Abstract
Rockburst, as a common disaster in geotechnical construction, such as mines, tunnels, and hydropower stations, induces huge economic losses and poses a great safety threat to construction workers. To estimate the rockburst disaster more reasonably, a method for estimating the rockburst intensity grade is proposed based on the improved entropy weight method-similar cloud model (IEWM-SCM). The IEWM-weighted rockburst estimation index can solve the problem of the imprecise objective weight in the traditional entropy weight method. Concurrently, based on the preference correction coefficient in the IEWM, the interference of abnormal values in the collected rockburst engineering case data samples is eliminated, so that the accuracy of rockburst estimation is higher, whereas the introduction of the similar cloud model theory can transfer the rockburst estimation index to the concept of cloud, thus eliminating the uncertainty and fuzziness during the rockburst estimation process. Therefore, a new method for estimating the rockburst is established based on these two methods. Moreover, seven comparative models were established for comparative analysis and finally applied to the Jinping II Hydropower Station, Jiangbian Hydropower Station, Cangling Tunnel, and Maluping Mine. Results show that the present model has higher accuracy and applicability, which offers a new method for estimating rockburst.
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Acknowledgements
This research was funded by the National Science Foundation of China (51934003) and the Major Science and Technology Special Project of Yunnan Province (No. 202202AG050014). This support is gratefully acknowledged.
Funding
This work was supported by National Natural Science Foundation of China Grant number 51934003 and Science and Technology Special Project of Yunnan Province Grant number 202102AG050024.
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ML contributed to data curation, software, and writing—original draft. KL contributed to conceptualization, methodology, supervision, and funding acquisition. QQ contributed to investigation, software, and data curation. RY contributed to writing—review and editing and data curation. GX contributed to writing—review and editing. All authors reviewed the manuscript.
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Li, M., Li, K., Qin, Q. et al. Rockburst estimation model based on IEWM-SCM and its application. Environ Earth Sci 82, 88 (2023). https://doi.org/10.1007/s12665-023-10764-y
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DOI: https://doi.org/10.1007/s12665-023-10764-y