Industrial decarbonization is an important step towards achieving ‘clean and affordable energy', which is one of the UN Sustainable Development Goals 2030 Agenda. With the currently limited renewable energy resources, a short-term strategy is required to replace the fossil-fuels in burners, furnaces, gas turbines and internal combustion engines with zero-carbon fuels, such as ammonia/hydrogen. Wet-HyAm proposes an intelligent novel approach for this transition while offering minimum technology retrofitting requirements. Wet (humidified) combustion of ammonia/hydrogen, which is a less-explored idea, has a huge potential to achieve flame characteristics similar to those of the conventional fossil fuels in order to enable such a transition and help mitigate NOx/N2O formation. In Wet-HyAm, machine learning through deep RL neural networks is employed to find the optimal operating conditions for transitioning from fossil fuels to zero-carbon fuels in various combustion systems.

2024

2028