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Advancing the Confidence in Parameterization for Coal Spontaneous Combustion Process: A Quantitative Study on Macro-kinetics

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Abstract

Understanding the macro-kinetics of coal–oxygen reactions is the theoretical foundation for combating coal spontaneous combustion, with focus on obtaining kinetic parameters. There are still open questions, including which thermal analysis kinetics processing methods (TAKPMs) output more confident kinetic parameters, and how these TAKPMs respond in terms of computational accuracy when experimental conditions change. This study evaluated these questions quantitatively, and yielded the following noteworthy findings. (1) Integral processing-based multi-scan methods were more data-friendly than differentials, which produced over 40% error due to thermal noise. (2) Combined 29 widely used most probable reaction mechanism functions (MPRMFs), like Jander, Ginstling–Brounshtein, and Zhuralev–Lesokin–Tempelman, with five popular single-scan methods, and ran 870+ calculations under six experimental conditions. Using traditional model fitting to identify MPRMFs can introduce errors of 4.08–275.49% (median 121.99%). (3) Applied spectroscopy–Málek–Popescu coupling for high-confidence MPRMFs. Its integration into single-scan methods improved computational accuracy, reducing error to the range of 1.84–76.20%. However, a median of 37.76% error indicates that some single-scan methods still failed to yield satisfactory results. (4) Notably, the accuracy of single-scan methods correlated significantly with heating rate, with various methods showing positive or negative correlations. From 5 to 15 K/min, the increase/decrease in accuracy ranged 10.63–244.25% (with median of 51.40%). These findings underline the need for a case-by-case selection of TAKPMs based on experimental conditions, ensuring more confident kinetic parameters. This study introduced a workflow, exemplified with bituminous coal, to assist researchers in selecting the optimal TAKPMs for diverse experimental scenarios.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant nos. 52274199, 51574111), Scientific Research Foundation of State Key Lab. of Coal Mine Disaster Dynamics and Control (Grant No. 2011DA105287—MS202113), the China Postdoctoral Science Foundation (Grant nos. 2021M700565, 2022T150772), and the Postdoctoral Natural Science Foundation of Chongqing (Grant no. cstc2021jcyj–bsh01).

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Authors and Affiliations

  1. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400044, China

    Xinlei Yang, Liang Wang, Haitao Li, Dong Yang & Minggao Yu

  2. School of Mine Safety, North China Institute of Science and Technology, Sanhe, 065201, Hebei, China

    Tingxiang Chu

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  1. Xinlei Yang
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Correspondence to Liang Wang or Minggao Yu.

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Yang, X., Wang, L., Chu, T. et al. Advancing the Confidence in Parameterization for Coal Spontaneous Combustion Process: A Quantitative Study on Macro-kinetics. Nat Resour Res 33, 1309–1333 (2024). https://doi.org/10.1007/s11053-024-10310-y

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