Toward sustainable mining: an in silico photothermal investigation of coal susceptibility to spontaneous combustion

Spontaneous combustion (sponcom) of coal poses serious safety, economic, and environmental challenges in mining operations, necessitating early and reliable assessment of coal susceptibility towards sponcom. This work presents a novel in silico photothermal sensing (PTS) framework to investigate coal's thermal behaviour and its relation to sponcom susceptibility. The proposed approach exploits laser-induced photothermal heating and the resulting thermo-optic refractive index modulation in the air near to the coal surface, detected using a Mach-Zehnder interferometric configuration. A transient heat diffusion model is developed to simulate temperature evolution and refractive index gradients for coal samples with varying thermal conductivity and specific heat capacity. System parameters, including pump-probe laser characteristics and detector sensitivity, are optimized to ensure measurable interferometric signals under mining-safe operating conditions. Simulated photothermal signatures corresponding to low, moderate, and high sponcom susceptibility are represented as interferometric images and are found to be distinct. The results demonstrate the potential of PTS as a rapid, non-contact, and field-deployable tool for early-stage assessment of coal spontaneous combustion risk, supporting safer and more sustainable mining practices.