3 citations · 4 across the 11 of their papers we have counts for
3 papers · 1 filter
Entropy-Constrained Machine Learning with Residual Data Augmentation for Modeling Chemical Kinetics
Okezzi Ukorigho, Opeoluwa Owoyele
We present a physics-constrained machine learning framework for accelerating the direct numerical simulation (DNS) of turbulent reacting flows. The model replaces the direct evalua…
A Liquid-Fueled Reactor Network Model for Enhanced NOx Prediction in Gas Turbine Combustors
Philip John, Haresh Chandrasekhar, Sourav Saha +1
This study introduces a liquid-fueled reactor network (LFRN) framework for reduced-order modeling of gas turbine combustors. The proposed LFRN extends conventional gaseous-fueled r…
Efficient bifurcation and parameterization of multi-dimensional combustion manifolds using deep mixture of experts: an a priori study
Opeoluwa Owoyele, Prithwish Kundu, Pinaki Pal
This work describes and validates an approach for autonomously bifurcating turbulent combustion manifolds to divide regression tasks amongst specialized artificial neural networks…