. Approach
3. Illustrative example
3.1. Process data
3.2. Results
4. Conclusion
References
128. Flexibility analysis of chemical processes considering overlaying uncertainty sources
Abstract
Keywords
1. Introduction
2. Flexibility index and suggested reformulations
2.1. Original flexibility index formulation and overlaying uncertainty sources
2.2. Suggested reformulation of the flexibility index problem
3. Illustrative Example
4. Industrial case study
5. Influence of operational flexibility target value
6. Conclusion
References
129. Flexible and Sustainable Methanol Production Including Option with Green Hydrogen
Abstract
Keywords
1. Introduction
2. Results and Discussion
2.1 Conventional Methanol Unit
2.2 Multistage Methanol Pilot Unit
3. Conclusions and Outlook
References
130. Optimization and Heat Exchanger Network Design of Diethyl Carbonate Two-step Synthesis Process from CO² and Propylene Oxide
Abstract
Keywords
1. Introduction
2. Process description and optimization
3. CO2 emission calculation
4. Process intensification and heat integration
4.1. Thermally-coupled process
4.2. Heat integration
5. Conclusion
References
131. Characterization of Industrial Flaring under Uncertainty for the Design of Optimum Flare Recovery and Utilization Systems
Abstract
Keywords
1. Introduction
2. Problem statement
3. Flare streams characterization and optimization model
4. Results
4.1. Probabilistic characterization
4.2. Sensitivity analysis
4.3. Effects of uncertainties on process economics
5. Conclusions
References
132. Development of Micro Scale ORC Using Low Grade Geothermal Thermal Energy
ABSTRACT
1. Introduction
2. Modeling
3. Simulation results and discussion
4. Conclusion
5. Reference
133. Scenario Outcomes for Electric Power Generation Expansion Planning considering the State of Indiana as a Case Study
Abstract
Keywords:
1. Main Text
2. Research Methods
2.1. Collection of Data
2.2. Treatment of Data
2.3. Mathematical Modeling
3. Results and Discussion
4. Conclusions
References
134. Requirements for the quality assessment of virtual commissioning models of modular process plants
Abstract
Keywords
1. Introduction
2. State of the art
2.1. Virtual Commissioning for modular process plants
2.2. Quality assessment for simulation models
3. Requirements for third-party model integration
3.1. Model compatibility
3.2. Model maintainability
3.3. Performance efficiency
4. Quality assessment for virtual commissioning models
5. Conclusion
References
Back Cover
9780323853668v2_WEB
Front Cover
14th INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING
Copyright
Contents
Contributed Papers: Modeling, Analysis, and Simulation
135. A combinatorial tool for monitoring flocculation processes: Using non-invasive measurements and hybrid deep learning assisted modeling
Abstract
Keywords
1. Introduction
2. Modelling framework
3. Application example
4. Conclusions
5. Acknowledgements
References
136. Optimal Design of Experiment Based on Artificial Neural Network Classifiers for Fast Kinetic Model Recognition
Abstract
Keywords
1. Introduction
2. Proposed framework and methods
3. Case study description
4. Results
5. Conclusions
References
137. Modelling of the rice bran protein extraction using response surface methodology
Abstract
Keywords
1. Introduction
2. Methodology
2.1 Raw material
2.2 Soni-auto hybrid extraction method
2.3 Response surface methodology (RSM)
3. Results and discussion
3.1 Model selection
4. Conclusions
Acknowledgement
References
138. Weibull Reliability Regression Model for Prediction of Bearing Remaining Useful Life
Abstract
Keywords
1. Background
2. Methodology
2.1. Weibull reliability model
2.2. Features
2.3. Target
3. Result and Discussion
3.1. Regression pre-process
3.2. Model selection
3.3. Single model to multiple models
4. Conclusions
References
139. Supporting Hyperparameter Optimization in Adaptive Sampling Methods
Abstract
Keywords
1. Introduction
2. Hydroformylation
3. Methodology
3.1. Surrogate model types
3.2. Adaptive sampling methodology
3.3. Hyperparameter optimization
3.4. Supporting hyperparameter optimization
4. Results
4.1. Hyperparameter dependency
4.2. Combination of adaptive sampling and hyperparameter optimization
5. Conclusion
6. Acknowledgment
References
140. Optimal Catalyst-Reactor Design for Load-Flexible CO² Methanation by Multi-Period Design Optimization
Abstract
Keywords
1. Introduction
2. Fixed-Bed Reactor and Catalyst Particle Model
3. Multi-Period Design Optimization
4. Results
4.1. Multi-Period Design Optimization
4.2. Dynamic Load-Change Simulations
5. Conclusions
6. Acknowledgment
References
141. Data-Driven Modeling of Long-term Performance Degradation in Solid Oxide Electrolyzer Cell System
Abstract
Keywords
1. Background
2. Modeling strategy
2.1. Development of the linear model from 200h to 2500h
2.2. Validation of the linear model out to 2500 h
2.3. Sublinear model out to 7000 h
3. Discussion and Future Work
4. Conclusions
References
142. Modeling and Optimal Design of Pressure Swing Adsorber for Carbon Dioxide and Hydrogen Separation from Industrial Waste Gas
Abstract
Keywords
1. Introduction
2. Process description
3. Mathematical model
3.1. Model fitting
3.2. Process optimization
4. Results and Discussion
4.1. Model fitting
4.2. Optimization Results
5. Conclusions
Acknowledgement
References
143. Membrane Characterization with Model-Based Design of Experiments
Abstract
Keywords
1. Introduction
2. Mathematical model, materials, and methods
3. Fisher Information Matrix (FIM)
4. Results and discussions
4.1. Diafiltration experiment enables identification of all model parameters
4.2. Additional retentate measurements improve parameter precision
4.3. MBDoE optimizes DA TA system
5. Conclusions
Acknowledgements
References
144. Systematic Modelling of Distillation Columns based on Topologies and Ontologies
Abstract
Keywords
1. Motivation
2. Structural model design
3. Mathematical model design
4. Results and discussion
5. Conclusions
Acknowledgements
References
145. Sensitivity Analysis of an Electrospray Dehumidification System
Abstract
Keywords
1. Introduction
2. Electrospray System Computational Fluid Dynamics (CFD) Model
2.1. Particle-Laden Gas Using Eulerian Method
2.2. Spray Charged Droplets Using Lagrangian Method
2.3. Droplet Electro-Condensation Model
3. Surrogate-based Sobol Sensitivity Analysis
4. Results
5. Conclusions and Future Work
6. Acknowledgments
References
146. Rigorous modeling for comparing batch and flow syntheses of a drug substance using heterogeneous hydrogenation
Abstract
Keywords
1. Introduction
2. Materials and methods
2.1. Target reaction
2.2. Model assumptions
2.3. Model equations for batch synthesis
2.4. Model equations for flow synthesis
3. Results and discussion
3.1. Conversion of raw materials
3.2. Sensitivity analysis of reaction rate constant and viscosity
4. Conclusions and outlook
References
147. Assessment on the heat integration potential for different pressure thermally coupled distillation structures
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical formulation
4. Case Study: n-butanol/isobutanol separation
5. Results and Discussions
6. Conclusions
References
148. Python platform for Tennessee Eastman Process
Abstract
Keywords
1. Introduction
2. Different versions of TEP
2.1. Original TEP
2.2. Simplified TEP
2.3. The Newest TEP
2.4. Possible way to improve TEP
3. Connect TEP to Python
3.1. System Architecture
3.2. Precision Comparison
3.3. GUI for S-TEP
4. Conclusions
References
149. Computational Modeling of Lube-Oil Flows in Pipelines to Study the Efficacy of Flushing Operations
Abstract
Keywords
1. Introduction
2. Optimal Control Problems and Applications
3. Viscosity Blending Equations
4. Modeling the Flushing Operation
5. Solution Methodology
6 . Results and Discussions
7. Conclusion
References
150. Comparison of ammonia synthesis plants of different scale with a dynamic model
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Model Description
2.2. Model Validation and Downscaling
2.3. Dynamic Simulations and Disturbance Testing
3. Results and Discussion
3.1. Model Validation
3.2. Disturbance Testing
4. Conclusion
References
151. Simulation Analysis of Gas Feed Method for Development of Ru-Based Catalyst for Ammonia Production
Abstract
Keywords
1. Introduction
2. Derivation of reaction rate equation for developed Ru-based catalyst
3. Simulation analysis for application of methods for split feed of gas
4. Conclusions
References
152. Estimation of the effect of liquid viscosity on gas-liquid mass transfer in a bioreactor using CFD-PBM coupled model
Abstract
Keywords
1. Introduction
2. Methodology
3. Numerical strategy
4. Results and discussion
4.1 . M odel validation
4.2 . Effect of liq uid viscosity on oxygen mass transfer
5 . Conclusions
Acknowledgements
References
153. Knowledge-matching based computational framework for genome-scale metabolic model refinement
Abstract
Keywords
1. Introduction
2. Knowledge-matching based framework for GEM analysis
3. SID-based GEM refinement
4. Conclusions
References
154. Multi-Regional Surrogate Model Selection (MRSMS) approach for the analysis and optimal fitting of univariate responses
Abstract
Keywords
1. INTRODUCTION
2. METHODOLOGY
3. CASE STUDY
5. Conclusion
6. Acknowledgements
7. References
155. A Digital Reality Pilot Plant for Research and Learning
Abstract
Keywords
1. Introduction
2. Existing Course Offering
3. A Cognitive Framework for the design of digital reality learning tools
4. Design Study: The PID
4.1 Original Design
4.2 Implemented Design
5. Conclusion
Acknowledgements
References
156. Soft sensors development for industrial reactive distillation processes under small training datasets
Abstract
Keywords
1. Introduction
2. Statement of problem and its analysis
3. Soft sensor evaluation based on the sample extension
4. Conclusions
5. Acknowledgements
References
157. Comprehensive Quantification of Model Prediction Uncertainty for Simulated Moving Bed Chromatography
Abstract
Keywords
1. Introduction
2. Methodology
2.1. SMB Process Model
2.2. Bayesian Inference and Predictive Distribution
3. Experimental
3.1. SMB Model, Operating and Simulation Condition
3.2. Artificial Data of Single-Column Experimental
3.3. Implementation of sequential Monte Carlo
4. Results
4.1. Posterior Distribution of Model Parameters
4.2. Prediction uncertainty in internal concentration of SMB
4.3. Predictive Distribution of Product Purities and Recoveries
5. Conclusions
References
158. A predictive model for multi-criteria selection of optimal thermochemical processing pathways in biorefineries
