CFD Study of Indian Coal to Assess the Severity of Coal Dust Explosion and Its Classification as Per Explosibility Niroj Kumar Mohalik, Asfar Mobin Khan, Santosh Kumar Ray, Debashish Mishra, Jai Krishna Pandey International Journal for Numerical Methods in Fluids, 2026 This paper presents a comprehensive study using computational fluid dynamics (CFD) to evaluate the explosibility of Indian coals and classify their explosion severity. A Siwek 20 L explosion chamber was simulated by ASTM standard 1226‐19 to analyze coal samples collected from 24 coal mines across various coalfields of India. The explosibility parameters that is, maximum explosion pressure (Pmax), maximum rate of pressure rise ((dP/dt)max), explosion delay time (Ted), time to reach Pmax (Tep), and deflagration index (Kst) were estimated for each coal sample to evaluate the deflagration index, which measures the severity of explosions. The deflagration index (Kst) of all coal samples varied significantly between 47.90 bar·ms−1 and 109.43 bar·ms−1 indicating weak explosion potentials (0 < Kst < 200) as per OSHA 2009 standards. Based on this result, a classification system can be proposed for Indian coals depending on shared characteristics, which may be helpful in identifying coal according to their deflagration index (degree of severity). Presently, no formal classification system exists for Indian coal, and current assessments rely on USA OSHA regulations. Hence, multivariate statistical techniques, including feature selection, correlation analysis, multiple regression, and hierarchical clustering, were employed to identify the factors influencing explosion severity and to categorize the coal samples. Volatile matter dry (VMd) and crossing point temperature (CPT) were the most influential factors impacting Kst. A non‐linear regression model yielded a polynomial equation with a strong fit (R2 = 0.909, std. error of estimate = 5.19%) for predicting the deflagration index and validated with test results. Hierarchical clustering further classified the coal samples into three distinct groups based on their explosion susceptibility: highly susceptible, moderately susceptible, and potentially susceptible. The proposed classification and prediction model can guide industry stakeholders to implement more effective explosion mitigation strategies and safety protocols.
Effect of depth and particle size on spontaneous combustion of coal in deep underground mines of Jharia coalfield Debashish Mishra, D.P. Mishra, N K Mohalik, S K Ray, J K Pandey Journal of Sustainable Mining, 2025 Since their inception, the deep mines have faced the challenges of spontaneous heating and fire. The study examines the impact of coal seam depth and particle size on the spontaneous combustion of coal. A spontaneous heating study of seven coal samples shows moisture, volatile matter, and ash do not exhibit any clear trend except for fixed carbon, which shows a direct relationship. However, crossing point temperature (CPT) and thermo-gravimetric (TGignition) temperature reveal an inverse relationship between spontaneous combustion and the depth of the coal seam. Five size ranges: < 106, 106–212, 212–425, 425–2000, and 0–212 µm are studied, which displayed an increase in mean specific surface area (SSA) by 87% and a decrease in mean D90 value by 93%, with a decrease in particle size from 2000 to 106 µm. The reduction in particle size increases the spontaneous heating tendency by nearly 12–14%. The results show that external factors like coal seam depth, particle size, specific surface area (SSA), mining methods, and others influence spontaneous heating and fire in the Jharia coalfield. Additionally, we develop three mathematical models to forecast spontaneous heating in deep underground coal mines, considering CPT, TGignition, particle size (D90), SSA, and coal seam depth.
Methodology in early detection of conveyor belt fire in coal transportation Santosh Kumar Ray, Asfar Mobin Khan, Niroj Kumar Mohalik, Debashish Mishra, Nikhil Kumar Varma, Jai Krishna Pandey, Pradeep Kumar Singh Energy Sources Part A Recovery Utilization and Environmental Effects, 2025 Thermal power units are a major source of power generation in India. Belt conveyor is the leading transportation system in a thermal power plant. Belt conveyor fire in a thermal power plant breaks ...
Optimization of ventilation system for prevention of spontaneous heating/fire during extraction of thick coal seam – A CFD approach Journal of Mines Metals and Fuels, 2019
