Molecular Modeling in Heavy Hydrocarbon Conversions

In the past two decades, new modeling efforts have gradually incorporated more molecular and structural detail in response to environmental and technical interests. Molecular Modeling in Heavy Hydrocarbon Conversions introduces a systematic molecule-based modeling approach with a system of chemical engineering software tools that can automate the entire model building, solution, and optimization process.





Part I shows how chemical engineering principles provide a rigorous framework for the building, solution, and optimization of detailed kinetic models for delivery to process chemists and engineers.
Part II presents illustrative examples that apply this approach to the development of kinetic models for complex process chemistries, such as heavy naphtha reforming and gas oil hydroprocessing. Molecular Modeling in Heavy Hydrocarbon Conversions develops the key tools and best possible approaches that process chemists and engineers can use to focus on the process chemistry and reaction kinetics for performing work that is repetitive or prone to human-error accurately and quickly.

Table of Contents
Chapter 1 Introduction
1.1 Motivation
1.2 Background.
1.3 Modeling Approaches
1.4 Molecule-based Kinetic Modeling Strategy.
1.5 The Premise
References
Part I Methods
Chapter 2 Molecular Structure and Composition Modeling of Complex Feedstocks
2.1 Introduction.
2.2 Analytical Characterization of Complex Feedstocks.
2.3 Molecular Structure Modeling: A Stochastic Approach
2.3.1 Probability Density Functions (PDFs)
2.3.1.1 PDFs Used to Describe Complex Mixtures
2.3.1.2 Molecular Structural Attributes
2.3.1.3 Appropriate PDF Forms
2.3.1.4 Discretization, Truncation, and Renormalization
2.3.1.5 Conditional Probability
2.3.2 Monte Carlo Construction
2.3.2.1 Monte Carlo Sampling Protocol
2.3.2.2 Optimal Representation of a Complex Feedstock
2.3.2.3 Sample Size
2.3.3 Quadrature Molecular Sampling
2.3.3.1 Quadrature Sampling Protocol
2.3.3.2 Fine-Tuning the Quadrature Molecular Representation
2.4 A Case Study: Light Gas Oil
2.5 Discussions and Summary
References
Chapter 3 Automated Reaction Network Construction of Complex
Process Chemistries
3.1 Introduction
3.2 Reaction Network Building and Control Techniques
3.2.1 Preprocessing Methodologies.
3.2.1.1 Rule-Based Model Building
3.2.1.2 Seeding and Deseeding
3.2.2 In Situ Processing Methodologies
3.2.2.1 Generalized Isomorphism Algorithm as an On-the-Fly Lumping Tool
3.2.2.2 Stochastic Rules for Reaction Site Sampling
3.2.3 Postprocessing Methodologies
3.2.3.1 Generalized Isomorphism-Based Late Lumping.
3.2.3.2 Species-Based and Reaction-Based Model Reduction
3.3 Properties of Reaction Networks
3.3.1 Properties of Species
3.3.2 Properties of Reactions
3.3.3 Characterization of the Reaction Network
3.4 Summary and Conclusions.
References
Chapter 4 Organizing Kinetic Model Parameters
4.1 Introduction.
4.2 Rate Laws For Complex Reaction Networks
4.2.1 Kinetic Rate Laws at the Pathways Level
4.2.2 Kinetic Rate Laws at the Mechanistic Level.
4.3 Overview of Linear Free Energy Relationships.
4.4 Representative Results and Summary of LFERS for Catalytic Hydrocracking
4.5 Summary and Conclusions
References
Chapter 5 Matching the Equation Solver to the Kinetic Model Type
5.1 Introduction
5.2 Mathematical Background
5.2.1 Underlying Numerical Methods for Solving DKM Systems
5.2.2 Stiffness in DKM Systems.
5.2.3 Sparseness in DKM Systems
5.3 Experiments
5.3.1 Candidate DKMs
5.3.2 Candidate Solvers
5.3.3 Experiment Setup
5.4 Results and Discussion
5.4.1 Pathways-Level DKM
5.4.2 Mechanistic-Level DKM
5.4.3 DKM Model Solving Guidelines
5.5 Summary and Conclusions
References
Chapter 6 Integration of Detailed Kinetic Modeling Tools and Model Delivery Technology
6.1 Introduction.
6.2 Integration of Detailed Kinetic Modeling Tools
6.2.1 The Integrated Kinetic Modeler’s Toolbox
6.2.1.1 The Molecule Generator (MolGen).
6.2.1.2 The Reaction Network Generator (NetGen)
6.2.1.3 The Model Equation Generator (EqnGen)
6.2.1.4 The Model Solution Generator (SolGen)
6.2.2 Parameter Optimization and Property Estimation
6.2.2.1 The Parameter Optimization (ParOpt) Framework
6.2.2.2 Optimization Algorithms
6.2.2.3 The Objective Function
6.2.2.4 Property Estimation of Mixtures
6.2.2.5 The End-to-End Optimization Strategy
6.2.3 Conclusions
6.3 KMT Development and Model Delivery
