Study of Site Investigation Sample Quality and Worst-Case Scale of Fluctuation for Monopiles Based on Conditional Random Fields
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 3
Abstract
The spatial variability of soil is usually modeled as a nonstationary unconditional random field (URF), which utilizes only the statistics of the soil field, and conditional random field (CRF), which utilizes both the statistics and the actual data at “sampled” locations. The simulated undrained shear strength of soil and random bearing capacity of monopiles using URF and CRF are compared, and the results show that CRF can more accurately reflect the real soil strength profile and significantly reduce the coefficient of variation of random bearing capacity of monopiles. However, of course, the priority of CRF over URF is based on the quality of the sampled data. The effects of various site investigation parameters (vertical investigation interval, investigation depth, and horizontal investigation distance) on the bearing capacity of monopiles are investigated. It can be concluded that, to ensure the quality of sampled data for establishing CRF, the vertical investigation interval and horizontal investigation distance should be less than 0.75 times the vertical and horizontal scales of fluctuation, respectively, and the investigation depth should be greater than 1.2 times the embedment depth of monopiles. Because the estimation of the horizontal scale of fluctuation is rarely performed due to the sparse in situ data in the horizontal direction, the worst-case scale of fluctuation for monopiles is also investigated. The worst-case horizontal scale of fluctuation mainly depends on the monopile diameter and is 5–7 times the diameter of monopiles. Therefore, to be on the safe side, it is suggested that the horizontal scale of fluctuation be 5–7 times the diameter of monopiles in the design and evaluation of monopile foundations.
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Data Availability Statement
All data and models that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by the National Natural Science Foundation of China (51978129 and 51979035). This support is gratefully acknowledged.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 3 • September 2024
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© 2024 American Society of Civil Engineers.
History
Received: Jul 24, 2023
Accepted: Jan 9, 2024
Published online: Apr 25, 2024
Published in print: Sep 1, 2024
Discussion open until: Sep 25, 2024
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