Abstract
Skempton and Brown (1961) presented a well-documented landslide case study involving a heavily
overconsolidated boulder clay deposit in Selset, Yorkshire, UK. While the laboratory testing program revealed significant
inherent variability in soil parameters, their analyses were limited to deterministic approaches. This study revisits their work
within the framework of probabilistic analysis. We employed Monte Carlo Simulations (MCS) alongside Random Field
Finite Element Limit Analysis (RF-FELA), which explicitly accounts for spatial variability. Additionally, we conducted
MCS using a closed-form solution, implicitly neglecting spatial variability, i.e., assuming a scale of fluctuation tending
towards infinity. Our analysis revealed that neglecting spatial variability can lead to an overestimation of the probability of
failure. Nevertheless, MCS with the closed-form solution substantially reduces the computational time required by RF-FELA
from hours (or even days) to minutes, making it an efficient tool for preliminary probabilistic analysis. The case study also
demonstrate that probabilistic slope stability analysis provides more profound insights, offers a more transparent means of
quantifying slope risk, and better captures the rapid increase in risk as the verge of failure is approached.
overconsolidated boulder clay deposit in Selset, Yorkshire, UK. While the laboratory testing program revealed significant
inherent variability in soil parameters, their analyses were limited to deterministic approaches. This study revisits their work
within the framework of probabilistic analysis. We employed Monte Carlo Simulations (MCS) alongside Random Field
Finite Element Limit Analysis (RF-FELA), which explicitly accounts for spatial variability. Additionally, we conducted
MCS using a closed-form solution, implicitly neglecting spatial variability, i.e., assuming a scale of fluctuation tending
towards infinity. Our analysis revealed that neglecting spatial variability can lead to an overestimation of the probability of
failure. Nevertheless, MCS with the closed-form solution substantially reduces the computational time required by RF-FELA
from hours (or even days) to minutes, making it an efficient tool for preliminary probabilistic analysis. The case study also
demonstrate that probabilistic slope stability analysis provides more profound insights, offers a more transparent means of
quantifying slope risk, and better captures the rapid increase in risk as the verge of failure is approached.
| Original language | English |
|---|---|
| Title of host publication | Geotechnical Engineering Challenges to Meet Current and Emerging Needs of Society |
| Editors | Nuno Guerra, Manuel Matos Fernandes, Cristiana Ferreira, António Gomes Correia, Alexandre Pinto, Pedro Sêco Pinto |
| Publisher | CRC Press |
| Pages | 1659-1664 |
| Number of pages | 6 |
| Edition | 1 |
| ISBN (Electronic) | 9781003431749 |
| DOIs | |
| Publication status | Published - 17 Sept 2024 |
| Event | XVIII European Conference on Soil Mechanics and Geotechnical Engineering: CHALLENGES OF GEOTECHNICAL ENGINEERING TO MEET CURRENT AND EMERGING SOCIETY NEEDS. - MEO Arena, Lisbon, Portugal Duration: 26 Aug 2024 → 30 Aug 2024 https://www.ecsmge-2024.com/ |
Conference
| Conference | XVIII European Conference on Soil Mechanics and Geotechnical Engineering |
|---|---|
| Abbreviated title | ECSMGE24 |
| Country/Territory | Portugal |
| City | Lisbon |
| Period | 26/08/24 → 30/08/24 |
| Internet address |