Download or read book Enabling Automatic Generation of Accurate Kinetic Models for Complicated Chemical Systems written by Kehang Han and published by . This book was released on 2018 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have seen much progress in predictive kinetic modeling. Reaction mechanisms have shown increased predictive capability, providing key insights into chemical transformations under conditions of interest. Coupled and integrated in multiscale-multiphysics models, reaction mechanisms help elucidate physical phenomena that are driven by chemical kinetics and are recognized as a necessary tool for chemical selection, reactor design and process optimization. These past kinetic modeling achievements have opened new opportunities for novel scientific applications in chemical kinetics community and encouraged kinetic modelers to study even more complex chemical systems. As one can expect, the system complexity significantly increases modeling cost in both reaction mechanism construction and simulation. Over the years we have seen formulation of various lumping strategies. Despite simplicity, the lumping strategy introduces an intrinsic error where the lumps contain molecules with very different reactivities. Frequently, oversimplified models using the kinetic parameters fitted from a very limited set of pilot experiments, resulting in poor accuracy in extrapolation. This thesis focuses on automated detailed kinetic modeling strategy using Reaction Mechanism Generator (RMG). RMG-generated models more faithfully represent the chemistry so they have superior extrapolation potential. But as system complexity increases, several computational limitations prevent RMG from converging. This thesis has made several contributions: reducing memory usage, boosting algorithm scalability, improving thermochemistry estimation accuracy, which eventually expand RMG's modeling capability toward large complex systems. These contributions are available to the kinetics community through the RMG software package. To demonstrate the improved modeling capability of RMG, the thesis also includes a large chemical application: heavy oil thermal decomposition under geological conditions via a C18 model compound, phenyldodecane. As an extension of RMG, the thesis also explores a promising alternative to detailed kinetic modeling when dealing with extremely large chemical systems: fragment-based kinetic modeling, which generates a reaction network in fragment space rather than molecule space. The thesis shows via a case study that the new method creates a much smaller reaction network but with similar prediction accuracy on feedstock conversion and products' molecular weight distribution compared to its counterpart model generated by RMG.

Download or read book Automatic Generation of Detailed Kinetic Models for Complex Chemical Systems written by Fariba Seyedzadeh Khanshan and published by . This book was released on 2016 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detailed chemical kinetic mechanisms represent molecular interactions that occur when chemical bonds are broken and reformed into new chemical compounds. Many natural and industrial processes such as combustion of hydrocarbons, biomass conversion into re- newable fuels, and synthesis of halogenated-hydrocarbon through halogenation reactions, include reaction network with hundred of species and thousands of reactions. Recently, the potential of such processes is leading to rapid industrial expansion and facing some technical drawbacks. Among various tools, detailed kinetic modeling is a reliable way to improve the scientific understanding of such systems and therefore optimize process conditions for desired production plans. Detailed chemical kinetic modeling is sensitive to the system chemistry, and sometimes too complex to model by hand. For example, utilizing predictive theoretical models by hand for biomass thermal conversion, which in- clude a wide variety of heavy cyclic oxygenated molecules, alcohols, aldehydes, ketones, ethers, esters, etc., is tedious. It is preferable to teach our chemistry knowledge to computers, and generate detailed chemical models automatically. To generate comprehensive detailed models, an extensive set of reaction classes, which would define how species can react with each other, should be implemented in mechanism generators. In this thesis, Reaction Mechanism Genera- tor (RMG), an open-source software, has been used to build detailed kinetic models for complex chemical systems. This thesis presents several significant contributions in the area of predictive automatic kinetic mechanism generation for biofuels thermal conversion and reactions of many chlo- rinated hydrocarbons. The first section of this thesis describes significant contributions in detailed kinetic modeling of bio-oil gasification for syngas production using RMG. The major challenge in modeling bio-oil gasification is the presence of a wide range of cyclic oxygenated species and several progress has been made in RMG to improve the automated chemical modeling of this process. RMG-built models were evaluated by comparison to available published data and to improve the understanding of such detailed models, dif- ferent types of analysis such as sensitivity analysis were performed. The second section of this thesis presents a theoretical study of the gas-phase unimolec- ular thermal decomposition of heterocyclic compounds via single step exo and endo ring opening reaction classes. Quantum chemical calculations were performed for a smaller set of reactants belonging to the endo and exo reaction classes and data were used to inspect the 'rate calculation rules' method. To study the e↵ect of the direct ring open- ing reactions in the automated detailed kinetic model generation, the bio-oil gasification mechanism, from Chapter 1, was updated after updating RMGs kinetic database with these new single step ring opening reaction classes and associated rate rules. The third section of this thesis provides significant contributions toward facilitating the automatic generation of predictive detailed kinetic models for 1,1,2,3- tetrachloropropene (1230xa) production and other hydrocarbon chlorination processes. In order to enable RMG to model chlorinated hydrocarbon conversions, the chlorine (Cl) chemistry has been added into the the Python version of the software. A model has been generated in RMG for 1230xa production with known associated thermodynamic and kinetic parameters. For model evaluation, reaction flux analysis and sensitivity analysis were performed to reveal the important reaction channels in the RMG-built model and several improvements to thermodynamic estimates were discussed. The ability to automatically generate these models for such complex chemical systems demonstrates the predictive capability of detailed chemical modeling. The impact of such models significantly improves the scientific understanding of two industrial chemical processes, bio-oil gasification and chlorination.