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Processes Modelling
2.2. Technical, environmental and economic studies
2.3. Regression Model
2.4. Model Evaluation
3. Results and Discussion
4. Conclusions
References
159. Numerical Investigation of the Shear Rate Variation in Cooling Crystallization
Abstract
Keywords
1. Introduction
2. Numerical model
3. Results and discussion
4. Conclusions
Acknowledgements
References
160. Application of machine learning model to optimization of the hydrogen liquefaction process
Abstract
Keywords
1. Introduction
2. Hydrogen liquefaction Process
3. Machine learning application result
4. Conclusions
Acknowledgment
References
161. Density Functional Theory on the CO2 Absorption Process with Ionic Liquids
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
3.1. Ionic liquids
3.2. Ionic liquids and CO² complexes
4. Conclusions
Acknowledgments
References
162. Transport of CO²/CH4 through PEBA membranes: experiments and mass transfer modeling
Abstract
Keywords
1. Introduction
2. Methodology
3. Mathematical Model
4. Results
4.1. Characterization of the membrane
4.2. Membrane permeability and selectivity
4.3. Mathematical modelling
5. Conclusions
References
163. Mathematical modelling, simulation and optimisation of an indirect water bath heater at the Takoradi distribution station (TDS)
Abstract
Keywords
1. Introduction
2. Model dev elopment
2.1. Process description
2.2. Optimisation model
2.3. Parameter specifications
2.4. Variable specifications
3. Results and discussion
4. Conclusions
References
164. Marine SOx Scrubber: Mass transfer Analysis, Design, Simulation and Experiment
Abstract
Keywords
1. Introduction
2. Closed-Loop Square Scrubber With Spray
2.1. Proposed Methodology
2.2. Process Description
2.3. Design of Square Spray Column
3. Materials And Methods
3.1. Materials
3.2. Diesel Engine
3.3. Spray Column
3.4. Analytical Methods
4. Results and Discussion
4.1. Simulation
4.2. Scrubber Operation
4.3. Comparison Between Simulation And Experimental Results
5. Conclusions
6. Acknowledgement
References
165. Connecting the Simulation Model to the Digital Twin to help drive Sustainability
Abstract
Keywords
1. Introduction
2. The Digital Twin
3. Unified Engineering
4. Process Simulation lifecycle
5. Conclusion
References
166. Development of predictive model for the size of gas and liquid slugs formed in millimeter scaled T-junctions
Abstract
Keywords
1. Introduction
2. Method
2.1. Steijn's Model
2.2. Optical Signal Measurements
2.3. Micrograph Measurements
3. Experimental
3.1. Setup
3.2. Procedure
4. Results and discussion
4.1. Steijn's Model Evaluation
4.2. Gutter Flow Ratio
4.3. Incorporated Gutter Flow
4.4. Gutter Flow Model Construction
5. Conclusions
References
167. Enviro-economic assessment of DME synthesis using carbon capture and hydrogen from methane pyrolysis
Abstract
Keywords
1. Introduction
2. Material and methods
2.1. P rocess simulation and economic analysis
3. Results and discussion
3.1. Midpoint environmental analysis - emissions
3.2. Endpoint analysis and total cost
Conclusions
Acknowledgements
References
168. Operational Envelopes of Cost-effective Sour Gas Desulfurization Processes
Abstract
Keywords
1. Introduction
2. Process Simulations and Desulfurization Cost Calculations
2.1. Triazine-based scavenger process
2.2. Liquid redox process
2.3. Chemical oxidation (SourCatTM) process
2.4. Cost calculation
2.5. Modularization criteria
3. Results & Discussion
4. Conclusions
References
169. Process Alternatives for the Co-Production of Hydrogen and Methanol using Fuel Switch and Energy Mix Systems
Abstract
Keywords
1. Introduction
2. Modelling and Simulation
3. Process Description
4. Results and Discussion
4.1 Methanol and H² Production Rates and Overall Process Performance
5. Economic Analysis and Project Feasibility
6. Conclusions
Acknowledgements
References
170. Documenting Models Comprehensively Using a Minimal Graphical Language
Abstract
Keywords
1.1 Background
2. Foundation: Reductionism
3. Language as paper-and-pencil tool and documentation
3.1. Example espresso maker
3.2 Example: A melting process
3.3. Example molecular modelling
3.4. Corrosion - a moving boundary process
1.2 Conclusions
Acknowledgments
References
171. Simulation and CO² emission analysis for co-processing of bio-oil and vacuum gas oil
Abstract
Keywords
1. Introduction
2. Process description
2.1. Bio-oil production
2.2. Bio-oil co-processing with VGO
3. Aspen Simulation
3.1. Component provision and material method
3.2. Process module analysis
3.3. Simulation results
4. Results and discussion
4.1. CO² emission
4.2. Results
5. Conclusion
References
172. Dynamic Simulation and Optimization of a Subcritical Coal-Fired Power Plant During Load-Ramping Operations
Abstract
Keywords
1. Introduction
2. Dynamic model description
3. Dynamic simulations
4. Dynamic optimization
4. Conclusions
References
173. Solvent Screening Methodology considering Techno-Economic and Environmental Sustainability criteria for Algae Lipid Extraction
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Liquid-liquid equilibrium data calculation
2.2. LLE data analysis and classification
2.3. Evaluation of physicochemical properties of solvents
2.4. Evaluation of health, safety, and environmental performance of solvents
2.5. Process simulation
3. Results
4. Conclusions
References
174. Modeling and simulation of the production of n-butyl lactate in a reactive distillation column at pilot plant scale
Abstract
Keywords
1. Introduction
2. Process Modelling
2.1 Model description
2.2 Model assumptions
2.3 Balance Equations
3. Model simulation
4. Conclusions
Reference
175. Optimal Design of Offshore Wind Power Farm Considering Wind Uncertainty
Abstract
Keywords
1. Introduction
2. Problem definition
3. Problem formulation
4. Case study
5. Conclusions
References
176. Economic and environmental impact of fouling in produced water re-injection
Abstract
Keywords
1. Introduction
2. Motivating example
3. Results and Discussion
3.1. Operational Behavior
3.2. Economic and environmental performance
4. Conclusion
5. Acknowledgement
References
177. Mathematical Modelling of Reactive Inks for Additive Manufacturing of Charged Membranes
Abstract
Keywords
1. Introduction
2. Dynamic mathematical model for reactive-ink formulation
3. Materials and methods
3.1. Materials
3.2. Parameter estimation with multi-start
3.3. Local and global sensitivity analysis
4. Results and discussion
4.1. Parameter estimation with multi-start
4.2. Local and global sensitivity analysis
4.3. Partial parameter estimation
5. Conclusions
Acknowledgments
References
178. Economic Analysis of a Hydrogen Liquefaction Process Based on Techno-Economic and Energy Optimization
Abstract
Keywords
1. Introduction
2. Process description
3. Process optimization
4. Results
5. Discussion
6. Conclusions
References
179. How Digital Twins are Propelling Metals Industry to Next Generation Decision-Making: A Practitioner's View
Abstract
Keywords
1. Introduction
2. Understand Digital Twin Technology
3. An Industrial Example: Blast Furnace Digital Twin
4. Development Approach and Lessons Learned
5. Conclusion
References
180. The study on feasibility of HFO refrigerants in BOG re-liquefaction process
Abstract
Keywords
1. Introduction
2. Process design
3. Results and discussion
4. Conclusion
References
181. Crude Oil Blending Process Optimization with Precise Consideration of Fraction Properties
Abstract
Keywords
1. Introduction
2. Model description
2.1. Composition and material balance constraint
2.2. Device and inventory constraint
2.3. Supply constraint
2.4. Yield and property constraint
2.5. Set of molecular structure constraints
2.6. Set of time slot timing constraints
2.7. Objective function
3. Simulation case
4. Conclusions
Acknowledgements
Reference
182. Novel Design of Optimum Heat Exchanger Networks for Textile Dyeing Process to Maximize Wastewater Heat Recovery Efficiency
Abstract
Keywords
1. Introduction
2. Process description
3. Methodology
3.1. Development of the process model
3.2. Model modification by pinch analysis
3.3. Techno-economic analysis
4. Results and discussion
5. Conclusions
Acknowledgements
References
183. Study on the Kinetic Parameters of Crystallization Process Modelled by Partial Differential Equations
Abstract
Keywords
1. Introduction
2. Data for snowflake formation process: CA simulation
3. The dynamic equation of snowflake formation based on data: the establishment of partial differential equations
4. The influence of process parameters on snowflakes morphology: from the perspective of the reaction-diffusion system
4.1. The influence of reaction parameters on the morphology of snowflakes
4.2. The influence of diffusion parameters on the morphology of snowflakes
5. Conclusions
Acknowledgements
References
184. Graphical user interface for development of dynamics model of fermentation process applying long short-term memory networks
Abstract
Keywords
1. Introduction
2. Program overview and technical description
3. The Graphic User Interface (GUI)
4. Network performance and results visualization
5. Availability
6. Conclusions
Acknowledgments
References
185. The biorefinery concept for the industrial valorization of pineapple leaves co-producing ethanol, citric acid, and xanthan gum: a technoeconomic analysis
Abstract
Keywords
1. Introduction
2. Biorefinery process description
2.1 Ethanol Production Steps
2.2 Xanthan Gum Production Steps
2.3 Citric Acid Production Steps
3. Economic Analysis
4. Results
5. Conclusions
References
186. First Principles Based Development of Hybrid Models of Distillation Towers
Abstract
Keywords
1. Background
2. Case study
3. Modeling approach
3.1. Simplified first principles model
3.2. Error correction models
3.3. Training data-driven models
4. Results and discussion
5. Conclusions
6. References
187. Model-Based Development of Fuel Cell Stack and System Controllers
Abstract
Keywords
1. Introduction
2. FC-system controller and closed-loop simulation of the entire FC system
3. Simulation results and discussion
Conclusions
Acknowledgement
References
Contributed Papers: Optimization Methods and Computational Tools
188. A Nested Schur Decomposition Approach for Multiperiod Process Optimization
Abstract
Keywords
1. Introduction
2. Problem statement
3. Solution strategy
4. Implementation
5. Case study
6. Conclusions
References
189. Design and Optimization of Boil-off Gas Recycling Strategy in Liquefied Natural Gas Production
Abstract
