Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 |
| Herausgeber/-innen | Michael Beer, Enrico Zio, Kok-Kwang Phoon, Bilal M. Ayyub |
| Seiten | 447-453 |
| Seitenumfang | 7 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Veranstaltung | 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 - Hannover, Deutschland Dauer: 4 Sept. 2022 → 7 Sept. 2022 |
Abstract
The study presents an approach for searching optimal borehole placement for shallow foundation design under spatially variable conditions. A recently proposed approach named Random Failure Mechanism Method is adopted, which allows for 3D bearing capacity estimations considering spatially variable soil and given borehole locations. The borehole placement problem is formulated as finding the borehole locations that minimize the standard deviation of the foundation bearing capacity. A stochastic optimization framework named Asymptotic Bayesian Optimization is implemented to handle the inherent variability of the standard deviation estimates. The applicability of the proposed approach is demonstrated based on a scenario involving a rectangular footing and two boreholes. The feasibility and effectiveness of the approach are promising for future applications, mostly for proposing optimal borehole placement for typical engineering practice foundation layouts.
ASJC Scopus Sachgebiete
- Entscheidungswissenschaften (insg.)
- Managementlehre und Operations Resarch
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
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Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. Hrsg. / Michael Beer; Enrico Zio; Kok-Kwang Phoon; Bilal M. Ayyub. 2022. S. 447-453.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Random Failure Mechanism Method in Optimal Borehole Placement for Shallow Foundation Design Under Spatially Variable Conditions
AU - Chwała, M.
AU - Jerez, D. J.
AU - Jensen, H. A.
AU - Beer, M.
N1 - Publisher Copyright: © 2022 ISRERM Organizers. Published by Research Publishing, Singapore.
PY - 2022
Y1 - 2022
N2 - The study presents an approach for searching optimal borehole placement for shallow foundation design under spatially variable conditions. A recently proposed approach named Random Failure Mechanism Method is adopted, which allows for 3D bearing capacity estimations considering spatially variable soil and given borehole locations. The borehole placement problem is formulated as finding the borehole locations that minimize the standard deviation of the foundation bearing capacity. A stochastic optimization framework named Asymptotic Bayesian Optimization is implemented to handle the inherent variability of the standard deviation estimates. The applicability of the proposed approach is demonstrated based on a scenario involving a rectangular footing and two boreholes. The feasibility and effectiveness of the approach are promising for future applications, mostly for proposing optimal borehole placement for typical engineering practice foundation layouts.
AB - The study presents an approach for searching optimal borehole placement for shallow foundation design under spatially variable conditions. A recently proposed approach named Random Failure Mechanism Method is adopted, which allows for 3D bearing capacity estimations considering spatially variable soil and given borehole locations. The borehole placement problem is formulated as finding the borehole locations that minimize the standard deviation of the foundation bearing capacity. A stochastic optimization framework named Asymptotic Bayesian Optimization is implemented to handle the inherent variability of the standard deviation estimates. The applicability of the proposed approach is demonstrated based on a scenario involving a rectangular footing and two boreholes. The feasibility and effectiveness of the approach are promising for future applications, mostly for proposing optimal borehole placement for typical engineering practice foundation layouts.
KW - Asymptotic Bayesian Optimization
KW - bearing capacity
KW - optimal borehole placement
KW - Random Failure Mechanism Method
KW - spatial variability
UR - http://www.scopus.com/inward/record.url?scp=85202063710&partnerID=8YFLogxK
U2 - 10.3850/978-981-18-5184-1_MS-13-188-cd
DO - 10.3850/978-981-18-5184-1_MS-13-188-cd
M3 - Conference contribution
AN - SCOPUS:85202063710
SN - 9789811851841
SP - 447
EP - 453
BT - Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022
A2 - Beer, Michael
A2 - Zio, Enrico
A2 - Phoon, Kok-Kwang
A2 - Ayyub, Bilal M.
T2 - 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022
Y2 - 4 September 2022 through 7 September 2022
ER -