Download or read book Automated Reaction Mechanism Generation written by Gregory Russell Magoon and published by . This book was released on 2012 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemical kinetic modeling plays an important role in the study of reactive chemical systems. Thus, an automated means of constructing chemical kinetic models forms a useful tool in the engineering and science surrounding such systems. This document describes work to further develop one such tool, known as RMG (Reaction Mechanism Generator). Focus is placed on improving the accuracy of parameter estimation in the mechanism generation process and expanding the scope of applicability of the tool. In particular, effort has targeted the generation and use of explicit three-dimensional molecular structures for chemical species considered during reaction mechanism generation. This work has resulted in the generation of a software system integrated with RMG that can automatically generate and use such structures with quantum chemistry or force field codes to obtain more reliable thermochemistry estimates for cyclic structures without human intervention. Ultimately, the result of these updates is improved usefulness and reliability of the software system as a predictive tool. An application of the tool to the high temperature oxidation of JP-10, a jet fuel often used in military applications, is described. Using the newly refined RMG system, a detailed chemical kinetic model was constructed for this system. The resulting model represents a significant improvement upon existing work for JP- 10 oxidation by capturing detailed chemistry for this system. Simulations with this model have been found to produce results for ignition delay and product distribution that compare favorably with experimental results. The successful application of the refined RMG software system to this system demonstrates the practical utility of these updates.

Download or read book Automatic Reaction Mechanism Generation written by Connie Wu Gao and published by . This book was released on 2016 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growing awareness of climate change and the risks associated with our society's dependence on fossil fuels has motivated global initiatives to develop economically viable, renewable energy sources. However, the transportation sector remains a major hurdle. Although electric vehicles are becoming more mainstream, the transportation sector is expected to continue relying heavily on combustion engines, particularly in the freight and airline industries. Therefore, research efforts to develop cleaner combustion must continue. This includes the development of more efficient combustion engines, identification of compatible alternative fuels, and the streamlining of existing petroleum resources. These dynamic systems have complex chemistry and are often difficult and expensive to probe experimentally, making detailed chemical kinetic modeling an attractive option for simulating and predicting macroscopic observables such as ignition delay or CO2 concentrations. This thesis presents several methods and applications towards high fidelity predictive modeling using Reaction Mechanism Generator (RMG), an open source software package which automatically constructs kinetic mechanisms. Several sources contribute to model error during automatic mechanism generation, including incomplete or incorrect handling of chemistry, poor estimation of thermodynamic and kinetics parameters, and uncertainty propagation. First, an overview of RMG is presented along with algorithmic changes for handling incomplete or incorrect chemistry. Completeness of chemistry is often limited by CPU speed and memory in the combinational problem of generating reactions for large molecules. A method for filtering reactions is presented for efficiently and accurately building models for larger systems. An extensible species representation was also implemented based on chemical graph theory, allowing chemistry to be extended to lone pairs, charges, and variable valencies. Several chemistries are explored in this thesis through modeling three combustion related processes. Ketone and cyclic ether chemistry are explored in the study of diisoproyl ketone and cineole, biofuel candidates produced by fungi in the decomposition of cellulosic biomass. Detailed kinetic modeling in conjunction with engine experiments and metabolic engineering form a collaborative feedback loop that efficiently screens biofuel candidates for use in novel engine technologies. Next, the challenge of modeling constrained cyclic geometries is tackled in generating a combustion model of JP-10, a synthetic jet fuel used in propulsion technologies. The model is validated against experimental and literature data and succeeds in capturing key product distributions, including aromatic compounds, which are precursors to polyaromatic hydrocarbons (PAHs) and soot. Finally, oil-to-gas cracking processes under geological conditions are studied through modeling the low temperature pyrolysis of the heavy oil analog phenyldodecane in the presence of diethyldisulfide. This system is used to gather mechanistic insight on the observation that sulfur-rich kerogens have accelerated oil-to-gas decomposition, a topic relevant to petroleum reservoir modeling. The model shows that free radical timescales matter in low temperature systems where alkylaromatics are relatively stable. Local and global uncertainty propagation methods are used to analyze error in automatically generated kinetic models. A framework for local uncertainty analysis was implemented using Cantera as a backend. Global uncertainty analysis was implemented using adaptive Smolyak pscudospcctral approximations to efficiently compute and construct polynomial chaos expansions (PCE) to approximate the dependence of outputs on a subset of uncertain inputs. Both local and global methods provide similar qualitative insights towards identifying the most influential input parameters in a model. The analysis shows that correlated uncertainties based on kinetics rate rules and group additivity estimates of thermochemistry drastically reduce a model's degrees of freedom and can have a large impact on model outputs. These results highlight the necessity of uncertainty analysis in the mechanism generation workflow. This thesis demonstrates that predictive chemical kinetics can aid in the mechanistic understanding of complex chemical processes and contributes new methods for refining and building high fidelity models in the automatic mechanism generation workflow. These contributions are available to the kinetics community through the RMG software package.

