Cover
Modeling of Chemical Process Systems
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atl_0005622155_
An introduction to modeling of chemical process systems
What is a model and modeling?
Historical perspective of simulation, systems engineering, and process systems modeling
Theoretical development
Computer software
Human-machine interface
Classification of models
Use of mechanism
Scales of models
Multiscale modeling
Modeling applications in processes
Research and development of new product
Design and commissioning of process systems
Operator training
Operations and debottlenecking
Abnormal situation management
Scope of the book
References
Preface
Model equations and modeling methodology
Process model and model equations
Model equations
Conservation equations
Constitutive equations
Systematic method for building process models
Systems thinking
Steps for mechanistic model building
Case study: PTA reactor model
Summary
References
Density functional theory (DFT) models for the desulfurization and extraction of sulfur compounds from fuel oi ...
Introduction
Global hardness and global softness
Electronegativity
Chemical potential
Electrophilicity index
Dipole moment
Results and discussion
Effect of the alkyl group chain lengths of the N-alkylpyridium and N-carboxyalkylpyridinium cations on the quantum c ...
Effect of alkyl group chain lengths on the quantum chemical properties of the N-alkylpyridium ILs
Effect of the five anions on the quantum chemical properties of the N-alkylpyridium ILs
Effect of the alkyl group chain lengths on the quantum chemical properties of the N-carboxyalkylpyridinium-based ILs
Molecular electrostatic potential results
Interaction energies and thermodynamic calculations for the interactions with DBT and the ILs
N-Alkylpyridinium ILs with HSO4- anions
N-Alkylpyridinium ILs with H2PO4- and Ac- anions
N-Alkylpyridinium ILs with TFA- and BF4- anions
N-Carboxyalkylpyridinium ILs with HSO4- anions
N-Carboxyalkylpyridinium ILs with H2PO4- and Ac- anions
N-Carboxyalkylpyridinium ILs with TFA- and BF4- anions
Conclusion and perspective for future developments
Summary
Acknowledgments
References
Molecular dynamics simulation in energy and chemical systems
Introduction
Fundamentals of MD technique
Emerge of MD technique
Architecture of MD technique
Theoretical frameworks of MD technique
Atomic interactions and forces
Periodic boundary conditions
Numerical integration algorithms
Statistical ensembles
Property calculation
Algorithms and simulation packages for MD technique
Advantages and disadvantages of the MD technique
Applications/case studies of MD
Theoretical and practical challenges in MD implementation
Current status and future prospects of MD technique
References
Single-event kinetic modeling of catalytic dewaxing on commercial Pt/ZSM-5
Introduction
Reactor modeling
Shape-selectivity effects
Reaction mechanism
Reaction network generation
Single-event kinetic modeling
Posteriori lumping
Net rate of formation
Reactor model
Physical properties estimation
Results and discussion
Parameter estimation
Effect of temperature
Effect of pressure
Effect of H2/HC ratio
Effect of the liquid hourly space velocity (LHSV)
Effects of feed carbon number
Effect of shape selectivity
Conclusions
References
Modeling and simulation of batch and continuous crystallization processes
Introduction to solution crystallization
Supersaturation and metastable limit
Solubility
Supersaturation
Metastable zone and metastable limit
Kinetics of crystallization in supersaturation
Nucleation kinetics
Kinetics of crystal growth
Crystal size distribution and population balance equations
Crystal size distribution
The population balance equation
Modeling of batch and continuous crystallization processes
Batch crystallization
Modeling of a batch crystallization process
The population balance
The mass balance of solute
Case study I: Seeded batch crystallization of (R)-mandelic acid in the presence opposite enantiomer
Continuous crystallization
Modeling of an MSMPR crystallizer
The population balance
The mass balance of solute
Case study II: The MSMPR crystallization of ciprofloxacin from crude APIs
Summary
References
Fuel processing systems
The need for fuel processing units
Fundamentals of fuel processing
Steam reforming
Dry reforming
Partial oxidation
Water gas shift reaction
Autothermal reforming
Recent developments in the reforming of common fuels
Reforming of hydrocarbons
Alcohol reforming
Electrochemical H2 production
PEM electrolyzer
Solid oxide electrolyzer
Overpotential loses
Kinetic models for reforming
Methane reforming
Methanol reforming
Ethanol reforming
Reactor choice
Reactor designs based on packed bed
Reactor design based on monoliths
Membrane reactors
Reactor modeling
Zero-dimensional stirred tank model
One-dimensional plug flow model
One-dimensional packed-bed model
Sizing of reactor for applications in fuel cells
Summary
References
Crude to chemicals: The conventional FCC unit still relevant
History of direct crude processing
Update on crude to chemical processing
FCC unit: Conventional FCC units with high severity to maximize propylene and ethylene
Riser and regenerator mathematical model
FCC catalysts and role in crude to chemical technology
The future of crude to chemicals
References
Hybrid model for a diesel cloud point soft-sensor
Introduction
Terminology related to hybrid model
Case study: A hybrid model for diesel cloud point prediction
Cloud point soft-sensor-Mechanistic model
TBP module
Hydro-dewaxing (HDW) reactor model
Hydrodesulfurization reactor model
Kinetic parameters and rate equations
Model equations
Solid-liquid equilibrium thermodynamic model
Surrogate model
Design of computer experiments
Nonlinearity tracking and exploration capability
Results
Industrial case study
On-line cloud point soft-sensor application
Summary
Appendix
References
Large-scale process models using deep learning
Large-scale system modeling challenges
Motivation for deep learning algorithms
Deep learning methods
Supervised deep learning
Unsupervised deep learning
Exploring key deep learning methods in large-scale process modeling
Recurrent neural network
Long short-term memory network
Autoencoder
Variational autoencoder
Application to modeling chemical and biological systems
Summary
References
atl_0005622154_