Keywords
1. Introduction
2. Methodology
3. Results
4. Conclusions
References
190. An Implicit Function Formulation for Nonlinear Programming with Index-1 Differential Algebraic Equation Systems
Abstract
Keywords
1. Introduction
2. Background and Implementation
3. Case Studies
3.1. Chemical Looping Combustion Simulation
3.2. Chemical Looping Combustion Optimization
4. Conclusions
Disclaimer
Reference
191. Multi-objective optimization of NH³ and CO² separation with ionic liquid process
Abstract
Keywords
1. Introduction
2. Methods
2.1 Process flow chart of NH³/CO² separation with ionic liquids
2.2 MOO of NH³/CO² separation with ionic liquids
3. Results and discussion
4. Conclusion
References
192. Primal-dual Feedback-optimizing Control with Direct Constraint Control
Abstract
Keywords
1. Introduction
2. Recent Works and Problem Statement
3. Proposed Control Structure
4. Implementation in Subsea Oil Production Network
5 . Conclusions
6 . Acknowledgment
References
193. Data-driven coordination of expensive black-boxes
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
4. Conclusion
Acknowledgements
References
194. Data-Driven Adaptive Robust Unit Commitment Assisted by Machine Learning Techniques
Abstract
Keywords
1. Introduction
2. Data-driven robust unit commitment with disjunctive uncertainty sets
3. Case study based on IEEE 39-bus systems
4. Conclusions
References
195. Heat integration for superstructure models: A MILP formulation for easy implementation and fast computing
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Energy targeting model
2.2. Heat integration costs
3. Model evaluation
3.1. Performance test cases
3.2. Results
4. Applied case study
4.1. Power-to-Methanol application
4.2. Flowsheet synthesis and heat integration results
4.3. Model limitations
5. Conclusion
6. Funding
References
196. A Software Framework for Optimal Multiperiod Carbon-Constrained Energy Planning
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Mathematical Optimisation Formulation
4. Case Study
5. Conclusions
References
197. Superstructure optimisation in various carbon capture and utilisation supply chains
Abstract
Keywords
1. Introduction
2. System description
3. CCU optimisation model
4. Results
5. Conclusions
References
198. Efficient Scenario Generation for Stochastic Programs with Extreme Events
Abstract
Keywords
1. Introduction
2. Optimization Model - Screening Plan for Colorectal Cancer
3. Scenario Generation Methods and Their Application to the Model
3.1. Monte Carlo Methods
3.2. Space-filling Methods
3.3. Clustering Based SG Methods
4. Results and Discussion
5. Conclusions and Future Directions
References
199. A Sustainable Framework for Optimal and Flexible Design Under Uncertainty in Separation Processes: Exergy, Energy, Economic, and Environmental Aspects
Abstract
Keywords
1. Introduction
2. Case study
3. Framework description
3.1. Process simulation
3.2. Stochastic modelling: mathematical formulation
3.2.1 Uncertainty representation & sampling
3.2.2 4E aspects: Exergy, energy, economic, and environmental analysis
3.3. Exergy
3.4. Energy
3.5. Economy
3.6. Environment
3.7. Optimizer: Multi-Objective Genetic Algorithm
3.8. Optimal design under uncertainty: Making decision criteria
4. Results
5. Conclusion
Acknowledgments
References
200. Application of nonlinear surrogate models on optimization of carbon capture and utilization network
Abstract
Keywords
1. Introduction
2. Optimization problem formulation
3. Case study
4. Results and discussion
5. Conclusions
References
201. Systematic process energy optimization via multi-level heat integration: A case study on low-temperature reforming for methanol synthesis
Abstract
Keywords
1. Introduction
2. Background on heat integration and optimization
2.1 Pinch analysis
2.2 Mathematical optimization
3. Method for process energy optimization via multi-level heat integration
3.1 Optimization using the Integer-Cut Constraint method
4. Implementation for Methanol Synthesis
4.1 Results and Discussion
5. Conclusions
Acknowledgements
References
202. Bayesian Optimization for Automobile Catalyst Development
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Experimental condition
2.2. Bayesian optimization
3. Results
4. Conclusions
Acknowledgements
References
203. Capacity Planning for Sustainable Process Systems with Uncertain Endogenous Technology Learning
Abstract
Keywords
1. Introduction
2. Stochastic programming model
2.1. Capacity expansion constraints
2.2. Non-anticipativity constraints
2.3. Objective function
3. Industrial case study
4. Conclusions
References
204. Development of a bi-objective optimisation framework for mixed-integer nonlinear programming problems and application to molecular design
Abstract
Keywords
1. Introduction
2. Background and motivation
2.1. The Sandwich Algorithm
2.2. The Normal Boundary Intersection Method
3. Proposed Algorithm
3.1. Inner and outer approximation
3.2. Decomposition of the search space
3.3. Modification of the mNBI sub-problem
4. Performance of the SDNBI algorithm
5. Results and Discussions
6. Conclusions
Acknowledgements
References
205. Data-driven scenario generation for two-stage stochastic programming
Abstract
Keywords
1. Motivation
2. Literature review
3. Methodology and mathematical developments
4. Case studies - Capacity Planning under uncertainty
5. Conclusions and future work
References
206. Joint Chance Constrained Process Optimization through Neural Network Approximation
Abstract
Keywords
1. Introduction
2. Problem formulation
3. Neural network approximation-based optimization
4. Case Study
5. Conclusions
References
207. Gaussian Processes for Simulation-Based Optimization and Robust Design
Abstract
Keywords
Introduction
Gaussian Processes
Method
Results
Conclusions
Acknowledgements
References
208. Machine Learning-Enabled Optimization of Force Fields for Hydrofluorocarbons
Abstract
Keywords
1. Introduction
2. Methods
2.1. Force Field Model
2.2. Bayesian Optimization Workflow
3. Results
4. Conclusions
5. Acknowledgements
6. References
209. Design of an Event-Driven Rescheduling Algorithm via Surrogate-based Optimization
Abstract
Keywords
1. Introduction
2. Bike sharing rebalancing
3. Surrogate-based optimization
4. Results
5. Conclusions
Acknowledgement
References
210. A two-stage network optimization for sustainable treated wastewater planning
Abstract
Keywords
1. Introduction
1.1 Background
1.2 Literature review
2. Methodology
2.1 Problem Formulation
2.2 Case study
3 Results
4 Conclusions
5 References
211. Surrogate Modeling for Superstructure Optimization with Generalized Disjunctive Programming
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Software resources
3. Case Study
4. Results
5. Conclusions
References
212. Educational computer-aided tools towards Industry 4.0: recommendations and BioVL
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Identification of Learning requirements
2.2. Learning Design formulation
2.3. Learning Design verification
3. Results & discussion: BioVL
4. Conclusions & Future perspectives
References
213. Process Superstructure Optimization through Discrete Steepest Descent Optimization: a GDP Analysis and Applications in Process Intensification
Abstract
Keywords
1. Introduction
2. Generalized Disjunctive Programming
3. Discrete Steepest Descent Optimization
4. Discrete-steepest descent optimization as a disjunctive algorithm LD-SDA
5. Numerical Experiments
5.1. Continuously Stirred Tank Reactors in series superstructure
5.2. Rate-based catalytic distillation column
6. Conclusions
References
214. Advances in Generalized Disjunctive and Mixed-Integer Nonlinear Programming Algorithms and Software for Superstructure Optimization
Abstract
Keywords
1. Introduction
2. Mixed-Integer Nonlinear Programming
3. Generalized Disjunctive Programming
4. GDPLib, the library for GDP models
5. Conclusions
References
215. Designing Novel Structured Packings by Topology Optimization and Additive Manufacturing
Abstract
Keywords
1. Introduction
2. Generative Packing Design
2.1. Optimization Problem Formulation
2.2. Optimization Tool
2.3. Analysis Model
2.4. Topology Optimization Study
3. Results
4. Conclusions
Acknowledgement
References
216. Multi-Objective Bayesian Optimization for Design and Operating of Fluidized Bed Reactor
Abstract
Keywords
1. Introduction
2. Mathematical model : Fluidized Bed Reactor
2.1. Governing equation
2.2. Cost estimation
3. Methodology : Multi-objective Bayesian optimization
3.1. Gaussian process
3.2 Multi-objective Bayesian optimization : -Expected Hypervolume Improvement
4. Results
5. Conclusions
6. Acknowledgement
References
217. Analysis of Optimization Algorithms for Real-Time Optimization Applied on the Model of a Fluid Catalytic Cracking Unit
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and analysis
3.1. Sensitivity analysis
3.2. Assessment of optimization algorithms
3.3. Hybrid optimization strategy
4. Conclusions
References
218. Scalable Stochastic Programming with Bayesian Hybrid Models
Abstract
Keywords
1. Introduction
2. Methods
2.1 Stochastic Programming Formulation
2.2 Ballistics Firing Example
3. Results
4. Conclusions
Acknowledgement
References
219. A Combined Particle Swarm Optimization and Outer Approximation Optimization Strategy for the Optimal Design of Distillation Systems
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Studies
3.1. Description
3.2. Results and Discussion
4. Conclusions
References
220. A semantic based decision support framework to enable model and data integration
Abstract
Keywords
1. Introduction
2. Theoretical formulation of model/data integration
3. Implementation
4. Demonstration
5. Conclusion
References
Contributed Papers: Process Monitoring and Safety
221. Design of Non-Redundant Sensor Networks for Reliable Estimation in Nonlinear Systems
Abstract
Keywords
1. Introduction
2. Problem Definition
3. Proposed Methodology
3.1. Equation-Variable Matching
3.2. Reliability Computation
4. Example
5. Case Study
6. Conclusions
References
222. A Novel Global-Local Feature Preserving Projection Method Based on Adaptive Linear Local Tangent Space Alignment for Process Monitoring
Abstract
Keywords
1. Introduction
2. NGLFPP Algorithm
2.1. Neighbourhood Construction
2.2. Local Feature Extraction
2.3. Global Feature Extraction
2.4. Unified Objective for NGLFPP
3. NGLFPP-Based Process Monitoring
4. Case Study
5. Conclusion
References
223. Prognostics on Noisy and Uncertain Dynamic Systems using Cumulative Sum Chart of Inferential Sensors
Abstract
Keywords
1. Introduction