Download or read book Predictive Chemical Kinetics written by Joshua William Allen and published by . This book was released on 2013 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of petroleum-based fuels for transportation accounted for more than 25% of the total energy consumed in 2012, both in the United States and throughout the world. The finite nature of world oil reserves and the effects of burning petroleum-based fuels on the world's climate have motivated efforts to develop alternative, renewable fuels. A major category of alternative fuels is biofuels, which potentially include a wide variety of hydrocarbons, alcohols, aldehydes, ketones, ethers, esters, etc. To select the best species for use as fuel, we need to know if it burns cleanly, controllably, and efficiently. This is especially important when considering novel engine technologies, which are often very sensitive to fuel chemistry. The large number of candidate fuels and the high expense of experimental engine tests motivates the use of predictive theoretical methods to help quickly identify the most promising candidates. This thesis presents several contributions in the areas of predictive chemical kinetics and automatic mechanism generation, particularly in the area of reaction kinetics. First, the accuracy of several methods of automatic, high-throughput estimation of reaction rates are evaluated by comparison to a test set obtained from the NIST Chemical Kinetics Database. The methods considered, including the classic Evans-Polanyi correlation, the "rate rules" method currently used in the RMG software, and a new method based on group contribution theory, are shown to not yet obtain the order-of-magnitude accuracy desired for automatic mechanism generation. Second, a method of very accurate computation of bimolecular reaction rates using ring polymer molecular dynamics (RPMD) is presented. RPMD rate theory enables the incorporation of quantum effects (zero-point energy and tunneling) in reaction kinetics using classical molecular dynamics trajectories in an extended phase space. A general-purpose software package named RPMD-rate was developed for conducting such calculations, and the accuracy of this method was demonstrated by investigating the kinetics and kinetic isotope effect of the reaction OH + CH4 --> CH3 + H2O. Third, a general framework for incorporating pressure dependence in thermal unimolecular reactions, which require an inert third body to provide or remove the energy needed for reaction via bimolecular collisions, was developed. Within this framework, several methods of reducing the full, master equation-based model to a set of phenomenological rate coefficients k(T, P) are compared using the chemically-activated reaction of acetyl radical with oxygen as a case study, and recommendations are made as to when each method should be used. This also resulted in a general-purpose code for calculating pressure-dependent kinetics, which was applied to developing an ab initio model of the reaction of the Criegee biradical CH 200 with small carbonyls that reproduces recent experimental results. Finally, the ideas and techniques of estimating reaction kinetics are brought together for the development of a detailed kinetics model of the oxidation of diisopropyl ketone (DIPK), a candidate biofuel representative of species produced from cellulosic biomass conversion using endophytic fungi. The model is evaluated against three experiments covering a range of temperatures, pressures, and oxygen concentrations to show its strengths and weaknesses. Our ability to automatically generate this model and systematically improve its parameters without fitting to the experimental results demonstrates the validity and usefulness of the predictive chemical kinetics paradigm. These contributions are available as part of the Reaction Mechanism Generator (RMG) software package.

