Experimental study on temperature and gas concentration evolution law during coal spontaneous combustion in the goaf
Abstract Coal spontaneous combustion (CSC) constitutes a persistent threat to global mining safety, particularly through its impact on goaf environments. Understanding the evolutionary patterns of critical parameters (O2, CH4, CO, C2H4 concentrations, and temperature) within goaf areas holds crucial...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-01688-7 |
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| Summary: | Abstract Coal spontaneous combustion (CSC) constitutes a persistent threat to global mining safety, particularly through its impact on goaf environments. Understanding the evolutionary patterns of critical parameters (O2, CH4, CO, C2H4 concentrations, and temperature) within goaf areas holds crucial importance for effective CSC prevention and control. Similarity simulation experiments were conducted using a scaled-down experimental platform to replicate CSC processes. Through numerical simulation and field measurement data, the distribution ranges of the “three zones” in the goaf within the experimental platform were determined. Results revealed the formation of an ellipsoidal heating surface centered around the combustion source. The temperature gradient near the heat source increased linearly with coal temperature (1 °C/min), while the heating effect attenuated proportionally with distance. Notably, O2 and CH4 concentration fields exhibited minimal variation due to continuous air leakage and limited gas generation. In contrast, CO and C2H4 formed enrichment zones around the heat source, demonstrating a power-law growth trend. Air leakage significantly influenced gas distribution, with downwind CO concentrations 3.96 × higher than upwind. Vertically, gas concentrations decreased with height. These findings highlight the importance of multi-parameter monitoring for early warning systems in coal mines. |
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| ISSN: | 2045-2322 |