1 citations · 1 across the 3 of their papers we have counts for
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Hyper-reduction-free reduced-order Newton solvers for projection-based model-order reduction of nonlinear dynamical systems
Liam K. Magargal, Parisa Khodabakhshi, Steven N. Rodriguez
This study proposes an intrusive projection-based model-order reduction framework for nonlinear problems with a polynomial structure, solved iteratively using a Newton solver in th…
Projection-based model-order reduction via graph autoencoders suited for unstructured meshes
Liam K. Magargal, Parisa Khodabakhshi, Steven N. Rodriguez +2
This paper presents the development of a graph autoencoder architecture capable of performing projection-based model-order reduction (PMOR) using a nonlinear manifold least-squares…
Multifidelity Methods for Uncertainty Quantification of a Nonlocal Model for Phase Changes in Materials
Parisa Khodabakhshi, Olena Burkovska, Karen Willcox +1
This study is devoted to the construction of a multifidelity Monte Carlo (MFMC) method for the uncertainty quantification of a nonlocal, non-mass-conserving Cahn-Hilliard model for…
Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference
Shane A McQuarrie, Parisa Khodabakhshi, Karen E Willcox
This work formulates a new approach to reduced modeling of parameterized, time-dependent partial differential equations (PDEs). The method employs Operator Inference, a scientific…