Reliability Analysis of Single Pile in Spatially Variable Soil Based on Variance Reduction Method
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 2
Abstract
Soil has spatial variability, which means that soil properties at different locations are different but correlated. To represent the spatial variability of soil surrounding a pile, the random field method (RFM) is usually adopted to discretize a random field into a number of random variables. Then, the first-order reliability analysis method (FORM) is modified and employed to perform reliability analysis, and the load-transfer method (LTM) is adopted to compute the bearing capacity of the pile. To reduce the computation cost of the reliability analysis and random field simulation, a FORM-LTM-variance reduction method (VRM) method is proposed to conduct reliability analysis for single pile in spatially variable soil, in which VRM is adopted to transfer a random field into a random variable over a characteristic length. By comparing the reliability indices using FORM-LTM-RFM and FORM-LTM-VRM, analytical formulas of the characteristic lengths under different pile lengths, coefficients of variation (COVs), and autocorrelation distances (ACDs) are computed. Benefitting from the computation accuracy and efficiency of the FORM-LTM-VRM with analytical formulas of characteristic length, resistance factors in LRFD for the reliability-based design of single pile in spatially variable soil can be easily computed for different safety levels. The accuracy and efficiency of the FORM-LTM-VRM with analytical formulas of characteristic length are demonstrated by a case study of a vertically loaded pile.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant Nos. 41972278 and 42030710).
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 2 • June 2024
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© 2024 American Society of Civil Engineers.
History
Received: Jul 13, 2023
Accepted: Nov 20, 2023
Published online: Feb 27, 2024
Published in print: Jun 1, 2024
Discussion open until: Jul 27, 2024
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