RUcore Resource Object
RUcore Resource Object
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TitleSoftware tools for molecule-based kinetic modeling of complex systems
NameHou, Zhen (author), Klein, Michael T (chair), Neimark, Alexander V (internal member), Glasser, Benjamin J (internal member), Saeger, Roland B (outside member), Rutgers University, Graduate School - New Brunswick,
Degree Date2011-05
Date Created2011
SubjectChemical and Biochemical Engineering,
Raw materials--Computer simulation
DescriptionModeling complex process chemistries with complex feedstocks involves several aspects: composition modeling of the complex feedstock, reaction modeling of the complex chemistry, and structure property correlations to provide feed and product property estimation. This thesis was developed to automate these modeling techniques and to provide an integrated approach for combing these modeling aspects into a continuous package. The first contribution of this thesis is the development of an automated composition modeling tool called the composition model editor (CME). CME uses a statistical hybrid approach to describe a complex feedstock in terms of a set of structural attributes expressed by probability density functions (PDF). Through optimizing a limited set of attribute PDF parameters, CME can obtain a molecular composition array (MCA) for a feedstock based on limited analytical information. The second contribution of this thesis is the development of a series of automated techniques that are useful for reaction modeling. Firstly, an attribute reaction modeling (ARM) approach is developed for complex process chemistries. ARM can condense a kinetic model by allowing the number of ODEs to be far less than the number of species for a complex system, while maintaining the full molecular detail of the model. Secondly, reaction family and LFER concepts are used to control the number of kinetic parameters for a complex model. Thirdly, the ability to impose LHHW rate law allows for heterogeneous systems involving with catalysts. Last but not least, various process configurations are addressed to satisfy the kinetic modeling for complex process chemistries. The third and final contribution of this thesis is the creation of a structure correlation module used to provide data support for kinetic modeling as well as composition modeling. Group contribution methods and the quantum chemistry package are applied to estimate thermodynamic properties. A supplemental database is developed to manage property data in a high efficient way. The above contributions were then successfully applied to the development of detailed kinetic and feedstock models for complex process chemistries, including complex feedstock characterizations, lignin pyrolysis, and resid pyrolysis.
NotePh.D.
NoteIncludes bibliographical references
Noteby Zhen Hou
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061271
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.