This paper presents a literature review on methods for enabling real-time analysis in digital
twins, which are virtual models of physical systems. The advantages of digital twins are …

The energy-intensive industry, heavily reliant on heat generation processes, faces the
critical challenge of drastically reducing greenhouse gas emissions. This study reviews the …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

A digital twin can be defined as an adaptive model of a complex physical system. Recent
advances in computational pipelines, multiphysics solvers, artificial intelligence, big data …

A chemistry reduction approach based on machine learning is proposed and applied to
direct numerical simulation (DNS) of a turbulent non-premixed syngas oxy-flame interacting …

In this work, a methodology for the tabulation of combustion mechanisms via Artificial Neural
Networks (ANNs) is presented. The objective of the methodology is to train the ANN using …

Climate change and global warming necessitate the shift toward low-emission, carbon-free
fuels. Although hydrogen boasts zero carbon content and high performance, its utilization is …

This article presents a joint numerical study on the Multi Regime Burner configuration. The
burner design consists of three concentric inlet streams, which can be operated …

Abstract Large Eddy Simulation (LES) is progressively becoming a crucial design tool for the
next generation of aeronautical combustion chambers. However, further improvements of …

There currently exist two methods for analysing an explosive mode introduced by chemical
kinetics in a reacting process: the Computational Singular Perturbation (CSP) algorithm and …