| Project Detail |
Boosting alternative fuel adoption to accelerate the clean energy transition Hydrogen can be used as a fuel for industry, power generation, heat and transport. However, current infrastructures are not ready to cope safely with hydrogen and renewable synthetic fuels. Funded by the Marie Sklodowska-Curie Actions programme, the ENCODING project aims to smooth the transition towards the use of alternative fuels, contributing to decarbonising energy-intensive industries. To this end, it will establish a training network designed to train 10 PhD students in sustainable fuels, experimental techniques for studying turbulent reacting flows, as well as in Big Data analytics and machine learning. The focus will be placed on developing a hybrid digital infrastructure to better tackle current and future issues regarding the use of hydrogen and synthetic fuels in energy-intensive industries. At the 26th UN Climate Change Conference of the Parties (COP26), the reached consensus points for the need of an energy revolution, in which hydrogen will play a key role, especially in Energy Intensive Industries (EIIs) for which electrification is more challenging. Still, current infrastructures are not ready to adopt hydrogen and other Renewable Synthetic Fuels (RSFs) in an efficient, safe, and sustainable way. ENCODING holds the promise to smooth the transition towards RSFs use, thereby helping decarbonise EIIs. To do so, ENCODING main objective is to train the next generation of digital combustion experts, by offering them an innovative training programme. The 10 doctoral candidates will gain multidisciplinary know-how in sustainable fuels, experimental techniques and numerical simulations of turbulent reacting flows, big data analytics and machine learning, and intersectoral experience (academic and industrial relevant training). Together, they will be able to create knowledge to develop a generalised hybrid ML-based digital infrastructure, with the capability to solve current and future outstanding questions to decarbonise EIIs. The unique training is only possible thanks to the participation of renowned academic institutions with partners specialized in combustion experiments and simulation (ULB, RWTH, CNRS, CNR), data analysis and dimensionality reduction (UPM, ULB), data-driven and ML-based modelling (ULB, RWTH, CNRS) and different companies in the whole chain of knowledge: sustainable fuels (Air Liquid), combustion systems (MITIS, NPT), fuel flexible burners (WS, TENOVA), pollutant remediation strategies (AGC, AMMR) and CFD software (CONVERGE, CFD Direct). |
