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2019.9.27,张永金,An adaptive model order reduction method for parametrized evolution equations

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报告题目:  An adaptive model order reduction method for parametrized evolution equations

报告人:  张永金  博士

摘要Model order reduction (MOR) has emerged as an important tool in reducing the computational burden of large-scale systems, particularly in real-time or many-query contexts, e.g., optimization, control, and uncertainty quantification. In this talk, we present a brief introduction of projection-based MOR methods and show some applications of MOR in chemical engineering. In particular, efficient output error estimates are derived to adaptively construct reduced-order models with desired accuracy. Applications to Burgers Equations and chromatographic models demonstrate that the reduced-order models are very efficient in reducing the computational cost when applied to accelerate PDE constrained optimization and uncertainty quantification.

 

时间:2019927日(周五)下午4:30-5:30

地点:逸夫楼1417

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