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Chapter 7 Trust-region Framework for ROM-based Optimization Synopsis Trust-region methods provide an excellent adaptive framework for ROM-based optimization since they not only restrict the step around the root-point, but also synchronize ROM upda- tion with the information obtained during the course of optimization, thus providing a robust and globally convergent framework. In this chapter, we first develop an exact penalty-based trust-region algorithm, and develop correction schemes for the objective and the constraints to ensure global convergence with ROM-based approximate models. Algorithm with correc- tions is demonstrated for a two-bed four-step PSA case study for post-combustion capture. Next, highlighting drawbacks of the penalty approach and benefits of a filter, we develop a hybrid filter trust-region algorithm for constrained ROM-based optimization. Finally, the filter algorithm is illustrated with the PSA case study. In particular, we observe that both algo- rithms converge to a local optimum of the original optimization problem within reasonable trust-region iterations and optimization CPU time. Chapter 7. Trust-region Framework for ROM-based Optimization 134PDF Image | Design and Operation of Pressure Swing Adsorption Processes
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