Bayesian Framework for Assessing Effectiveness of Geotechnical Site Investigation Programs
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 1
Abstract
Site investigation data can play an important role in not only site characterization but also the improvement of engineering design. It is tempting to predict the potential benefit of a site investigation before it is actually conducted. In this study, a Bayesian framework to assess the effectiveness of a site investigation program is proposed. The expected reduced variance (ERV) is employed to measure the uncertainty reduction owing to site investigation data. The uncertain outcomes of all possible site investigation data are considered through their probabilistic distributions. Then a framework to calculate the ERV is established. Monte Carlo simulation is adopted and the statistical uncertainty can be analyzed through the bootstrap method. Two examples of a shallow foundation on sand and an undrained slope are illustrated in this paper. Based on the examples studied, the optimal sampling layout is also discussed. The proposed method is promising to be applied in optimization of the sampling layout for various geotechnical practices.
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Data Availability Statement
All data that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Key Research and Development Program of China (Grant No. 2021YFB2600500), the National Natural Science Foundation of China (Nos. 42072302 and 41672276), Shuguang Program from Shanghai Education Development Foundation and Shanghai Municipal Education Commission (19SG19), and the Fundamental Research Funds for the Central Universities.
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© 2022 American Society of Civil Engineers.
History
Received: Feb 1, 2022
Accepted: Aug 27, 2022
Published online: Oct 20, 2022
Published in print: Mar 1, 2023
Discussion open until: Mar 20, 2023
ASCE Technical Topics:
- Analysis (by type)
- Bayesian analysis
- Computing in civil engineering
- Continuum mechanics
- Distribution functions
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Foundations
- Geotechnical engineering
- Geotechnical investigation
- Mathematical functions
- Mathematics
- Motion (dynamics)
- Probability
- Probability distribution
- Shallow foundations
- Site investigation
- Solid mechanics
- Statistical analysis (by type)
- Uncertainty principles
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