Efficiency of Nondeterministic Methods in Reliability Analysis of Deep Excavations: Case Study of the Soheil Project
Publication: International Journal of Geomechanics
Volume 21, Issue 10
Abstract
Geotechnical engineers deal with uncertainties in different projects. These uncertainties can be captured using nondeterministic approaches. Although during the last two decades numerous probabilistic and nonprobabilistic studies have been performed in a variety of fields in geotechnical engineering there is a limited amount of research in the literature on the applicability of different nondeterministic methods to evaluate statistical moments, reliability index (β), and most likely values (MLVs) of a system’s response during excavation projects. In this paper, the point estimate method (PEM), random set (RS) theory, and Monte Carlo simulation (MCS) methods with different mathematical procedures will be employed. This paper aims to present and compare these methods when estimating the mean (μ), standard deviation (σ), MLVs, probability of unsatisfactory performance (Pf), or β in the deformation and stability analysis of an instrumented deep excavation project in the presence of normal and nonnormal basic variables. In addition, due to the successful performance of the RS theory that was reported in previous researches, the code for the RS method was provided for further practical and research purposes. Finally, recommendations on the suitability of the methods to estimate the aforementioned statistics during excavation are provided.
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International Journal of Geomechanics
Volume 21 • Issue 10 • October 2021
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© 2021 American Society of Civil Engineers.
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Received: Nov 24, 2020
Accepted: May 1, 2021
Published online: Jul 23, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 23, 2021
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