2. Methods
2.1. System model representation
2.2. Active FDI test design optimization
2.3. Cumulative Sum control chart
2.4. Genetic Programming
3. Case Study
4. Results - Discussion
5. Conclusions
References
224. Quantifying Subsea Gas Leakages using Machine Learning: a CFD-based study
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
4. Conclusions
Acknowledgments
References
225. Dynamic Risk Analysis for Process Safety
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Safety critical variable analysis
2.2. System monitoring
2.3. Dynamic risk analysis
3. Application of the proposed methodology
3.1. Introduction of the coal slurry gasification
3.2. Determine safety critical variables
3.3. Fault detection
3.4. Dynamic risk analysis for the gasification
4. Conclusions
References
226. Monitoring of smart chemical processes: A Sixth Sense approach
Abstract
Keywords
1. Introduction
2. System architecture
2.1. Industrial process
2.2. Communication network
2.3. Machine learning
2.4. Cooperative control
2.5. Decision-making system
3. Results
4. Conclusions
References
227. Fault detection in a benchmark simulation model for wastewater treatment plants
Abstract
Keywords
1. Introduction
1.1. Benchmark simulation models
2. Methods
2.1. Sensor/actuator fault generation
2.2. Process fault generation
2.3. Fault detection
2.4. Performance evaluation
3. Results
3.1 Sensor/actuator fault
3.2 Process fault
4. Conclusion
References
228. Formulation of integrated key performance indicator dashboard for chemical plant
Abstract
Keywords
1. Introduction
2. Integrated KPI
3. KPI tree graph
4. KPI balance graph
5. KPI trend graph
6. Case S tudy
7. Conclusion
References
229. Evaluation of risk in the biodiesel production process with supercritical ethanol
Abstract
Keywords
1. Introduction
2. Case study
3. Process simulation
4. Risk assessment
5. Results
6. Conclusions
Acknowledgments
References
230. Process Monitoring Based on Deep Neural Networks with Continuous Wavelet Transform
Abstract
Keywords
1. Introduction
2. Method
2.1. Continuous wavelet transforms
2.2. 3D convolutional neural network
2.3. Proposed model
3. Case study
4. Result
4.1. Metrics for evaluation
4.2. Application to TEP
5. Discussion
6. Conclusions
References
231. Methyl sec-butyl ether content estimation in MTBE products via clustering-based adaptive nonlinear soft sensors
Abstract
Keywords
1. Introduction
2. Industrial plant description and problem formulation
3. Methods used for model evaluation
3.1. Alternating Conditional Expectation (ACE)
3.2. Kernel-based Orthogonal Projections to Latent Structures (Kernel-OPLS)
3.3. Neural networks
4. Description of the proposed adaptation algorithm
5. Results and discussion
5.1. Comparison of models accuracy
5.2. Comparison of computational costs for adaptive soft sensors
6. Conclusions
7. Acknowledgements
References
232. Early identification of abnormal deviation in nonstationary processes by removing non-stationarity
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Stationarity test
2.2. Mutual information (MI)
2.3. Support vector regression (SVR)
2.4. Principal component analysis (PCA)
3. The proposed monitoring strategy by removing process non-stationarity
3.1. Strategy for removing process non-stationarity
3.2. The implementation procedures of the proposed process monitoring framework
4. Case studies on Tennessee Eastman process (TEP)
4.1. Tennessee Eastman process and data description
4.2. Results and discussion
5. Conclusions
References
233. AI System for Substance Identification Based on Chemical Substance-Symptom Knowledge Graph
Abstract
Keywords
1. Introduction
2. P roposed System: SE ARCH
3. Chemical-symptom knowledge base generation
3.1. Chemical and symptom data collection
3.2 . Chemical information and molecular structure preprocessing
3.3. Chemical substance-symptom knowledge base construction
4. Knowledge verification using knowledge graph embedding
4.1. Adaptation of KB embedding algorithm
4.2. Knowledge verification results
5. Identification of symptom-based exposure substances
6. Symptom knowledge expansion using DNN
6.1. Adaptation of DL algorithm
6.2. Result of model performance assessment
7. Conclusions
References
234. Model-based monitoring of an intensified unit for continuous pharmaceutical filtration-drying
Abstract
Keywords
1. Introduction
2. Continuous filtration-drying of paracetamol/ethanol slurries
3. Monitoring system: implementation and proof of concept
Conclusions
Acknowledgements
References
235. Plant Fault Diagnosis System using Negative Selection Algorithm
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Fault Detection using Negative Selection Algorithm
2.2. Fault Diagnosis Method
3. Simulations Results
4. Conclusions
References
236. Digital Twin of a pilot-scale bio-production setup
Abstract
Keywords
1. Introduction
2. Digital Models
2.1. Data-driven vs. mechanistic models
2.2. Hybrid models
3. Proposed Framework
4. L essons learnt
4 .1. Minimum Communication Req uirements
4.2. Minimum Modeling Requirements
4.3. Potential Fault Detection
5. Conclusions
Acknowledgements
References
237. Plant O& M Support System Based on Supervised Data-Clustering Technology
Abstract
Keywords
1. Introduction
2. Proposed system
2.1 Overview of the proposed system
2.2 Data clustering algorithm
3. Data analysis and results
4. Conclusions
References
238. A Novel Cycle Partitioning Approach to Reliability Based Optimal Sensor Placement for Linear Flow Processes
Abstract
Keywords
1. Introduction
2. Preliminaries related to reliability based sensor placement design
3. Proposed cycle partitioning based sensor placement design
3.1. Cycle-variable bipartite graph partitioning algorithm and SPD formulation
4. Case Study
5. Conclusions
References
239. The impact of sampling frequency on chemical process monitoring
Abstract
Keywords
1. Introduction
2. Methodology
2.1. The auto-correlation functions
2.2. Principal component analysis (PCA)
2.3. Dynamic principal component analysis (DPCA)
3. Selection of optimal sampling frequency and its application on Tennessee Eastman Process (TEP)
3.1. Tennessee Eastman Process (TEP) and data description
3.2. Determination of the optimal sampling frequency in this work
3.3. Selection of optimal sampling frequency in TEP
4. Results and discussion
5. Conclusions
References
240. Autoregressive Distributed Lag Model Based Cointegration Analysis for Batch Process Monitoring
Abstract
Keywords
1. Introduction
2. ADL model based cointegration analysis
3. ADL cointegration test based batch process monitoring approach
4. Case study on penicillin process
4.1. Process description and data preparation
4.2. Batch process monitoring based on proposed method
4.3. Monitoring result analysis and discussion
5. Conclusion
Acknowledgements
References
241. A Data-Driven Fault Detection and Diagnosis by NSGAII-t-SNE and Clustering Methods in the Chemical Process Industry
Abstract
Keywords
1. Introduction
2. Theory
2.1 Data Pre-processing
2.2 Clustering
3. Results and discussion
3.1. Data normalization
3.2. Feature selection
3.3. Feature extraction
3.4. Fault detection and diagnosis
3.5. Evaluation
4. Conclusion
References
Contributed Papers: Cyber-Physical Systems and Security
242. Cyberattack Detectability-Based Controller Screening: Application to a Nonlinear Process
Abstract
Keywords
1. Introduction
2. Controller Screening Methodology
3. Application to a Nonlinear Chemical Process
4. Conclusions
References
243. OPC UA information transfer via unidirectional data diode for ICS cyber security
Abstract
Keywords
1. Improved security by combining data diode and OPC UA
2. OPC UA secure communication via the unidirectional data diode
2.1. Basic OPC UA Client/Server models encryption key exchange
2.2. Basic OPC UA PubSub models encryption key exchange
2.3. Encryption key exchange via the unidirectional data diode
2.4. OPC UA PubSub Data encryption and signature
3. Conclusions
References
244. Study on Device Authentication System for Dynamic Zoning of Industrial Control Systems
Abstract
Keywords
1. Introduction
2. Device Authentication System for Dynamic Zoning
2.1. Device Authentication System with Authentication Switch for ICSs
2.2. Device Authentication System with Security Unit for Mobility Network Systems
3. System Implementation and Results
4. Discussion
5. Conclusions
References
245. Designing Framework for Tabletop Exercise to Promote Resilience Against Cyber Attacks
Abstract
Keywords
1. Introduction
2. Exercises for improving resilience developed
2.1. Type1: Roleplay based Cyber Defense Exercise [4]
2.2. Type2: Workflow Based Cyber Defense Exercise [5]
3. Card-Type Incident Response Exercise
4. Pilot Exercise
5. Conclusions
References
246. Self-Organizing Map Based Approach for Assessment of Control Room Operator Training
Abstract
Keywords
1. Introduction
2. Experimental Studies and Methodology
3. Results and Discussion
4. Conclusions
Acknowledgments
References
247. Digital Twin of Alkaline Water Electrolysis Systems for Green Hydrogen Production
Abstract
Keywords
1. Introduction
2. Alkaline Water Electrolysis System
3. Model Description
3.1. AWE cell model in Python
3.1.1. Reversible voltage
3.1.2. Activation overvoltage
3.1.3. Ohmic overvoltage
3.1.4. Hydrogen production rate
3.2. AWE system modelling in gPROMS
4. Simulation Results
4.1. Model validation
4.2. AWE system simulation
4.2.1. Without compressor power
4.2.2. With compressor power
5. Conclusions
References
Acknowledgements
248. Cyber Security Risks of aspects of operations of OPC Unified Architecture
Abstract
Keywords
1. Introduction
2. Related Research
3. Proposed approach
3.1. Attack scenarios
3.2. Evaluation environment
4. Evaluation Result
4.1. Unauthorised connection to OPC UA server
4.2. Decryption of OPC UA message
5. Recommendation for secure practice using OPC UA
6. Conclusions
References
249. Managing Experimental-Computational Workflows in Robotic Platforms using Directed Acyclic Graphs
Abstract
Keywords:
1. Introduction
2. Experimental-computational Workflows
3. Case study
4. Airflow-based implementation environment
4.1. Architecture of the workflow manager
4.2. Project workflow manager
4.3. Airflow ecosystem
5. Concluding remarks
References
250. Development of cyber incident exercise to be widely adopted in supply chains
Abstract
Keywords
1. Introduction
2. IMANE CARD
2.1 Components of the IMANE Card
2.2 Procedure for the IMANE Card exercise
3. Online IMANE Card
3.1 The hurdles to improve for the incident response exercise
3.2 Components of the online IMANE Card
