Constrained reduced-order modeling using bounded Gaussian processes for physically consistent reacting flow predictions

Constrained reduced-order modeling using bounded Gaussian processes for physically consistent reacting flow predictions

Reduced-order models offer a cost-effective and accurate approach to analyzing high-dimensional combustion problems. These surrogate models are built in a data-driven manner by combining computational fluid dynamics simulations with Proper Orthogonal Decomposition (POD) for dimensionality reduction...

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Bibliographic Details
Main Authors: Muhammad Azam Hafeez, Alberto Procacci, Axel Coussement, Alessandro Parente
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Energy and AI
Subjects:
Reduced-order model
Gaussian Process Regression
Constrained likelihood functions
Downsampling
Combustion
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546825000862
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http://www.sciencedirect.com/science/article/pii/S2666546825000862

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