In a significant innovative breakthrough that is expected to bring down cases of deaths due to the explosion of boilers across the world, Indian scientists are working on a technology that will predict and control ‘vapour explosion induced accidents in boilers’ using AI (Artificial Intelligence) and Machine Learning online.
Indian scientist Rishi Raj, an Associate Professor in the Department of Mechanical Engineering, IIT Patna, and a recipient of this year’s Swarnajayanti fellowship instituted by the Department of Science and Technology (DST), is working on the ‘novel technology’ utilising Artificial Intelligence, Machine Learning to develop prognostic tools for advance prediction and control of vapor explosion induced accidents in boilers, a Ministry of Science and Technology note here disclosed.
According to an estimate, a staggering 23,000 boiler accidents involving large-scale boiling systems used in chemical, thermal, nuclear, petroleum, space-based, and manufacturing application have been registered worldwide over the past 10 years, wherein India alone accounts for 34 percent of global deaths.
“This indigenous technology for online monitoring and control of the boiling process for online monitoring and control of the 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,” the note further added.
Prof Raj recently demonstrated that the acoustic fingerprint associated with bubbles may be instrumental in decoding the science of boiling. The thermal and optical characterization 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. To this end, his research group has developed an acoustic emission-based deep learning framework that enables advanced prediction of boiling crisis to mitigate thermal runaway-induced failures in boiling-based systems.
Boiling crisis or very vigorous boiling or formation of bubbles is dangerous for applications due to sudden increases in pressure and temperature, according to Prof Raj.
Professor Raj said with the support of the Swarnajayanti fellowship, he will visualize the bubble behaviour in terms of size, number density, and frequency of bubble formation and couple it with sound and thermal (temperature) data to get to the root of the problem and explain the physics of the phenomenon.
“The eventual goal is to identify the dominant bubble activity features to develop a physics-informed tool for the advance prediction of boiling regimes using a single acoustic sensor (hydrophone). Such a tool may then be deployed to invoke pre-emptive control of vapour explosion-induced accidents in industrial boilers,” Raj said.
Raj further proposed to demonstrate a feedback control strategy to initiate auxiliary cooling units to avoid undesired thermal runaway in an existing 30 kW fire-tube boiler installed at IIT Patna. Additional demonstrations will include complete mitigation of sudden increase in temperature from a few hundred to above thousand degrees (thermal runaway) observed during the boiling crisis in challenging scenarios of boiling in space-based zero-gravity conditions and to develop smart thermal management solutions for miniaturized electronic devices. Such sudden and a large increase in temperature usually results in pressure increase or meltdown of metallic components leading to leakage and explosion or other accidents, the Indian scientist said.
The progress made as a part of this project is not only anticipated to advance the science of boiling but is also expected to accelerate the implementation of modern prognostics and health management tools in existing boilers. Improved safety due to the modernization of boilers, higher productivity due to reduction in downtime, and optimal usage of energy and water resources are together anticipated to address important sustainability challenges, the Ministry note further said.