3.3 Procedure for the online IMANE Card exercise
4. Conclusions
References
251. Requirements to a digital twin-centered concept for smart manufacturing in modular plants considering distributed knowledge
Abstract
Keywords
1. Introduction
2. Simulation in the life cycle of conventional and modular plants
3. The digital twin and the distribution of knowledge in modular plants
4. A digital twin-centered concept for smart manufacturing in MPs
4.1. The smart PEA as cyber-physical system for smart manufacturing in modular plants
4.2. Simulation in the life cycle of smart modular plants
4.2.1. Design simulation and offline optimization in smart modular plants
4.2.2. Virtual commissioning in smart modular plants
4.2.3. Operator training in smart modular plants
4.2.4. Online optimization in smart modular plants
4.3. R&D challenges
5. Conclusion
References
Back Cover
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Contributed Papers: Machine Learning and Big Data
252. Equivalence Judgment of Equation Groups Representing Process Dynamics
Abstract
Keywords
1. Introduction
2. Proposed Method
2.1. Conversion of Equations
2.2. Equivalence Judgment of Equations
2.3. Equivalence Judgment of Equation Groups
3. Case Studies
4. Conclusion
Acknowledgments
References
253. Data-driven operation support for equipment deterioration detection in drug product manufacturing
Abstract
Keywords
1. Introduction
2. Methodology
3. Case study
4. Results & Discussion
4.1. Detection
4.2. Localization
4.3. Prevention
5. Conclusion
References
254. Pilot Plant 4.0: A Review of Digitalization Efforts of the Chemical and Biological Engineering Department at the Technical University of Denmark (DTU)
Abstract
Keywords
1. Introduction
2. Overall Framework and Infrastructure
3. Database Design
4. Digital Twin Integration
5. Conclusions
References
255. Identification Method of Multiple Sequential Alarms that Occured Simultaneously in Plant-operation Data
Abstract
Keywords
1. Introduction
1.1. Plant alarm systems
1.2. Previous research
1.3. Objective
2. Proposed method
2.1. Plant-operation data
2.2. Problem formulation
2.3. Preparation
2.4. Similarity evaluation method
2.5. Grouping
2.6. Calculation procedure
3. Case study
3.1. Simulation Data
3.2. Results of identified sequential alarms
4. Conclusions
References
256. Understand how CNN diagnoses faults with Grad-CAM
Abstract
Keywords
1. Introduction
2. Explainable CNN and Grad-CAM
3. Understand how CNN diagnoses faults
3.1. CNN-based fault diagnosis
3.2. Tennessee Eastman process
3.3. Data preparation and model training
3.4. Explain fault diagnosis results with Grad-CAM
4. Conclusions
References
257. A Comprehensive Framework for the Modular Development of Condition Monitoring Systems for a Continuous Dry Granulation Line
Abstract
Keywords
1. Introduction
2. Condition Monitoring Framework Development
2.1. A Probabilistic Condition Monitoring Model for Continuous Dry Granulation
2.2. Probabilistic Programming and Inference
3. Results and Discussion
3.1. Parameter Learning
3.2. Predictive Modeling
4. Conclusions
5. References
258. Framework for Suppressing Transient Fault Alarms Online
Abstract
Keywords
1 Introduction
2 Algorithm for suppressing transient fault alarms online
2.1 T² alarms
2.2 Q alarms
3 Case study
4 Conclusions
References
259. Using Reinforcement Learning in a Game-like Setup for Automated Process Synthesis without Prior Process Knowledge
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Example Process and Flowsheet simulation
2.2. Agent structure and training procedure
2.3. Evaluation
3. Results
4. Conclusions
Funding
References
260. Generation and Benefit of Surrogate Models for Blackbox Chemical Flowsheet Optimization
Abstract
1. Introduction
2. Case Study
3. Framework for Flowsheet Optimization
4. Evaluation and generation of surrogate-models
5. Results
6. Conclusions
Acknowledgement
References
261. Flowsheet Recognition using Deep Convolutional Neural Networks
Abstract
Keywords
1. Introduction
2. Deep Convolutional Neural Networks
3. Method
3.1. Data Set
3.2. Data Augmentation and Oversampling
3.3. Model Training
4. Results and Discussions
5. Conclusions
References
262. Active learning for multi-objective optimizaiton of processes and energy systems
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Superstructure optimization
2.2. Pareto-active learning
3. Application
Results
4. Conclusion and outlook
Acknowledgements
References
263. Data-driven Stochastic Optimization of Numerically Infeasible Differential Algebraic Equations: An Application to the Steam Cracking Process
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Steam Cracking Optimization: Problem Formulation
2.2. Scenario Analysis for the Stochastic Feed Compositions
2.3. Mapping the Feasible Region og Implicit Constraints with Support Vector Machines
3. Results
3.1. Performance Metrics for the SVM Classifier in the Offline Phase
3.2. Optimal Solution: Reactor Design Parameters and Key Results in the Online Phase
4. Conclusions
References
264. Tensor-Based Autoencoder Models for Hyperspectral Produce Data
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Residual Tensor Autoencoder (AE) Architecture
2.2. Non-Linear Architectures of the Fully Connected Autoencoder
2.3. Multi-Task Learning: Classification of Reduced Tensors
3. Experimental Results
4. Conclusions
5. Acknowledgements
References
265. Molecular Representations in Deep-Learning Models for Chemical Property Prediction
Abstract
Keywords
1. Introduction
2. Methods
2.1. Models
2.1.1. Fixed representation models
2.1.2. Adaptive/learned representation models
2.2. Training & Optimization
3. Case Study: Predicting the enthalpy of formation of organic compounds
3.1. Property Data
3.2. Results
3.3. Discussion
4. Conclusions
References
266. Deep Reinforcement Learning for Continuous Process Scheduling with Storage, Day-Ahead Pricing and Demand Uncertainty
Abstract
Keywords
1. Introduction
2. Soft Actor-Critic (SAC) Method
3. System Formulation and Description
4. Case Study Results
4.1. Case Study 1: Perfect Information Scenario
4.2. Case Study 2: Demand Forecast Uncertainty
5. Conclusions
References
267. Convolutinoal Neural Network based Detection and Measurement for Microfluidic Droplets
Abstract
Keywords
1. Introduction
2. Experiment
3. Method
4. Results and discussions
4.1. Model tuning
5. Conclusions
References
268. Deep Reinforcement Learning Based Controller for Modified Claus Process
Abstract
Keywords
1. Introduction
2. Seq2Seq and A2C Networks
3. Industrial Example
4. Conclusions
References
269. Process performance prediction based on spatial and temporal feature extraction through bidirectional LSTM
Abstract
Keywords
1. Introduction
2. Reactor network process
3. Feature extraction by bidirectional Long short-term memory networks
4. Results
5. Conclusions
References
270. Exploring the Potential of Fully Convolutional Neural Networks for FDD of a Chemical Process
Abstract
Keywords
1. Introduction
2. Methods
2.1. Tennessee Eastman Process Benchmark
2.2. Data collection and preprocessing
2.3. CNN based FDD framework
3. Results and Discussion
4. Conclusions
References
271. Data-driven online scenario selection for multistage NMPC
Abstract
Keywords
1. Introduction
1.1. Multistage MPC
1.2. Motivation
1.3. Notation
2. Sensitivity assisted multistage NMPC
3. Data driven sensitivity assisted multistage NMPC
3.1. Principal component analysis
3.2. Algorithm for scenario selection using both data and NLP sensitivities
4. Case study
4.1. Data analysis
4.2. Results
5. Conclusions
References
272. Data-driven Robust Model Predictive Control with Disjunctive Uncertainty for Building Control
Abstract
Keywords
1. Introduction
2. Model formulation
2.1. Complete state-space model
2.2. PCA and KDE based data-driven uncertainty sets clustered by K-means algorithm
3. Control strategy
4. Case study
5. Conclusions
6. Nomenclature
References
273. Low-Dimensional Input and High-Dimensional Output Modelling Using Gaussian Process
Abstract
Keywords:
1. Introduction
2. Related works
2.1. Decomposing Sparse and Low-Rank Matrices
2.2. Gaussian Process
3. High-dimensional-output modelling method
4. Case studies
4.1. Homo-polymerization Ziegler-Natta Catalyst System
4.2. Projection of MWD Matrices on Intrinsic-Low-dimensional Matrices
4.3. LS-MGP Prediction
5. Conclusions
References
274. Piecewise Smooth Hybrid System Identification for Model Predictive Control
Abstract
Keywords
1. Introduction
2. Hybrid System Identification
2.1. Problem Definition
2.2. Challenges of Hybrid System Identification
2.3. Spectral Clustering for Hybrid System Identification
3. Local Predictive Clustering
3.1. Similarity Function
3.2. Graph Construction and Clustering
3.3. Local Models
3.4. Parameter Tuning
3.5. From Local Predictive Clustering to Model Predictive Control
4. Case Study
5. Conclusions
References
275. Distillation Column Temperature Prediction Based on Machine-Learning Model Using Wavelet Transform
Abstract
Keywords
1. Introduction
2. Methods
2.1. Description of the distillation process
2.2. Figure 1. Mixed butane splitter process diagram. Wavelet transforms and wavelet basis functions
2.3. Long short-term memory
3. WT-LSTM model development
4. Results and discussion
4.1. Wavelet basis functions
4.2. Performance evaluation
5. Conclusion
Acknowledgement
References
276. Moisture Estimation in Woochips Using IIoT Wi-Fi and Machine Learning Techniques
Abstract
Keywords
1. Introduction
2. Data collection and feature engineering
2.1. Channel state information for moisture estimation
2.2. Data description
2.3. Methodology and feature engineering
3. Results and discussion
4. Conclusions
References
277. Transfer Learning for Quality Prediction in a Chemical Toner Manufacturing Process
Abstract
Keywords
1. Introduction
2. Chemical toner manufacturing process
3. Prediction using transfer learning
3.1. Frustratingly Easy Heterogeneous Domain Adaptation
3.2. Prediction Model
4. Comparison of prediction methods
5. Application to a mass-production plant
6. Conclusions and future tasks
References
278. Towards An Automated Physical Model Builder: CSTR Case Study
Abstract
Keywords
1. Introduction
2. Automated Physical Model Builder
2.1. Document Format Conversion
2.2. Information Extraction
2.3. Equivalence Judgment and Unification
2.4. Integration & Scoring
3. Case Study
3.1. Implementation
3.2. Dataset
3.3. Results & Discussion
4. Conclusions
Acknowledgments
References
279. Forward physics-informed neural networks for catalytic CO² methanation via isothermal fixed-bed reactor