Download or read book Modeling of Chemical Reactions written by R.W. Carr and published by Elsevier. This book was released on 2007-09-04 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Chemical Reactions covers detailed chemical kinetics models for chemical reactions. Including a comprehensive treatment of pressure dependent reactions, which are frequently not incorporated into detailed chemical kinetic models, and the use of modern computational quantum chemistry, which has recently become an extraordinarily useful component of the reaction kinetics toolkit. It is intended both for those who need to model complex chemical reaction processes but have little background in the area, and those who are already have experience and would benefit from having a wide range of useful material gathered in one volume. The range of subject matter is wider than that found in many previous treatments of this subject. The technical level of the material is also quite wide, so that non-experts can gain a grasp of fundamentals, and experts also can find the book useful. A solid introduction to kinetics Material on computational quantum chemistry, an important new area for kinetics Contains a chapter on construction of mechanisms, an approach only found in this book

Download or read book Modeling Chemical Systems using Cellular Automata written by Lemont B. Kier and published by Springer Science & Business Media. This book was released on 2006-02-23 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Chemical Systems using Cellular Automata provides a practical introduction to an exciting modeling paradigm for complex systems. The book first discusses the nature of scientific inquiry using models and simulations, and then describes the nature of cellular automata models. It then gives detailed descriptions, with examples and exercises, of how cellular automata models can be used in the study of a wide variety chemical, physical, and biochemical phenomena. Topics covered include models of water itself, solution phenomena, solution interactions with stationary systems, first- and second-order kinetic phenomena, enzyme kinetics, vapor-liquid equilibrium, and atomic and molecular excited-state kinetics. The student experiences these systems through hands-on examples and guided studies. This book is the first of its kind: a textbook and a laboratory manual about cellular automata modeling of common systems in chemistry. The book is designed to be used as a text in undergraduate courses dealing with complex systems and/or as a computational supplement to laboratory courses taught at the undergraduate level. The book includes: - Compact descriptions of a large variety of physical and chemical phenomena - Illustrative examples of simulations, with exercises for further study - An instructor's manual for use of the program The book will be of great value in undergraduate courses in chemistry, physics, biology, applied mathematics, and bioinformatics, and as a supplement for laboratory courses in introductory chemistry, organic chemistry, physical chemistry, medicinal chemistry, chemical engineering and other courses dealing with statistical and dynamic systems. It allows the exploration of a wide range of dynamic phenomena, many of which are not normally accessible within conventional laboratory settings due to limitations of time, cost, and experimental equipment. The book is both a textbook on applied Cellular Automata and a lab manual for chemistry (physics, engineering) courses with lab activity. It would supplement other lab work and be an additonal book the students would use in the course. The authors have assessed the emerging need for this kind of activity in science labs because of the cost of the practical activitites and the frequent failure of some exercises leading to lost didactic value of some experiments. This book is pioneering an alternative that will grow in use. There are no course directors who would use Cellular Automata exclusively. The authors see an emerging interest in this kind of work in courses that contain lab exercises. One such course is the graduate course that Lemont Kier gives in Life Sciences about complexity. He uses many examples and studies from Cellular Automata in the latter part of this course.

Download or read book Stochastic Chemical Kinetics written by Péter Érdi and published by Springer. This book was released on 2014-05-06 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

Download or read book Progress Towards Automatic Chemical Kinetic Model Development written by Mark Barbet and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of a kinetic model that is predictive of certain quantities of interest (ignition delay times, flame speeds, etc) can broadly be broken into four distinct stages: 1) initial ``crude'' model generation, 2) experimental design, 3) experiments and ab-initio theory calculations, and 4) kinetic model optimization. Advances in data-enabled science and ever-increasing computing power have offered pathways towards eventually automating this process. This work aims to introduce a collection of tools and building blocks that will assist in the overall aim of automatic kinetic model development, and in doing so fill important gaps in the current capabilities available in the literature. In particular, the work here touches on aspects of all four of the stages in the model development process described above. With regard to 1), while there are tools available in the literature for automatic generation of kinetic models for an increasingly large library of fuels, these models remain subject to the constraints imposed by current chemical kinetic model structures and combustion codes.