6.3.1 Platform and Porting
6.3.2 Data Issues
6.3.3 User Interface Issues
6.3.4 Documentation Issues
6.3.5 Lessons Learned
6.4 Summary
References
Part II Applications
Chapter 7 Molecule-Based Kinetic Modeling of Naphtha Reforming.
7.1 Introduction.
7.2 Modeling Approach
7.3 Model Development
7.3.1 Dehydrocyclization
7.3.2 Hydrocracking
7.3.3 Hydrogenolysis
7.3.4 Paraffin Isomerization
7.3.5 Naphthene Isomerization
7.3.6 Dehydrogenation (Aromatization)
7.3.7 Dealkylation
7.3.8 Coking
7.4 Automated Model Building
7.5 The Model For C14 Naphtha Reforming
7.6 Model Validation
7.7 Summary and Conclusions
References
Chapter 8 Mechanistic Kinetic Modeling of Heavy Paraffin Hydrocracking
8.1 Introduction
8.2 Mechanistic Modeling Approach
8.3 Model Development
8.3.1 Reaction Mechanism
8.3.2 Reaction Families
8.3.2.1 Dehydrogenation and Hydrogenation
8.3.2.2 Protonation and Deprotonation
8.3.2.3 Hydride and Methyl Shift
8.3.2.4 PCP Isomerization
8.3.2.5 β-Scission
8.3.2.6 Inhibition Reaction
8.3.3 Automated Model Building
8.3.4 Kinetics: Quantitative Structure Reactivity Correlations
8.3.5 The C16 Paraffin Hydrocracking Model at the Mechanistic Level
8.4 Model Results and Validation
8.5 Extension to C80 Model
8.6 Summary and Conclusions
References
Chapter 9 Molecule-Based Kinetic Modeling of Naphtha Hydrotreating
9.1 Introduction
9.2 Modeling Approach
9.3 Model Development
9.3.1 Reaction Families
9.3.1.1 Reactions of Sulfur Compounds: Desulfurization and Saturation
9.3.1.2 Olefin Hydrogenation
9.3.1.3 Aromatic Saturation
9.3.1.4 Denitrogenation
9.3.2 Reaction Kinetics
9.3.3 Automated Model Building
9.4 Results and Discussion
9.4.1 The Naphtha Hydrotreating Model
9.4.2 Model Optimization and Validation
9.5 Summary and Conclusions
References
Chapter 10 Automated Kinetic Modeling of Gas Oil Hydroprocessing
10.1 Introduction
10.2 Modeling Approach
10.3 Model Development
10.3.1 Feedstock Characterization and Construction
10.3.2 Reaction Families
10.3.2.1 Reactions of Aromatics and Hydroaromatics
10.3.2.2 Reactions of Naphthenes
10.3.2.3 Reactions of Paraffins
10.3.2.4 Reactions of Olefins
10.3.2.5 Reactions of Sulfur Compounds
10.3.2.6 Reactions of Nitrogen Compounds
10.3.3 Kinetics: LHHW Formalism
10.3.4 Automated Model Building
10.4 Results and Discussion
10.5 Summary and Conclusions
References
Chapter 11 Molecular Modeling of Fluid Catalytic Cracking
11.1 Introduction
11.2 Model Pruning Strategies For Mechanistic Modeling
11.2.1 Mechanistic Modeling
11.2.2 Rules Based Reaction Modeling
11.2.2.1 Reaction Rules
11.2.2.2 Stochastic Rules
11.3 Kinetics
11.3.1 Intrinsic Kinetics
11.3.2 Coking Kinetics
11.4 Model Diagnostics and Results
11.5 Mechanistic Model Learning as a Basis for Pathways Level Modeling
11.6 Pathways Modeling
11.6.1 Pathways Model Development Approach
11.6.2 Pathways Level Reaction Rules.
11.6.2.1 Cracking Reactions
11.6.2.2 Isomerization Reactions
11.6.2.3 Methyl Shift Reactions
11.6.2.4 Hydrogenation and Dehydrogenation
Reactions
11.6.2.5 Aromatization
11.6.3 Coking Kinetics
11.6.4 Gas Oil Composition
11.6.5 Model Diagnostics and Results
11.7 Summary and Conclusions
References
Chapter 12 Automated Kinetic Modeling of Naphtha Pyrolysis
12.1 Introduction
12.2 Current Approach to Model Building
12.3 Pyrolysis Model Development
12.3.1 Reaction Rules
12.3.1.1 Initiation
12.3.1.2 Hydrogen Abstraction
12.3.1.3 β-Scission
12.3.1.4 Radical Addition to Olefins
12.3.1.5 Diels–Alder Reaction
12.3.1.6 Termination Reactions
12.4 Contribution of Reaction Families
12.5 Reaction Network Diagnostics
12.6 Parameter Estimation
12.7 Summary and Conclusions
References
Chapter 13 Summary and Conclusions
13.1 Summary
13.1.1 Molecular Structure and Composition Modeling of Complex Feedstocks
13.1.2 Automated Reaction Network Building of Complex Process Chemistries
13.1.3 Kinetic Rate Organization and Evaluation of Complex Process Chemistries
13.1.4 Model Solving Techniques for Detailed Kinetic Models
13.1.5 Integration of Detailed Kinetic Modeling Tools and Model Delivery Technology
13.1.6 Molecule-Based Kinetic Modeling of Naphtha Reforming
13.1.7 Mechanistic Kinetic Modeling of Heavy Paraffin Hydrocracking
13.1.8 Molecule-Based Kinetic Modeling of Naphtha Hydrotreating
13.1.9 Automated Kinetic Modeling of Gas Oil Hydroprocessing
13.1.10 Molecular Modeling of Fluid Catalytic Cracking
13.1.11 Automated Kinetic Modeling of Naphtha Pyrolysis
13.2 Conclusions