Abstract
Keywords:
1. Introduction
2. Isothermal fixed-bed reactor for CO² methanation
3. Forward PINN structure
4. Results and discussion
5. Conclusions
References
280. Hashing-based just-in-time learning for big data quality prediction
Abstract
Keywords
1. Introduction
2. Preliminaries
2.1. Just-in-time (JIT) modelling method
2.2. Gaussian process regression (GPR)
3. Hashing-based just-in-time (HbJIT) modeling method
4. Case studies
5. Conclusions
References
281. Physics-Constrained Autoencoder Neural Network for the Prediction of Key Granule Properties in a Twin-Screw Granulation Process
Abstract
Keywords
1. Introduction
2. Methods
2.1. Data collection and completion methods
2.2. Development of Physics-constrained supervised auto-encoders (PCSAE)
3. Results
3.1. Performance of the PCSAE
3.2. Sensitivity analysis of PCSAE
4. Conclusions
References
282. CSTR control with deep reinforcement learning
Abstract
Keywords
1. Introduction
2. Reinforcement Learning and Deep Reinforcement Learning
2.1. Twin Delayed DDPG: TD3 algorithm
2.2. Deep Reinforcement Learning for process control
3. Case study
3.1. Implementation of the process
4. Simulation results
5. Conclusions and further work
References
283. Application of machine learning and big data for smart energy management in manufacturing
Abstract
Keywords
1. Introduction
Methodology
1.1. Machine specific energy disaggregation
1.2. Day-ahead energy scheduling via data-driven optimization
2. Results
2.1. Energy Disaggregation
2.2. Data-driven stochastic optimization for day-ahead energy scheduling
3. Conclusion
References
284. Adaptive least-squares surrogate modeling for reaction systems
Abstract
Keywords
1. Introduction
2. Problem statement
3. Surrogate model building: an adaptive sampling algorithm
4. Example
5. Conclusions
References
285. Machine Learning and Inverse Optimization Approach for Model Identification of Scheduling Problems in Chemical Batch Plants
Abstract
Keywords
1. Introduction
2. Problem description
2.1. Estimation problem for weighting factors in the objective function
2.2. Production scheduling problem
3. Proposed approach
3.1. Machine Learning Algorithm
3.2. Inverse Optimization Approach
4. Computational experiments
4.1. Randomly generated instances
5. Application to petrochemical batch plant
5.1. Case study
6. Conclusion and future works
References
286. Decision-Focused Surrogate Modeling with Feasibility Guarantee
Abstract
Keywords
1. Introduction
2. Mathematical Formulation
3. Solution Strategy
4. Computational Case Study
5. Conclusions
References
287. Grade transition optimization by using gated recurrent unit neural network for styrene-acrylonitrile copolymer process
Abstract
Keywords
1. Introduction
2. Process description
3. Data-driven GRU dynamic model
3.1. Data collection and pre-processing
3.2. Variable selection
3.3. MI simulation method and results
3.4. MI real-time prediction
4. Improvement of grade transition
4.1. Controller design
4.2. Grade transition result
5. Conclusions
References
288. Development of Estimating Algorithm for Biodegradation of Chemicals Using Clustering and Learning Algorithm
Abstract
Keywords
1. Introduction
2. Methods
2.1. Clustering algorithm
2.2. Machine learning algorithm
2.3. Objective data
3. Results and Discussions
4. Conclusions
Acknowledgements
References
289. Surrogate Classification based on Accuracy and Complexity
Abstract
Keywords
1. Introduction
2. Data sets, Surrogate Forms, and Performance Metrics
2.1. Data sets
2.2. Surrogate Forms
2.3. Performance Metric
3. Similarity Assessment and Families Identification
4. Families for NNR2, NNSQS, NR2, and NSQS
5. Conclusions
References
290. Training Stiff Dynamic Process Models via Neural Differential Equations
Abstract
Keywords
1. Introduction
2. Methods
3. Results
4. Conclusions
References
291. Wiz 4.0: A Novel Data Visualization and Analytics Dashboard for a Graphical Approach to Industry 4.0
Abstract
Keywords
1. Background
2. Methods
3. Results and Discussion
4. Conclusion
Acknowledgements
References
292. About data reduction techniques and the role of outliers for complex energy systems
Abstract
Keywords
1. Introduction
2. Method
2.1. Time Series aggregation
2.2. Outlier detection
3. Case study
4. Results and Discussion
4.1. Time Series Aggregation
4.2 Outlier detection
5. Conclusion
References
293. Deepgsa: Plant Data-Driven Global Sensitivity Analysis using Deep Learning
Abstract
Keywords
1. Introduction
2. Methods
2.1. Sobol Method
2.2. Derivative-Based Global Sensitivity Method (DGSM)
3. DeepGSA: Toolbox for plant data-driven and DL-assisted GSA
4. Case Study
4.1. Benchmark Case Study: Sobol g-function
4.2. Plant Data Case Study: Modelling liquid N²O concentration in WWTP
5. Conclusions & Future work
References
294. Analyzing Different Dynamically Modelled Data Structures and Machine Learning Algorithms to Predict PM2.5 Concentration in China
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Dataset
2.2. Data Pre-processing
2.3. Data Structures
2.4. Prediction Model
3. Results and Discussion
4. Conclusion
Acknowledgement
References
295. A multi-output machine learning approach for generation of surrogate models in process engineering
Abstract
Keywords
1. Introduction
2. Multi-output machine learning strategy
3. Case studies
4. Numerical results and discussion
5. Conclusions and future directions
Acknowledgements
References
296. Practical Human Interface System for Transition Guidance in Chemical Plants using Reinforcement Learning
Abstract
Keywords
1. Introduction
2. Related work
2.1. Simulation-based optimal control
2.2. Explainable AI
2.3. Sensitivity analysis
3. Proposed method
3.1. Operation flow
3.2. Assessment of the offline procedure
3.3. Assessment of the online action
4. Experiment
5. Conclusions
Acknowledgements
References
297. Surrogate modeling for nonlinear gasoline blending operations
Abstract
Keywords
1. Introduction
2. Problem statement
3. Surrogate modeling methodology
4. Results and discussion
5. Conclusion
References
298. Continuous Manufacturing Process Sequential Prediction using Temporal Convolutional Network
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Process description
2.2. Temporal convolutional network sequence-to-sequence (TCN-StS) Model
3. Result and discussion
4. Conclusions
Acknowledgment
References
299. Surrogate modeling for mixed refrigerant streams in the refrigeration cycle of an LNG plant
Abstract
Keywords
1. Introduction
2. Problem Statement
3. Methodology
4. Results
5. Conclusion
References
300. Prediction for heat deflection temperature of polypropylene composite with Catboost
Abstract
Keywords
1. Introduction
2. Method
2.1. Categorical data treatment
2.2. Catboost
3. Results and discussions
3.1. Dimensionless number "A" for categorical data treatment
3.2. Comparison of the three algorithms
4. Conclusion and future work
Acknowledgements
References
301. A New Machine Learning Framework for Efficient MOF Discovery: Application to Hydrogen Storage
Abstract
Keywords
1. Introduction
2. Methods
3. Case Study
4. Conclusions
References
302. Data-driven Modeling for Magma Density in the Continuous Crystallization Process
Abstract
Keywords
1. Introduction
2. Preliminaries
2.1. Deep neural network
2.2. Recurrent neural network : LSTM and GRU
3. Development of the magma density prediction model
3.1. Process and data description
3.2. Model structure
4. Results and discussion
4.1. Density prediction accuracy
4.2. Application for steam flow rate control
5. Conclusion
Acknowledgement
References
303. Gaussian Process Regression Machine Learning Models for Photonic Sintering
Abstract
Keywords
1. Introduction
1.1. Background
2. Method
2.1. Decision Variables and Data
2.2. Gaussian Process Regression
2.3. Hyperparameter Tuning
3. Results
3.1. Log Marginal Likelihood (LML) and Leave-one-out Cross-Validation (Loo-CV) identify similar hyperparameter values
3.2. Retrospective Analysis
4. Conclusion
Reference
304. Development of Dye Exhaustion Behavior Prediction Model using Deep Neural Network
Abstract
Keywords
1. Introduction
2. Process description
3. Methodology
3.1. Data generation and preprocessing
3.2. Development of DNN-based prediction model
4. Results and discussion
4.1. Performance of the DNN-based prediction model
4.2. Prediction results of the dye exhaustion behavior
5. Conclusions
Acknowledgements
References
305. Guaranteed Error-bounded Surrogate Modeling and Application to Thermodynamics
Abstract
Keywords
1. Introduction
2. THEORETICAL BOUNDED APPROXIMATION OF BLACKBOX MODELS
2.1. Edge-concave underestimation and edge-convex overestimation based bounding
2.2. Bounded Surrogate Model Parameter Estimation Formulation
3. GEMS FRAMEWORK
4. APPLICATION TO SURROGATE THERMODYNAMIC MODELING
5. CONCLUSIONS
6. Acknowledgment
References
306. Development of an ANN-based soft-sensor to estimate pH variations in Intelligent Packaging Systems with visual indicators
Abstract
Keywords
1. Introduction
2. Materials and methods
2.1. Chitosan Intelligent films
2.2 Color indication intelligent device
2.3 Development of empirical mathematical models using Artificial Neural Networks
3. Results
4. Conclusions
Acknowledgments
References
307. Process Systems Engineering Guided Machine Learning for Speech Disorder Screening in Children
Abstract
Keywords
1. Introduction
2. Materials and Methods
2.1. Data description
2.2. Methodology
3. Results and discussion
4. Conclusions
References
Contributed Papers: Energy, Food and Environmental Systems
308. Emission and mitigation of CO² and CH4 produced by cattle: a case study in the Brazilian Pantanal
Abstract
Keywords
1. Introduction
2. Livestock in the Brazilian Pantanal region
3. The system dynamics (SD) model
4. Material and methods
5. Results
6. Conclusion
7. References
309. Promoting phosphorus recovery at livestock facilities in the Great Lakes region: Analysis of incentive policies
Abstract
Keywords
1. Introduction
2. Framework for the assessment of incentive policies
3. Results and discussion
3.1. Combined effect of incentives for phosphorus and renewable electricity recovery
3.2. Environmental cost-benefit analysis
3.3. Fair distribution of incentives
4. Conclusions
References
310. Production of ethanol, xylitol and antioxidants in a biorefinery from olive tree wastes: process economics, carbon footprint and water consumption
Abstract
Keywords
1. Introduction
2. Materials and Methods
2.1. Feedstock
2.2. Process modelling
2.3. Process description
2.4. Economic evaluation
2.5. Carbon footprint and water consumption
