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Numerical Methods for PDEs
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principal component analysis

Reduced-Order High Fidelity Simulations of Reacting Flows Using Low Dimensional Manifolds and Machine Learning

Hong G. Im, Professor, Mechanical Engineering; Deputy Chair, Clean Energy Research Platform, King Abdullah University of Science and Technology (KAUST)

Apr 7, 14:30 - 15:30

B1 R3119

machine learning Applied Machine Learning principal component analysis PCA computational singular perturbation renewable energy flow problems computational simulations

This talk will provide an overview of historical developments in mathematical and computational approaches to reduced order models for accelerated high fidelity reacting flow simulations in modern computing hardware.

Numerical Methods for PDEs (NumPDE)

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