Due to the significant improvement in computing power and the rapid advancement of data
processing technologies, artificial intelligence (AI) has introduced new tools and …

Predictive simulation of the combustion process in engine is crucial to understand the
complex underlying physicochemical processes, improve engine performance, and reduce …

Propagating uncertainties in kinetic models through turbulent combustion simulations to
properly quantify the uncertainties in the simulation results remains a challenging and …

The effective and efficient utilization of low-calorific value (LCV) gases has gained
increasing attention in scientific research and industrial fields. In this study, the combustion …

The active subspace method is applied to Burrows–Kurkov supersonic wall-jet flame to
quantify modeling uncertainties associated with chemical kinetics, turbulence combustion …

With the increased demand for hydrogen for carbon-neutral propulsion technologies,
understanding the coupling effect of the fuel injection and cavity on flow characteristics is …

Quantifying the uncertainty of soot formation in a turbulent combustion simulation remains a
challenging task. In this work, global sensitivity analysis and uncertainty quantification of …

The numerical studies for film cooling performance have gained considerable interest for the
development of advanced gas turbines and aero-engines. However, the accuracy of …

This study introduces a novel algorithm that combines deep learning with active subspace
method to address the challenge of quantitatively analyzing the effects of various …

Propagating uncertainties in kinetic models through combustion simulations can provide
important metrics on the reliability and accuracy of a model, but remains a challenging and …