Researcher to develop tools to control vapour explosion

New Delhi: Artificial Intelligence (AI) and machine learning may soon be used to develop indigenous technology for prediction and control of vapour explosion-induced accidents in boilers so as to prevent such mishaps.

The development assumes importance in view of the fact that a staggering 23,000 boiler accidents have been recorded worldwide over the past 10 years, wherein India alone accounts for the 34 per cent of the global deaths.

An Associate Professor in the Department of Mechanical Engineering, IIT-Patna, Rishi Raj, and a recipient of this year's Swarnajayanti fellowship instituted by the Department of Science and Technology (DST), Government of India, is working on a "novel" technology utilising Artificial Intelligence/Machine Learning to develop prognostic tools for advance prediction and control of vapor explosion-induced accidents in boilers.

"This indigenous technology for online monitoring and control of boiling process will help improve the health, efficiency, and economy of boilers used in key industrial and strategic applications. It bridges the gap between the fundamental knowledge of bubble dynamics on a heated substrate and about how boiling actually occurs in large-scale systems used in chemical, thermal, nuclear, petroleum, space-based, and manufacturing applications," said a release from the Ministry of Science & Technology.

Rishi Raj recently demonstrated that the acoustic fingerprint associated with bubbles may be instrumental in decoding the science of boiling. The thermal and optical characterisation strategies represent a two-dimensional map of the actual three-dimensional boiling phenomena.

In comparison, the sound of boiling imbibes statistically rich and temporally resolved information of bubble activity. For this, his research group has developed an acoustic emission-based deep learning framework which enables advance prediction of boiling crisis to mitigate thermal runaway induced failures in boiling-based systems.