##Statistics Seminar##\\ Department of Mathematics and Statistics
^ **DATE:**|Thuesday, September 19, 2023 |
^ **TIME:**|12:00pm -- 1:00pm |
^ **LOCATION:**|WH 100E |
^ **SPEAKER:**|Zengyan Zhang, Binghamton University |
^ **TITLE:**|Structure-preserving Reduced-order Models for Thermodynamically Consistent PDEs |
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**//Abstract//**
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As a powerful data-driven approach for dimensionality reduction,
the proper orthogonal decomposition reduced-order model (POD-ROM) has been
widely used as a computationally efficient surrogate model for complex
large-scale systems. Given the computational complexity of the
thermodynamically consistent models, the POR-ROM plays an important role in
reducing the spatial-temporal complexity. However, the classical POD-ROM
can destroy the thermodynamic structure in the reduced-order modeling
approach for the systems. In this talk, we will introduce a numerical
platform that can systematically derive ROMs for thermodynamically
consistent PDEs while maintaining their inherent thermodynamic principles,
and demonstrate its effectiveness in several numerical examples.
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