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Identical Acoustic Waveforms Found Between Different-Sized Outbursts: Implications for the Propagation Mechanism of Coal and Gas Outbursts

Journal Article


Abstract


  • Every gigantic Coal and Gas Outburst begins as a tiny, localized coal failure. This point of failure leads to a rupture of the coal seam, resulting in a violent ejection of enormous amounts of gas and pulverized coal. Whether the size of an outburst is predictable and whether a large-scale outburst requires unique conditions different from smaller events are fundamental questions associated with the potential for disaster probabilistic forecasting. In this study, we conducted a series of outburst simulations using carbon dioxide (CO2) and He and recorded acoustic signals in the frequency band 0.5–50 Hz during each outburst. We established that the cross-correlation coefficients of initial waveforms between Different-Sized Outbursts are generally high, which provides evidence for identical onsets of large and small events. Therefore, we focused on the self-similar properties of rupture growth and developed a viable model to explain the outburst mechanism. In our model, every outburst is essentially a trigger sequence. A large outburst results from a cascading sequence from a small rupture whose propagation proceeded along a route at which each step of the sequence had a sufficient energy supply to continue the cascade to a larger area. However, the route to the rupture of outbursts is sensitive to coal properties and the energy supply from the surrounding area. Hence, large-scale events are highly variable and almost independent of their initial state. If this is true for the actual outbursts, it would be quite difficult to predict the scale for any forthcoming outburst event.

Publication Date


  • 2022

Citation


  • Lei, Y., Cheng, Y., Wang, L., Ren, T., & Shu, L. (2022). Identical Acoustic Waveforms Found Between Different-Sized Outbursts: Implications for the Propagation Mechanism of Coal and Gas Outbursts. Rock Mechanics and Rock Engineering. doi:10.1007/s00603-022-03026-z

Scopus Eid


  • 2-s2.0-85136874496

Web Of Science Accession Number


Abstract


  • Every gigantic Coal and Gas Outburst begins as a tiny, localized coal failure. This point of failure leads to a rupture of the coal seam, resulting in a violent ejection of enormous amounts of gas and pulverized coal. Whether the size of an outburst is predictable and whether a large-scale outburst requires unique conditions different from smaller events are fundamental questions associated with the potential for disaster probabilistic forecasting. In this study, we conducted a series of outburst simulations using carbon dioxide (CO2) and He and recorded acoustic signals in the frequency band 0.5–50 Hz during each outburst. We established that the cross-correlation coefficients of initial waveforms between Different-Sized Outbursts are generally high, which provides evidence for identical onsets of large and small events. Therefore, we focused on the self-similar properties of rupture growth and developed a viable model to explain the outburst mechanism. In our model, every outburst is essentially a trigger sequence. A large outburst results from a cascading sequence from a small rupture whose propagation proceeded along a route at which each step of the sequence had a sufficient energy supply to continue the cascade to a larger area. However, the route to the rupture of outbursts is sensitive to coal properties and the energy supply from the surrounding area. Hence, large-scale events are highly variable and almost independent of their initial state. If this is true for the actual outbursts, it would be quite difficult to predict the scale for any forthcoming outburst event.

Publication Date


  • 2022

Citation


  • Lei, Y., Cheng, Y., Wang, L., Ren, T., & Shu, L. (2022). Identical Acoustic Waveforms Found Between Different-Sized Outbursts: Implications for the Propagation Mechanism of Coal and Gas Outbursts. Rock Mechanics and Rock Engineering. doi:10.1007/s00603-022-03026-z

Scopus Eid


  • 2-s2.0-85136874496

Web Of Science Accession Number