Reduced-Order Modeling and ROM-Based Optimization of Batch Chromatography
A reduced basis method is applied to batch chromatography and the underlying optimization problem is solved efficiently based on the resulting reduced model. A technique of adaptive snapshot selection is proposed to reduce the complexity and runtime of generating the reduced basis. With the help of an output-oriented error bound, the construction of the reduced model is managed automatically. Numerical examples demonstrate the performance of the adaptive technique in reducing the offline time. The ROM-based optimization is successful in terms of the accuracy and the runtime for getting the optimal solution.
KeywordsPosteriori Error Estimation Reduce Basis Parabolic Partial Differential Equation Reduce Basis Method Random Sample Point
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