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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| Main Authors: | Muhammad Azam Hafeez, Alberto Procacci, Axel Coussement, Alessandro Parente |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546825000862 |
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