Project description
Digital twins for energy-efficient combustion systems
As renewable energy sources become increasingly vital for achieving carbon neutrality, sustainable combustion and renewable synthetic fuels remain essential, necessitating the development of new technologies. Establishing a robust digital infrastructure for research holds significant importance in this endeavour. However, accurately predicting combustion processes presents a complex challenge, and current tools require enhancement. In this context, the ERC-funded INVENT project proposes an innovative method that integrates theory, experiments, simulations and machine learning to create a digital twin. This unique approach enables the prediction of complex multi-physics systems and facilitates the design of combustion-based energy generation applications for expanding markets. The method can help streamline the resources and time required for designing fuel-flexible, non-polluting and energy-efficient systems.
Objective
Significant adoption of renewable sources will be witnessed in future years to meet the long-term objective of CO2 neutrality and mitigate the effects of global warming. While electrification will play a key role in the transition to a sustainable energy system, combustion processes will remain part of the picture, requiring sustainable combustion technologies and renewable synthetic fuels. The design and development of novel combustion technologies in power and heat generation, transportation and manufacturing processes require developing a digital combustion infrastructure that promises to bring down the needed R&D investments for meeting the tightening environmental regulations. However, predicting combustion processes is a complex and challenging task, and the tools available today fall very short of what is needed for new design and optimisation. We made an innovation that formed a digital twin, combining theory, experiments, simulations and machine learning into one unique combination. With our approach, we can predict complex multi-physics systems that can be used for designing combustion-based energy generation applications for growing markets. Our approach is expected to impact significantly new combustion systems while reducing the resources and time for designing such fuel-flexible, nonpolluting and energy-efficient systems. This is expected to have vast commercialisation potential in the industries 1) designing environmentally friendly energy systems and 2) supplying digital tools for the design processes.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
1050 Bruxelles / Brussel
Belgium