Molecular Modeling in Heavy Hydrocarbon Conversions

Molecular Modeling in Heavy Hydrocarbon Conversions introduces and develops a systematic molecule-based modeling approach with a system of chemical engineering software tools. This book 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. It discusses the Kinetic Modeler's Toolbox, a user-friendly software package that integrates molecule-based kinetic modeling. This text includes examples that apply this approach to the development of kinetic models for complex process chemistries, such as heavy naphtha reforming and gas oil hydroprocessing.

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.

IntroductionMotivation Background Modeling Approaches Molecule-based Kinetic Modeling Strategy The Premise PART I METHODSMolecular Structure and Composition Modeling of Complex FeedstocksIntroduction Analytical Characterization of Complex Feedstocks Molecular Structure Modeling: A Stochastic ApproachA Case Study: Light Gas Oil Discussions And SummaryAutomated Reaction Network Construction of Complex Process ChemistriesIntroduction Reaction Network Building and Control TechniquesProperties of Reaction NetworksSummary and ConclusionsOrganizing Kinetic Model ParametersIntroduction Rate Laws For Complex Reaction NetworksOverview of Linear Free Energy Relationships Representative Results and Summary of Lfers for Catalytic Hydrocracking Summary and ConclusionsMatching the Equation Solver to the Kinetic Model Type Introduction Mathematical BackgroundExperimentsResults and Discussion.Summary and ConclusionsIntegration of Detailed Kinetic Modeling Tools and Model Delivery Technology Introduction Integration of Detailed Kinetic Modeling ToolsKMT Development and Model DeliverySummaryPART II APPLICATIONSMolecule-Based Kinetic Modeling of Naphtha Reforming IntroductionModeling Approach Model DevelopmentAutomated Model Building The Model For C14 Naphtha Reforming Model Validation Summary and ConclusionsMechanistic Kinetic Modeling of Heavy Paraffin Hydrocracking Introduction Mechanistic Modeling Approach Model Development.Model Results and Validation Extension to C80 Model Summary and ConclusionsMolecule-Based Kinetic Modeling of Naphtha Hydrotreating Introduction Modeling ApproachModel DevelopmentResults and DiscussionSummary and ConclusionsAutomated Kinetic Modeling of Gas Oil Hydroprocessing Introduction Modeling Approach Model DevelopmentResults and DiscussionSummary and ConclusionsMolecular Modeling of Fluid Catalytic CrackingIntroductionModel Pruning Strategies For Mechanistic ModelingKineticsModel Diagnostics and ResultsMechanistic Model Learning as a Basis for Pathways Level ModelingPathways ModelingSummary and ConclusionsAutomated Kinetic Modeling of Naphtha PyrolysisIntroductionCurrent Approach to Model BuildingPyrolysis Model DevelopmentReaction Network DiagnosticsParameter EstimationSummary And ConclusionsSummary and Conclusions

Michael T. Klein, Gang Hou, Ralph Bertolacini, Linda J. Broadbelt, Ankush Kumar