3. Results and Discussion
3.1. Process design and simulation
3.2. Economic evaluation
3.3. Carbon footprint and water consumption
4. Conclusions
References
311. Application of CAPE Tools into Prospective Life Cycle Assessment: A Case Study in Acetylated Cellulose Nanofiber-Reinforced Plastics
Abstract
Keywords
1. Introduction
2. Materials and methods
2.1. Application of CAPE tools into prospective LCA
2.2. Case study: Acetylation of pulp for AcCNF-RP
3. Results and discussion
4. Conclusions
Acknowledgement
References
312. Climate Control in Controlled Environment Agriculture Using Nonlinear MPC
Abstract
Keywords
1. Introduction
2. Dynamic model formulation
3. Nonlinear model predictive control
4. Case studies on simulated CEA
5. Conclusions
References
313. Thermodynamic Analysis of an Integrated Renewable Energy Driven EWF Nexus: Trade-Off Analysis of Combined Systems
Abstract
Keywords
1. Introduction
2. System Description
3. Thermodynamic Analysis & Results
4. Conclusion
5. Acknowledgment
References
314. Low-Carbon Hydrogen Production in Industrial Clusters
Abstract
Keywords
1. Introduction
2. Methodology
3. Results & Discussion
4. Conclusions
References
315. Thermoacoustic Flow-Through Cooler for Cryogenic Hydrogen
Abstract
Keywords
1. Introduction
2. Mathematical Model
3. Sample Results
4. Conclusions
References
316. Life Cycle Assessment of Green Hydrogen Transportation and Distribution Pathways
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and discussion
4. Conclusions
References
317. Sector coupling of green ammonia production to Australia's electricity grid
Abstract
Keywords
1. Introduction
2. Methodology
3. Grid Connectivity Results
4. Impacts of Scale
5. Operating Considerations
6. Conclusions
References
318. Development of Multi-Purpose Dynamic Physical Model of Fuel Cell System
Abstract
Keywords
1. Introduction
2. Physical modeling methods of FC system
3. Model validation and verification
Conclusions
Acknowledgement
References
319. Embracing the era of renewable energy: model-based analysis of the role of operational flexibility in chemical production
Abstract
Keywords
1. Introduction
2. Case study 1: methanol production
2.1. System overview and modelling approach
2.2. Results
3. Case study 2: aluminium production
3.1. System overview and modelling approach
3.2. Results
4. Conclusions
References
320. Hollow Fiber-based Rapid Temperature Swing Adsorption (RTSA) Process for Carbon Capture from Coal-fired Power Plants
Abstract
Keywords
1. Introduction
1.1. Global Warming and Carbon Capture
1.2. Hollow Fiber-Based Rapid Temperature Swing Adsorption
2. Process Description
3. Economic Analysis
3.1. Sensitivity of Price Annualize Factor
4. Conclusions
References
321. Determining Accurate Biofuel System Outcomes: Spatially Explicit Methods for Combined Landscape-Feedstock and Supply Chain Design
Abstract
Keywords
1. Background
2. Landscape Design Model
3. Model and Data Integration
4. Results
4 .1. Case Study Description
4.2. Landscape Design Benefit
5. Conclusions
References
322. Assessing the Environmental Potential of Hydrogen from Waste Polyethylene
Abstract
Keywords
1. Introduction
2. Methods description
2.1. Process description
2.2. Life cycle assessment (LCA) and scenarios definition
3. Results and Discussion
4. Conclusions
Acknowledgments
References
323. A Systematic Comparison of Renewable Liquid Fuels for Power Generation: Towards a 100% Renewable Energy System
Abstract
Keywords
1. Introduction
2. Process Description
3. Results
4. Conclusions
References
324. Guiding innovations and Value-chain improvements using Life-cycle design for Sustainable Circular Economy
Abstract
Keywords
1. Introduction
2. Life Cycle Assessment (LCA) framework
3. SCE Design Framework
3.1. Node-alphabet representation of superstructure networks
3.2. Illustrative example
3.3. Constraints
3.4. Objectives and Pareto-front generation
3.5. SCE designs for the illustrative example
4. Sensitivity optimization for innovation discovery
5. Conclusions
6. Acknowledgments
References
325. Simultaneous Optimal Operation and Design of a Thermal Energy Storage Tank for District Heating Systems with Varying Energy Source
Abstract
Keywords
1. Introduction
2. Case Study
2.1. Historical Data
3. Methodology
4. Results
5. Conclusions and Future Work
Acknowledgements
References
326. A flexible energy storage dispatch strategy for day-ahead market trading
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Problem description & assumptions
2.2. Mathematical Formulation
3. Case study
4. Conclusions
References
327. Monetizing Flexibility in Day-Ahead and Continuous Intraday Electricity Markets
Abstract
Keywords
1. Introduction
2. Method for optimal bidding strategies in day-ahead and intraday markets
2.1. Deriving the option value for the continuous intraday market
2.2. Two-stage stochastic optimization of day-ahead and intraday market participation
3. Case study: market participation of a multi-energy system
4. Conclusions
Acknowledgements
References
328. Planetary boundaries analysis of Fischer-Tropsch Diesel for decarbonizing heavy-duty transport
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Life cycle assessment and planetary boundaries
3. Results
3.1. Relative impact to the Safe Operating Space
3.2. Impact breakdown
4. Conclusions
Acknowledgements
References
329. Renewable Power Systems Transition Planning using a Bottom-Up Multi-Scale Optimization Framework
Abstract
Keywords
1. Introduction
2. Multi-scale bottom-up energy transition optimization framework
3. Case study for New York State
4. Conclusion
References
330. Design and Operation of Urban Energy Network: Integration of Civic, Industrial, and Transportation Sectors
Abstract
1. Introduction
2. Optimization problem formulation
2.1. Decision variables
2.2. Constraints
2.3. Objective function
3. Case study description
4. Results and discussion
5. Conclusions
References
331. Sustainable Design of Hybrid Energy Systems for Net Zero Carbon Emission
Abstract
Keywords
1. Introduction
2. Problem Statement and Model Summary
3. Global Optimization Strategy
5. Conclusion
References
332. Prediction of Charge / Discharge Behavior of Tri-Electrode Zinc-air Flow Battery Using Linear Parameter Varying Model
Abstract
Keywords
1. Introduction
2. Description of tri-electrode ZAFB and experimental data
3. LPV modeling
4. Results and discussion
5. Conclusion
References
333. An optimized resource supply network for sustainable greenhouses: A circular economy ap
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Model Formulation
2.1. Illustrative example and available data
3. Results
4. Conclusion
5. References
334. Exergoeconomic optimization of a double effect evaporation process of coffee extract
Abstract
Keywords
1. Introduction
2. Materials and Methods
2.1. System Description
2.2. Exergoeconomic Optimization
3. Results and Discussion
4. Conclusions
References
335. Ecohydrological modeling and dynamic optimization for water management in an integrated aquatic and agricultural livestock system
Abstract
Keywords
1. Introduction
2. Methodology
3. Numerical results
4. Conclusions
References
336. Parametric Analysis of Ortho-to-Para Conversion in Hydrogen Liquefaction
Abstract
Keywords
1. Introduction
2. Ortho-to-Para Conversion
3. Research Methods
4. Further Discussion
5. Conclusions
Acknowledgment
References
337. Model agnostic framework for analyzing rainwater harvesting system behaviors
Abstract
Keywords
1. Introduction
2. Methods
2.1. System Modelling
2.2. K-means Clustering
2.3. PLS Model
2.4. Supplementing clustering results with PLS scores
3. Results and discussion
3.1. Clustering and the classification of response modes
3.2. PLS model and the identification of main system driving forces
3.3. Distinguishing rainfall properties between response modes
4. Conclusions
Acknowledgements
References
338. Global assessment and optimization of renewable energy and negative emission technologies
Abstract
Keywords
1. Introduction
2. Methodology
3. Results and Discussion
4. Conclusion
Acknowledgment
References
339. The Trade-Off between Spatial Resolution and Uncertainty in Energy System Modelling
Abstract
Keywords:
1. Introduction
2. Methodology
2.1. Novelty
2.2. Global Sensitivity Analysis
2.3. Case Study
3. Results and Discussion
4. Conclusions
References
340. Designing a Resilient Biorefinery System under Uncertain Agricultural Land Allocation
Abstract
Keywords:
1. Introduction
2. Problem formulation
3. Stochastic optimization
4. Case study details
5. Results and discussion
6. Conclusions
References
341. LCA modeling as a decision-tool for experimental design: the case of extraction of astaxanthin from crab waste
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Goal and scope
2.1.1. Production process: production of astaxanthin-oleoresin (AXT-oleoresin)
2.2. Life Cycle Inventory
3. Results & Discussion
4. Conclusions
References
342. Decomposition of Organic Compounds in Water from Oil Refineries
Abstract
Keywords:
1. Introduction
2. Proposed process for the treatment of water oil refineries
3. Methods
3.1. The removal of organic sulfur, organic nitrogen, and other organic compounds using hydrogen
3.2. The treatment of phenol through photocatalysis
4. Results and Discussion
4.1. The overall conversion ratio of the organic sulfur and organic nitrogen
4.2. The removal of phenol by photocatalysis
5. Conclusion
References
343. Energy Harvesting Wireless Sensors Using Magnetic Phase Transition
Abstract
Keywords:
1. Introduction
2. Energy harvesting using magnetic phase transition and sensors
3. Experimental procedure and set-up
4. Experimental results
5. Conclusion
Acknowledgement
References
344. Competitive Adsorption of Copper, Nickel, and Chromium Ions onto Amine Functionalized SBA-15
Abstract
Keywords
1. Introduction
2. Materials and methods
2.1. Materials
2.2. Synthesis of SBA-15
2.3. Preparation of amine functionalized SBA-15
2.4. Batch adsorption studies
3. Results and discussion
3.1. Effect of pH
3.2. Effect of initial metal concentration
3.3. Mathematical modeling
4. Conclusions
References
345. Use of Environmental Assessment and Techno Economic Analysis (TEA) to Evaluate the Impact and Feasibility of Coatings for Manufacturing Processes
Abstract
Keywords
1. Introduction
2. Goal and scope
3. Data collection and inventory
4. Cost and environmental assessment
4.1 Gas production
4.2 Target production
4.3 Electricity consumption
4.4 Labor, maintenance and annuities
4.5 Summary
5. Conclusions
6. References
