Extracting fuel can tremendously help the country attain fuel self-sufficiency
Indian Institute of Technology Madras researchers are using artificial intelligence tools to study the processes involved in the conversion of biomass to gaseous fuel. With increasing environmental concerns associated with petroleum-derived fuels, biomass is a practical solution, not in the conventional sense of directly burning wood, cow dung cakes, and coal, but as a source of energy-dense fuel. Researchers all over the world are finding methods to extract fuel from biomass such as wood, grass, and even waste organic matter.
Such biomass-derived fuel is particularly relevant to India because the current availability of biomass in India is estimated at 750 million metric tonnes per year and extracting fuel from them can tremendously help the country attain fuel self-sufficiency.
The research was led by Dr Himanshu Goyal, Assistant Professor, Department of Chemical Engineering, IIT Madras and Dr Niket S Kaisare, Professor, Department of Chemical Engineering, IIT Madras.
The paper has been co-authored by Dr Himanshu Goyal, Dr Niket Kaisare and Krishna Gopal Sharma, Fourth Year B.Tech. Student, Department of Computer Science and Engineering, IIT Madras.
Explaining the importance of such studies, Dr Himanshu Goyal, Assistant Professor, Department of Chemical Engineering, IIT Madras, said, “Understanding the complex mechanisms involved in the conversion of raw biomass into fuel is important for designing the processes and optimising reactors for the purpose.”
While models are being developed all over the world to understand the conversion of biomass into fuels and chemicals, most models take a long time to become operational. Artificial Intelligence tools such as Machine Learning (ML) can hasten the modelling processes.
The IIT Madras research team used an ML method called Recurrent Neural Networks (RNN) to study the reactions that occur during the conversion of lignocellulosic biomass into energy-dense syngas (gasification of biomass).