Download or read book Advanced Chemical Kinetics written by Muhammad Akhyar Farrukh and published by BoD – Books on Demand. This book was released on 2018-02-21 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book on Advanced Chemical Kinetics gives insight into different aspects of chemical reactions both at the bulk and nanoscale level and covers topics from basic to high class. This book has been divided into three sections: (i) "Kinetics Modeling and Mechanism," (ii) "Kinetics of Nanomaterials," and (iii) "Kinetics Techniques." The first section consists of six chapters with a variety of topics like activation energy and complexity of chemical reactions; the measurement of reaction routes; mathematical modeling analysis and simulation of enzyme kinetics; mechanisms of homogeneous charge compression ignition combustion for the fuels; photophysical processes and photochemical changes; the mechanism of hydroxyl radical, hydrate electron, and hydrogen atom; and acceptorless alcohol dehydrogenation. The understanding of the kinetics of nanomaterials, to bridge the knowledge gap, is presented in the second section. The third section highlights an overview of experimental techniques used to study the mechanism of reactions.

Download or read book Mathematical Models of Chemical Reactions written by Péter Érdi and published by Manchester University Press. This book was released on 1989 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Aided Modeling of Reactive Systems written by Warren E. Stewart and published by John Wiley & Sons. This book was released on 2008-03-17 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to apply modeling and parameter estimation tools and strategies to chemicalprocesses using your personal computer This book introduces readers to powerful parameter estimation and computational methods for modeling complex chemical reactions and reaction processes. It presents useful mathematical models, numerical methods for solving them, and statistical methods for testing and discriminating candidate models with experimental data. Topics covered include: Chemical reaction models Chemical reactor models Probability and statistics Bayesian estimation Process modeling with single-response data Process modeling with multi-response data Computer software (Athena Visual Studio) is available via a related Web site http://www.athenavisual.com enabling readers to carry out parameter estimation based on their data and to carry out process modeling using these parameters. As an aid to the reader, an appendix of example problems and solutions is provided. Computer-Aided Modeling of Reactive Systems is an ideal supplemental text for advanced undergraduates and graduate students in chemical engineering courses, while it also serves as a valuable resource for practitioners in industry who want to keep up to date on the most current tools and strategies available.

Download or read book Kinetic Models of Catalytic Reactions written by G.S. Yablonskii and published by Elsevier. This book was released on 1991-04-17 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been written by a group of mathematicians and chemists whose common interest is in the complex dynamics of catalytic reactions. Based on developments in mathematical chemistry, a general theory is described that allows the investigation of the relationships between the kinetic characteristics of complex reactions and their detailed reaction mechanism. Furthermore, a comprehensive analysis is made of some typical mechanism of catalytic reactions, in particular for the oxidation of carbon monoxide on platinum metals. In fact, the book presents three kinetics: (a) detailed, oriented to the elucidation of a detailed reaction mechanism according to its kinetic laws; (b) applied, with the aim of obtaining kinetic relationships for the further design of chemical reactors; and (c) mathematical kinetics whose purpose is the analysis of mathematical models for heterogeneous catalytic reactions taking place under steady- or unsteady-state conditions.

Download or read book Mathematical Modelling of Gas Phase Complex Reaction Systems Pyrolysis and Combustion written by and published by Elsevier. This book was released on 2019-06-06 with total page 1034 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modelling of Gas-Phase Complex Reaction Systems: Pyrolysis and Combustion, Volume 45, gives an overview of the different steps involved in the development and application of detailed kinetic mechanisms, mainly relating to pyrolysis and combustion processes. The book is divided into two parts that cover the chemistry and kinetic models and then the numerical and statistical methods. It offers a comprehensive coverage of the theory and tools needed, along with the steps necessary for practical and industrial applications. Details thermochemical properties and "ab initio" calculations of elementary reaction rates Details kinetic mechanisms of pyrolysis and combustion processes Explains experimental data for improving reaction models and for kinetic mechanisms assessment Describes surrogate fuels and molecular reconstruction of hydrocarbon liquid mixtures Describes pollutant formation in combustion systems Solves and validates the kinetic mechanisms using numerical and statistical methods Outlines optimal design of industrial burners and optimization and dynamic control of pyrolysis furnaces Outlines large eddy simulation of turbulent reacting flows

