Parametric optimization is a critical component in designing and prototyping combustion
systems. However, existing parametric optimization methods often suffer from either …

A combustion chemistry acceleration scheme for implementation in reacting flow simulations
is developed based on deep operator nets (DeepONets). The scheme is based on a …

Chemical reaction neural networks (CRNNs) established as a useful tool for autonomous
mechanism discovery. While they encode some fundamental physical laws, mass-and atom …

Recently, artificial neural networks (ANNs) have been frequently embedded in
computational fluid dynamics (CFD) solvers as surrogate tools for solving chemical reaction …

Trained neural networks (NN) are attractive as surrogate models to replace costly
calculations in physical simulations, but are often unknowingly applied to states not …

As emissions regulations for greenhouse gas emissions become more strict, it is important to
increase the efficiency of engines by improving on the design and operation. Current …

As emissions regulations for greenhouse gases become more strict, it is important to
increase the efficiency of engines by improving their design and operation. Current …

The mixture-of-experts (MoE) framework, which enables collaborative utilization of multiple
models specialized in distinct tasks toward a new task, is especially useful for materials …

As emissions regulations for greenhouse gas emissions become more strict, it is important to
increase the efficiency of engines by improving on the design and operation. Current …

The energy transition and the transformation of the chemical industry are major efforts in
addressing the challenges of climate change. Both require the development of new and …