Innovative Digital Twins for Advanced Combustion Technologies

Introduction

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.

Digital Combustion Infrastructure

The design and development of novel combustion technologies in power and heat generation, transportation, and manufacturing processes require developing a digital combustion infrastructure. This infrastructure promises to bring down the needed R&D investments for meeting the tightening environmental regulations.

Challenges in Combustion Prediction

However, predicting combustion processes is a complex and challenging task. The tools available today fall very short of what is needed for new design and optimisation.

Innovation: Digital Twin

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.

Expected Impact

Our approach is expected to impact significantly new combustion systems while reducing the resources and time for designing such fuel-flexible, non-polluting, and energy-efficient systems.

Commercialisation Potential

This is expected to have vast commercialisation potential in the industries:

1. Designing environmentally friendly energy systems
2. Supplying digital tools for the design processes.