Abstract
An accurate understanding of the physical and mechanical properties of rocks is of great importance in several rock mechanical engineering projects. Direct measurement is the most reliable method for obtaining the properties, however, it is sometimes restricted. In such cases, applying prediction models is a practical alternative. The Mohr-Coulomb failure criterion is one of the most frequently adopted models in rock mechanics and is represented by the cohesion and internal friction angle. However, despite their importance, prediction models for the two properties are relatively fewer than those of other properties. In this study, prediction models for the two properties were constructed based on a database collected from southern part of the Korean Peninsula. The extreme gradient boosting method was adopted to construct the models, and their performances were evaluated by comparing them with conventional regression models and artificial neural networks. Consequently, the extreme gradient boosting model exhibited the lowest error and highest prediction performance for both the Mohr-Coulomb constants. In addition, sensitivity analyses were performed to investigate the relative importance of the input variables. This paper aims to provide a database of several properties and to suggest prediction models for the Mohr-Coulomb constants so that it can be utilized as a reference in several rock engineering applications.
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This research was financially supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry and Energy (No. 20211710200010C), South Korea.
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Choi, S., Jeong, H. & Cheon, DS. Prediction of Mohr-Coulomb Constants of Selected Korean Rocks Based on Extreme Gradient Boosting Method and Its Evaluation. KSCE J Civ Eng 26, 2468–2477 (2022). https://doi.org/10.1007/s12205-022-1388-3
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DOI: https://doi.org/10.1007/s12205-022-1388-3