346. Forecasting Operational Conditions: A case-study from dewatering of biomass at an industrial wastewater treatment plant
Abstract
Keywords
1. Introduction
2. Methods
2.1. Plant description
2.2. Data availability
2.4. Batch data-extraction algorithm
2.3. Partial autocorrelation matrix (PACM)
2.5. Predictive method
3. Results
3.1. Analysis of batch data
4.2. Assessment of process delays
4.3. Random forest
4.3.1. Model training
4.3.2. Model predictions
4.3.3. Discussion
4. Conclusion
5. Acknowledgement
6. References
347. Plant wide modelling of a full-scale industrial water treatment system
Abstract
Keywords
1. Introduction
2. Methods
2.1 Plant description and measuring campaign
2.3 Mass balancing and data reconciliation
2.4. Influent fractionation
2.5. Main mathematical models
3. Results
3.1. Reconciled mass balances
3.2. Influent fractionation
3.3. Computer simulations
3.3.1. Buffer tank (BT) + primary clarifier (PRIM)
3.3.2. Pre-acidification tank (PAT)
3.3.3. Anaerobic granular sludge reactor (AGSR)
3.3.4. Activated sludge reactor (ASR) + secondary clarifier (SEC) + flotation (FLOT)
3.3.5. Inactivation tank (IT) + dewatering unit (DEW)
4. Conclusion
5. References
348. A Systematic Framework for the Integration of Carbon Capture, Renewables and Energy Storage Systems for Sustainable Energy
Abstract
Keywords
1. Introduction
2. THESEUS Framework
3. Results and D iscussion
4. Conclusions
5. Acknowledgements
References
349. Integration of experimental study and computer-aided design: A case study in thermal energy storage
Abstract
Keywords:
1. Introduction
2. Material and Methodology
3. Case study in thermal energy storage
3.1. Experimentally validated computer-aided design
3.2. Seamless connection to system-level analysis utilizing experimental data
3.3. Research flow of integrating experimental study and system-level analysis
4. Conclusions
Acknowledgement
References
350. Design support toolbox for renewable-based regional energy systems
The concept, data integration, and simulator development
Abstract
Keywords
1. Introduction
2. Case studies of designing renewable-based regional energy systems
3. Requirement definition of the design support toolbox
3.1. Activity model
3.2. Data model for flow simulation
3.3. The function of design support toolbox
4. Development of modules in the toolbox
4.1. Data integration and visualization of resources and demands
4.2. Matching between resources and technologies
4.3. Simulation of the material and energy balances
4.4. Environmental and socio-economic evaluations
5. Conclusions
Acknowledgement
References
351. Circular Economy Integration into Carbon Accounting Framework for Comprehensive Sustainability Assessment
Abstract
Keywords:
1. Introduction
2. Circular Economy Actions Selection Framework
3. Case Study
3.1. Identify Hot Spots Through INCAM
3.2. Propose CE Actions and Priority Ranking
4. Conclusions
5. Acknowledgement
References
352. Design and analysis of fuel-assisted solid oxide electrolysis cell combined with biomass gasifier for hydrogen production
Abstract
Keywords:
1. Introduction
2. Models of Gasifier and Fuel-Assisted Solid Oxide Electrolysis Cell
2.1. Gasifier model
2.2. SOFEC model
3. Integrated System process description
4. Results and Discussions
4.1. Effect of equivalence ratio on the system
4.2. Effect of gasification temperature on the system
4.3. Effect of different gasifier operating conditions on system efficiency
5. Conclusions
6. Reference
353. Plasma-Based Pyrolysis of Municipal Solid Plastic Waste for a Robust WTE Process
ABSTRACT
Keywords
1. Introduction
2. Materials and Methods
2.1. Materials and chemicals
2.2. Waste characterization
2.2.1 Thermogravimetric analysis
2.2.2 Fourier Transform Infra-red spectroscopy (FTIR) analysis
2.2.3 Scanning electron microscope (SEM) analysis
2.3 Thermal source design
3. Results and Discussion
3.1 Waste characterization
3.1 Thermal source design
4. CONCLUSION
Acknowledgements
References
Contributed Papers: Pharma and Healthcare Systems
354. Hybrid Modeling Strategies of Continuous Pharmaceutical Manufacturing within Digital Twin Framework
Abstract
Keywords
1. Introduction
2. Hybrid Multi-zonal Compartmentalization
3. Hybrid Adaptive Modelling
4. Conclusions
Acknowledgement
References
355. Determination of probabilistic design spaces in the hybrid manufacture of an active pharmaceutical ingredient using PharmaPy
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Study
4. Results
5. Conclusions
6. Acknowledgement
References
356. Hybrid Modelling of CHO-MK Cell Cultivation in Monoclonal Antibody Production
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Experimental Data
2.2. Cultivation Model
3. Results and Discussion
3.1. Cell Cultivation Modelling Results
3.2. Insights from PCA loading trends
4. Conclusions
Acknowledgements
References
357. Multimodal modelling of uneven batch data
Abstract
Keywords
1. Introduction
2. Materials and Methods
2.1. SCREAM Model
2.2. Preprocessing
3. Case Study: Industrial Simulation of Penicillin Fermentation
4. Results and Discussions
5. Conclusions
References
358. Application of MHE-based NMPC on a Rotary Tablet Press under Plant-Model Mismatch
Abstract
Keywords
1. Introduction
2. Methodology
3. Case Study
3.1. Tablet press model
3 .2. Applying MHE to tablet press: Comparison of fix ed model and adaptive model
3 .3 . Ex perimental verification of MHE-NMPC
4. Conclusions
Acknowledgement
References
359. Gray-box modeling of pharmaceutical roller compaction process
Abstract
Keywords
1. Introduction
2. Materials and Methods
2.1. Physical testing of powder blends and ribbons
2.2. The modified rolling theory of granular solids and the gray-box model
3. Results
4. Conclusions
References
360. Multi-objective optimisation for early-stage pharmaceutical process development
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Selected KPIs and process configuration
2.2. Conceptual process model
2.2.1. Obtaining kinetic rate and gas solubility equations
2.2.2. Deriving flow reactor material balance equations of all reaction species
2.3. Formulating and solving the multi-objective reactor optimisation problems
3. Results and discussion
4. Conclusions
Acknowledgments
References
361. Quality by design and techno-economic modelling of RNA vaccine production for pandemic-response
Abstract
Keywords
1. Introduction
2. The AVV, mRNA and saRNA vaccine production platform technologies
3. Techno-economic modelling of the AVV, mRNA and saRNA platforms
4. Integration of QbD and techno-economic modeling with the RNA platform
5. Conclusions
Acknowledgements
References
362. Design of Value Function Trajectory for State of Control in Continuous Manufacturing System
Abstract
Keywords:
1. Introduction
2. Process control with a priori knowledge
3. Reactor Simulation Model
3.1. Constraints of the reaction system
3.2. Reactor configuration, size and flow condition
3.3. Typical trends of reactants and products
4. Design Space
4.1. Determination of value function
4.2. Comprehension of wide-range process attributes
4.3. Robust design space against process disturbances
5. Trajectory Tracking Control
5.1. Determination of value function trajectory
5.2. Proposed control
6. Conclusions
References
363. A Thermodynamic Approach for Simultaneous Solvent, Coformer, and Process Optimization of Continuous Cocrystallization Processes
Abstract
Keywords:
1. Introduction
2. Approach
2.1. Process Model Development
2.2. Cocrystal Solubility Advantage
2.3. Optimization
3. Results and Discussion
4. Conclusions
Acknowledgment
References
364. Optimizing the selection of drug-polymer-water formulations for spray-dried solid dispersions in pharmaceutical manufacturing
Abstract
Keywords
1. Introduction
2. Design Methodology
2.1. Problem definition
2.2. MINLP formulation for designing drug-polymer blends
3. Case study: optimal binary and ternary blends for the SSD of naproxen
3.1. Problem description
3.2. Results and discussion
4. Conclusions
Acknowledgments
Data statement
References
365. Integrated design of injectable manufacturing processes considering characteristics of process- and discrete-manufacturing systems
Abstract
Keywords
1. Introduction
2. Methodology
2.1. Process flowsheet model
2.2. Scheduling model
2.3. Evaluation mod
3. Case study
4. Conclusion
5. References
366. A bi-level decomposition approach for CAR-T cell therapies supply chain optimisation
Abstract
Keywords
1. Introduction
2. Materials and methods
3 . R esults and discussion
4. Conclusions
5. Acknowledgements
References
367. An agent-based model for cost-effectiveness analysis in the manufacture of allogeneic human induced pluripotent cells in Japan
Abstract
Keywords
1. Introduction
2. Methods
2.1. Effectiveness indicators of medical treatments
2.2. Model overview
2.3. Data pre-processing
2.4. Treatment model
2.5. DALY model
2.6. Cost model
3. Results and discussion
3.1. Data pre-processing
3.2. Case study: Investigation of treatment mode
4. Conclusions and outlook
Acknowledgements
References
368. Design and operation of healthcare facilities using batch-lines: the COVID-19 case in Qatar
Abstract
Keywords
1. Introduction
2. Problem statement
3. Mathematical modeling
4. Results
5. Conclusions
References
369. Application of PSE Methods on Monoclonal Antibody Productivity Improvement and Quality Control
Abstract
Keywords
1. Introduction
2. Flowsheet modeling and techno-economic analysis
2.1. Process Description
2.2. Simulation software and techno-economic analysis
2.3. Results
3. Predictive modeling of cell culture and protein glycosylation processes
3.1. Background
3.2. Equations
3.3. Results
4. Fed-batch bioreactor modeling and design space identification
4.1. Kriging and dynamic kriging
4.2. Feasibility analysis
4.3. Results
5. Conclusions
References
370. Image classification of experimental yields for cardiomyocyte cells differentiated from human induced pluripotent stem cells
Abstract
Keywords
1. Introduction
2. Methods and Materials
2.1. Experiments
2.2. Data Used to Build the Classifier Model
2.3. Feature Extraction
2.4. Classifier Model Construction and Evaluation
3. Results and Discussion
4. Conclusions
5. Acknowledgments
References
371. Prediction of API concentration using NIRS measured off-line and in-line instruments
Abstract
Keywords
1. Introduction
2. Experimental
3. Model development and validation
4. Results
5. Conclusions
References
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14th International Symposium on Process Systems Engineering

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