Simultaneous Modeling and Optimization of a Cascade of Electrochemical Reactors
Soon, See-Aun
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https://hdl.handle.net/2142/69778
Description
Title
Simultaneous Modeling and Optimization of a Cascade of Electrochemical Reactors
Author(s)
Soon, See-Aun
Issue Date
1986
Department of Study
Chemical Engineering
Discipline
Chemical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Chemical
Abstract
Modeling tools based on fundamental scientific principles for the process design of cascades of electrochemical reactors are not yet available. Interactions between the electrochemical reactors, different operating conditions for each reactor, and the flow configuration of the cascade of electrochemical reactors make it a complex problem. A general, flexible methodology for process design, scale-up, simulation, and optimization of a cascade of electrochemical reactors was established. Candidate processes drawn from the chlor-alkali industry, electrodialysis, and electroorganic synthesis were used to illustrate the methodology. Process design models were developed based on fundamental scientific principles of mass, energy, and voltage balances. In addition, mass transfer, charge transfer, and ohmic effects were also taken into consideration. The system includes both nonlinear algebraic and differential equations. An orthogonal collocation technique was used to approximate the differential equation. An efficient and reliable nonlinear equation solver based on a modification of Powell's dogleg method called NEQLU was used to solve the system of nonlinear equations consisting of collocation, model, and design equations in the simulation and design studies. This system of nonlinear equations becomes part of the equality constraints in a nonlinear program in optimization. A successive quadratic programming method as implemented in the program SQPHP was used to solve the optimization model. Sensitivity of the variables at the optimum was determined through the use of Lagrange multipliers.
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