Dr Rodolfo Da Silva Machado De Freitas
PhD, MSc


Research Overview

Machine learning, Combustion, Alternative and renewable fuel, Renewable energy, Molecular dynamics simulation, Modelling and simulation, Uncertainty Quantification


My research interests focus on Machine Learning (ML) in Thermofluid Modelling/Simulation for Sustainable Energy Utilisation, the development of Uncertainty Quantification (UQ) techniques for calibration and validation of simplified (reduced) chemical kinetics models, and modeling of turbulence-chemistry interactions for combustion models. The Modelling/Simulation techniques include Big data analytics for energy utilization applications; High-performance computing (HPC) for thermofluid applications; Large-eddy simulation / direct numerical simulation for fluid flow and combustion; Machine learning (with applications to fuel property and combustion emission predictions); Molecular dynamics simulation; (Multi-scale) modeling of flow in porous media.