Engineering topics

PAL, PINAKI

Publications and source records attributed to PAL, PINAKI.

2 records

DOE OSTI2021

CHEMNODE: CHEMICAL KINETICS SOLVER APPROACH BASED ON NEURAL ORDINARY DIFFERENTIAL EQUATIONS

This software contains an algorithm to model and predict the time evolution of chemical kinetics in reacting flow simulations using neural ordinary differential equations (NODEs). The approach works by using artificial neural networks to predict the chemical source terms. It achieves this by using forward-mode automatic differentiation and the Levenberg-Marquardt algorithm to adjust the neural network parameters, such that the discrepancies between the actual and predicted species profiles are minimized.

OWOYELE, OPEOLUWA↗

DOE OSTI2017

ML-GA

ML-GA is a software that can be used to expedite design optimization process combining machine learning and genetic algorithm approaches. It employs a machine learning (ML) model (any ML algorithm can be incorporated) to predict the quality (merit) of a design from the input parameters. Then, a stochastic global optimization genetic algorithm (GA) is used, with the machine learning model as the objective function, to optimize the input parameters based on the merit function. ML-GA is scalable to higher computational platforms like supercomputers and clusters enabling optimization to be performed in significantly short time frames (e.g., in a day).

PAL, PINAKI↗