Scientific machine learning (SciML) offers innovative approaches to tackle challenges in kinetic modeling and uncertainty quantification (UQ) for combustion simulations. This talk discusses two recent examples. First, a Chemical Reaction Neural Network (CRNN) framework is introduced for modeling lithium-ion battery thermal runaway, where Bayesian inference quantifies thermal-kinetic uncertainties, enabling more accurate and robust predictions.
Second, a neural network-accelerated framework for UQ in turbulent combustion simulations identifies a low-dimensional active kinetic subspace, capturing the effects of kinetic uncertainties across the solution space. Applied to a target turbulent flame simulation, the framework achieves accurate temperature uncertainty predictions with significantly reduced computational cost. These advances demonstrate SciML’s potential to improve the reliability and efficiency of combustion modeling.
Sili Deng,
Massachusetts Institute of Technology
Prof. Sili Deng is the Class of 1954 Career Development Associate Professor in Mechanical Engineering at Massachusetts Institute of Technology. She received her doctoral degree in mechanical and aerospace engineering from Princeton University, co-advised by Profs. Chung K. Law and Michael E. Mueller. After her postdoctoral training with Prof. Xiaolin Zheng at Stanford University, she joined MIT as an assistant professor in 2019.
Her research focuses on energy conversion and storage, specifically, the fundamental understanding of combustion and emissions, physics-informed data-driven modeling of reacting flows, carbon-neutral energetic materials, and flame synthesis of materials for catalysis and energy storage.
Prof. Deng received the Bernard Lewis Fellowship from the Combustion Institute in 2016, was selected as a member of the Frontiers of Engineering from the National Academy of Engineering in 2021, received the NSF CAREER Award in 2022, was selected as a Scialog Fellow by Research Corporation for Science Advancement in 2024, and received the Irvin Glassman Young Investigator Award by Eastern States Section of Combustion Institute and the Energy and Fuels Rising Star Award in 2024.