Analysis of an innovative sampling strategy based on k-means clustering algorithm for POD and POD-DEIM reduced order models of a 2-D reaction-diffusion system

EA Cutillo, G Petito, K Bizon… - Combustion Theory and …, 2023 - Taylor & Francis
In this work, a model-order reduction methodology based on proper orthogonal
decomposition (POD) and Galërkin projection is presented and applied to the simulation of …

Parametric Nonlinear Model Reduction Using Machine Learning on Grassmann Manifold with an Application on a Flow Simulation

N Sukuntee, S Chaturantabut - Journal of Nonlinear Science, 2024 - Springer
This work introduces a parametric model order reduction (PMOR) approach that enhances
an existing widely used technique based on proper orthogonal decomposition (POD) and …

[PDF][PDF] Stabilized model reduction for nonlinear dynamical systems through a contractivity-preserving framework

S Chaturantabut - International Journal of Applied Mathematics …, 2020 - intapi.sciendo.com
This work develops a technique for constructing a reduced-order system that not only has
low computational complexity, but also maintains the stability of the original nonlinear …

Reduced-order modeling of a local discontinuous Galerkin method for Burgers-Poisson equations

N Ploymaklam, S Chaturantabut - Thai Journal of …, 2020 - thaijmath2.in.cmu.ac.th
In this work, we apply model reduction techniques to efficiently approximate the solution of
the Burgers-Poisson equation. The proper orthogonal decomposition (POD) framework is …

[PDF][PDF] QUERY SHEET

EA Cutillo, G Petito, K Bizon, G Continillo - 2023 - researchgate.net
In this work, a model-order reduction methodology based on proper orthogonal
decomposition (POD) and Galërkin projection is presented and applied to the simulation of …

MACHINE LEARNING FOR PROJECTION-BASED MODEL-ORDER-REDUCTION OF ELASTOPLASTICITY

S Vijayaraghavan - 2022 - orbilu.uni.lu
Projection-based model-order-reduction (MOR) accelerates computations of physical
systems in case the same computation must be performed many times for different load …