CoEC Combustion Autumn School 2022: Combustion theory with ML/AI applications and interactive analysis

CoEC Combustion Autumn School 2022: Combustion theory with ML/AI applications and interactive analysis intends to present the fundamentals and current challenges in combustion, as well as to introduce the use of Machine Learning (ML) and High Performance Computing (HPC) to approach Exa-scale simulations of turbulent reacting flows. Different methodologies to enhance the computational performance of high-fidelity combustion simulations will be introduced in this school. The methods cover from node to system level performance optimisations and algorithms for combustion simulations. 

This is the second training course in a series of two CoEC seasonal schools that have been planned for 2022 as part of the CoEC project. This CoEC school of combustion will allow participants to broaden their knowledge and understanding in a range of topics, including chemical kinetics in flames, soot formation in laminar, turbulent combustion, multiphase combustion of solid fuels, HPC algorithms for combustion simulation, ML and data driven modeling for turbulent reacting flows and interactive supercomputing for in-situ analysis.

The CoEC Autumn School 2022 is a joint effort by NCSA (Bulgaria), CERFACS (France), BSC (Spain), Institute of Combustion Technology (ITV) - RWTH Aachen University (Germany), Juelich Supercomputing Centre (Germany), Eindhoven University of Technology (Netherlands), and Technical University of Darmstadt (Germany).

For more information, please refer to the NCSA website (ncsa.bg) or see the attached flyer with the program.

Program Chair - Daniel Mira, Coordinator and Technical Manager of Center of Excellence in Combustion