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

DOI10.1080/13647830.2023.2174451OpenAlexW4319788667MaRDI QIDQ6046679

Unnamed Author, Unnamed Author, Unnamed Author, Unnamed Author

Publication date: 6 September 2023

Published in: Combustion Theory and Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/13647830.2023.2174451

zbMATH Keywords

reaction-diffusion systemmodel-order reduction\(k\)-means clusteringdiscrete empirical interpolation methodPOD-Galërkin

Mathematics Subject Classification ID

Fluid mechanics (76-XX) Thermodynamics and heat transfer (80Axx)

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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

Cites Work

• Parametric nonlinear model reduction using \(K\)-means clustering for miscible flow simulation
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• 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