Download or read book Modeling of Chemical Reactions written by R.W. Carr and published by Elsevier Science. This book was released on 2007-11-01 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Chemical Reactions covers detailed chemical kinetics models for chemical reactions. Including a comprehensive treatment of pressure dependent reactions, which are frequently not incorporated into detailed chemical kinetic models, and the use of modern computational quantum chemistry, which has recently become an extraordinarily useful component of the reaction kinetics toolkit. It is intended both for those who need to model complex chemical reaction processes but have little background in the area, and those who are already have experience and would benefit from having a wide range of useful material gathered in one volume. The range of subject matter is wider than that found in many previous treatments of this subject. The technical level of the material is also quite wide, so that non-experts can gain a grasp of fundamentals, and experts also can find the book useful. A solid introduction to kinetics Material on computational quantum chemistry, an important new area for kinetics Contains a chapter on construction of mechanisms, an approach only found in this book

Download or read book Automatic Generation and Analysis of Chemical Kinetic Mechanisms written by Matthew Sean Johnson and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many important processes in the world are controlled by chemical kinetics, from the combustion of fuels in engines, the production of polymers, the electrochemistry of batteries to biological processes. However, many if not most overall chemical processes do not occur in a single step reaction between reactants and products and can involve hundreds of different elementary reactions and intermediates. In many cases how well we can resolve and parametrize these elementary reactions and intermediates control ability to predict the behavior of the associated process. These systems of species reactions and their associated parameters are usually referred to as detailed kinetic mechanisms. Creating detailed kinetic mechanisms, however, requires us to determine both what reactions can happen in a given system and how fast they occur. This can be incredibly tedious an challenging to do by hand so it is often more practical to use automatic mechanism generators such as the Reaction Mechanism Generator (RMG) software. RMG allows us to build a workflow for generating and refining these mechanisms where we run RMG to generate a mechanism analyze the mechanism to determine important parameters and improve those parameters based on quantum chemistry calculations, experiments and literature, integrate the new data into RMG's estimators and rerun RMG to generate a new mechanism. This thesis presents a number of improvements to different aspects of this workflow and applications of this workflow. New faster and more advanced techniques and software are presented for analyzing chemical kinetic mechanisms. Improvements are presented for RMG's algorithm for selecting species and reactions to include in the mechanism. Improved techniques for generating, refining and computing phenomenological rate coefficients for pressure dependent networks are also presented. Additionally presented, is the RMG-database that manages estimation with RMG and a new machine learning based algorithm for estimating the rate coefficients of reactions. Lastly, an application of this workflow to generate a mechanism for the combustion and pyrolysis of methyl propyl ether and the extension and application of RMG to model the solid electrolyte interphase in lithium batteries are presented.

Download or read book Development of Kinetic Model Reduction Framework and Its Application in Realistic Flow Simulation written by Kaiyuan He and published by . This book was released on 2010 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this research is to develop a kinetic model reduction framework that enables incorporation of detailed chemistry with realistic flow simulation. Comprehensive computational fluid dynamics tools and detailed kinetic mechanisms have been developed, and the fully integration of these two components has been recognized as an imperative necessity to represent realistic systems. However, integrating detailed chemistry in complex flow simulation is expensive and oftentimes prohibitive. Thus this work is driven by the premise to reduce the computational intensity introduced by including detailed chemistry in realistic flow simulation and meanwhile retain acceptable accuracy. The work in this dissertation is focused on the development of an efficient yet accurate kinetic reduction method that enables dynamic reduction within the context of reactive simulations. Excessive computational intensity introduced by the integration of detailed chemistry in reactive flow simulation stems from the large size of detailed kinetic models. The kinetic model reduction method proposed in this dissertation is to address the following two unique aspects: (i) effective reduction of model size; and (ii) efficient integration of the reduction method dynamically during reactive flow simulation without introducing significant overhead. The proposed method is based on an element flux analysis approach which provides an indicator to quantify element transitions between species. The element flux can be further implemented to retrieve useful information from the kinetic network and identify active species under given reaction conditions, which constitute the fundamental of kinetic analysis and redundancy identification in mechanism reduction. It is demonstrated in this research that element flux analysis gives rise to both an effective and efficient dynamic mechanism reduction method, as well as a useful kinetic analysis tool. The proposed approaches can be extended to multiple disciplines since a large number of applications in novel fuel development, engine design, and petro chemistry require the efficient modeling of reactive flows.