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During the Fulbright-Nehru Fellowship, Dr. Mariappan will specialize in applying physics informed neural network (PINN): a machine learning method, to study combustion driven oscillations in combustors of gas turbine engines. PINN is an emerging tool, having the striking advantage to synergize experimental data and physics-based models. This synergy brings a new understanding of flame-flow interactions and helps develop more accurate hybrid models, which serve for instability prognosis and mitigation. This alternative (superior) hybrid framework will model combustor dynamics more accurately (than models derived purely from theory or experiments), even in practical systems, leading to efficient/robust control of oscillations.
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论文共 33 篇作者统计合作学者相似作者
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INTER-NOISE and NOISE-CON Congress and Conference Proceedingsno. 5 (2023): 2625-2632
Journal of Energy and Environmental Sustainability (2020): 24-31
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