Multivariate adaptive regression splines model for reliability assessment of serviceability limit state of twin caverns
Goh, Anthony Teck Chee
Date of Issue2014
School of Civil and Environmental Engineering
Construction of a new cavern close to an existing cavern will result in a modification of the state of stresses in a zone around the existing cavern as interaction between the twin caverns takes place. Extensive plane strain finite difference analyses were carried out to examine the deformations induced by excavation of underground twin caverns. From the numerical results, a fairly simple nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) has been used to relate the maximum key point displacement and the percent strain to various parameters including the rock quality, the cavern geometry and the in situ stress. Probabilistic assessments on the serviceability limit state of twin caverns can be performed using the First-order reliability spreadsheet method (FORM) based on the built MARS model. Parametric studies indicate that the probability of failure increases as the coefficient of variation of Q increases, and decreases with the widening of the pillar.
Geomechanics and engineering
© 2014 Techno-Press. This paper was published in Geomechanics and Engineering and is made available as an electronic reprint (preprint) with permission of Techno-Press. The paper can be found at the following official DOI: [http://dx.doi.org/10.12989/gae.2014.7.4.431]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.