Prediction of rock burst risk in underground openings based on intuitionistic fuzzy set
Abstract Rock burst is a complex geological disaster caused by numerous factors in underground engineering construction, it is necessary to take measures to reduce disaster losses caused by rock burst under high crustal stress environment. In this paper, a model for risk prediction of rock burst is...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-07301-1 |
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| Summary: | Abstract Rock burst is a complex geological disaster caused by numerous factors in underground engineering construction, it is necessary to take measures to reduce disaster losses caused by rock burst under high crustal stress environment. In this paper, a model for risk prediction of rock burst is proposed based on intuitionistic fuzzy set theory. Considering the internal and external driving factors affecting rock burst, the uniaxial compressive strength $${\sigma _c}$$ , uniaxial tensile strength $${\sigma _t}$$ , maximum tangential stress $${\sigma _\theta }$$ , burial depth H, brittleness index $${\sigma _c}/{\sigma _t}$$ , stress coefficient $${\sigma _\theta }/{\sigma _c}$$ , and elastic strain energy index $${w_{et}}$$ were selected as the indices to analyze the risk of rock burst. A coupling algorithm of spherical fuzzy analytic hierarchy process and grey relational analysis is used to calculate the index weight. Meanwhile, membership degree and non-membership degree are used to describe the uncertainty of rock burst prediction, and the final risk level of rock burst is determined by the risk score value. To verify the degree of its accuracy and reliability, the proposed model was tested in conjunction with 35 groups of rock burst cases and compared with cloud model theory and actual situation. Eventually, this model was applied to a practical case, Kan-tan 4 (KT4) tunnel in Xinjiang, China. The predicted results align well with the actual excavation results, indicating that this model has high accuracy and reliability, and can provide a new research perspective for rock burst prediction. |
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| ISSN: | 2045-2322 |