Model Identification and Model Based Analysis of Membrane Reactors

This work considers problems of model identification and model based analysis of membrane reactors. The parameter identification and optimal experimental design problems for gas transport through both single and multi-layer membranes have been investigated. A genetic algorithm has been improved to solve the corresponding global optimization problems. Nonlinear analysis has been performed for the steady state solution of membrane reactor models, and pattern formation has been studied. In chapter 2, the membrane reactor models considered in this work are introduced and discussed briefly. The identification of multi-layer membrane models, which is the focus of the first part of this work, is a difficult global optimization problem. Chapter 3 discusses methods for solving this problem. Since the objective function is non-convex, a traditional gradient based hill climbing algorithm is unable to locate the minima correctly. Therefore a global optimizer should be applied instead. However, the genetic algorithm that is used in this work becomes also inefficient in solving this problem because of the high correlation of the parameters. Chapter 3 first gives background of numerical algorithm for parameter identification and experimental design, and then is focused on improving the efficiency of genetic algorithm to solve the demanding global optimization problems. A new method with coordinate transformation is developed and applied successfully to the problems in chapter 4.

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