Optimization of Site-Exploration Programs for Slope-Reliability Assessment
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 1
Abstract
Site investigation through boreholes, such as vane shear tests or cone penetration tests, provides an effective means to assess the performance of geotechnical sites. Boreholes should be located such that they provide a maximum amount of information. This study develops a systematic approach for optimizing site-exploration programs based on maximizing the value of information. To compute the value of information, test data are randomly generated based on the prior model of soil parameters. Bayesian updating of the slope reliability is carried out by application of an adaptive version of the Bayesian updating with structural reliability methods (BUS) in combination with subset simulation, which is efficient in tackling problems with discrete random field representations. The approach is used for the reliability assessment of a slope in undrained clay, wherein the site-exploration program is optimized with vane shear tests to identify the undrained shear strength. Results show that the approach is able to identify the optimal location and number of boreholes.
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Data Availability Statement
Some or all data, models, or code generated or used during this study are available from the corresponding author by request. The items are listed as follows:
1.
Virtual vane shear test data simulated at different borehole locations;
2.
Karhunen–Loève expansion code used to discretize the stationary random field of a soil property;
3.
Adaptive BUS code that is used to learn the distribution of spatially varying soil properties and estimating the posterior probability of slope failure.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Projects 41867036, 41972280, U1765207), Natural Science Foundation of Jiangxi Province (CN) (Projects 2018ACB21017, 20181ACB20008, 20192BBG70078), and Young Elite Scientist Sponsorship Program by CAST (YESS). Their financial support is gratefully acknowledged.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6 • Issue 1 • March 2020
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©2020 American Society of Civil Engineers.
History
Received: Dec 29, 2018
Accepted: Jul 29, 2019
Published online: Jan 11, 2020
Published in print: Mar 1, 2020
Discussion open until: Jun 11, 2020
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