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RISA Data-Driven Framework for Computationally Efficient Integration of Chemical Kinetics Using Neural Ordinary Differential Equations
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A data-driven methodology is introduced for computationally efficient integration of systems of stiff rate equations in chemical kinetics using neural ordinary differential equations (NODE). A systematic algorithm is ...
Performance Assessment of Chemical Kinetics Neural Ordinary Differential Equations in Pairwise Mixing Stirred Reactor
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The present study aims to assess the potential of the neural ordinary differential equations (NODE) network for reliable and computationally efficient implementation of chemistry in combustion simulations. Investigations ...