Stochastic assessment of rockburst potential in underground spaces using Monte Carlo simulation
| dc.authorid | 0000-0001-7301-5914 | |
| dc.contributor.author | Kadkhodaei, Mohammad Hossein | |
| dc.contributor.author | Ghasemi, Ebrahim | |
| dc.contributor.author | Sarı, Mehmet | |
| dc.date.accessioned | 2022-09-29T06:16:48Z | |
| dc.date.available | 2022-09-29T06:16:48Z | |
| dc.date.issued | 2022 | |
| dc.department | Mühendislik Fakültesi | |
| dc.description.abstract | Rockburst (RB) is known as one of the deadliest and most destructive geotechnical events in deep underground spaces under high stresses. The complexity of the RB phenomenon and uncertainty arising from variability in geotechnical and geomechanical conditions makes its prediction very difficult. The current study is an attempt to address the suitability of the stochastic modeling approach for the evaluation of RB potential and to assess the effects of the contributing parameters on the phenomenon. To do this study, a database containing the major effective parameters on RB potential (i.e. stress concentration coefficient, brittleness coefficient, and elastic energy index) compiled from 335 case histories of RB in various underground projects worldwide was applied. Using this database, first, a new deterministic mathematical relation for predicting RB potential was developed using gene expression programming (GEP) method. Then, the RB phenomenon was simulated by the Monte Carlo (MC) method. The results reveal that stochastic modeling is a good means for modeling and evaluating the effects of the variability of contributing parameters on RB. Finally, sensitivity analysis was conducted to analyse the effects of the contributing parameters on RB potential. Sensitivity analysis showed that stress concentration coefficient, brittleness coefficient, and elastic energy index have a direct relationship with RB potential. Furthermore, the elastic energy index was found to be the most effective parameter on the RB potential with regression coefficient of + 0.50. | |
| dc.identifier.doi | 10.1007/s12665-022-10561-z | |
| dc.identifier.endpage | - | en_US |
| dc.identifier.issn | 1866-6280 | |
| dc.identifier.issn | 1866-6299 | |
| dc.identifier.issue | 18 | en_US |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.startpage | - | en_US |
| dc.identifier.uri | https:/dx.doi.org/10.1007/s12665-022-10561-z | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/9696 | |
| dc.identifier.volume | 81 | en_US |
| dc.identifier.wos | WOS:000852586900003 | |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Springer | |
| dc.relation.ispartof | Environmental Earth Sciences | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/embargoedAccess | |
| dc.subject | Rockburst | |
| dc.subject | Underground Spaces | |
| dc.subject | Stochastic Modeling | |
| dc.subject | Gene Expression Programming | |
| dc.subject | Monte Carlo Simulation | |
| dc.title | Stochastic assessment of rockburst potential in underground spaces using Monte Carlo simulation | |
| dc.type | Article |
