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Landslide Analysis Subject to Geological Uncertainty Using Monte Carlo Simulation (A Study Case in Taiwan)
Landslide is the primary driver of the denudational process and sediment source dominantly onsite. Landslides are one of the most disastrous effects in Taiwan; groundwater or flood erosion is highly attributed to the landslide. Water induced to the slope increases driving force and decrease resisting force causing a slope landslide. This condition is generally affecting slope stability. In this study, we attempt to consider the uncertainty of the dip angle in slope stability analysis. In this research, the Monte Carlo simulation was used to quantify the effect of the geological uncertainty. Various sources of dip angles (with mean and standard deviation) were employed to generate 100,000 dip angle samples. All of the dip angles employed in this study were based on Highway no. 3 sliding events in Taiwan. Four different measurement sources, i.e., Central Geological Survey (CGS, Taiwan), Compass measurement before the sliding event, Surface measurement after the event, and LiDAR-derived data, were employed in this study. Further, the measured dip angles were converted to the projected dip angle based on the plane's strike. Simulation results show LiDAR Measurement Source provides the lowest failure probability of 16.9%, and Central Geological Survey (CGS, Taiwan) Measurement provides the highest failure probability of 78%. Therefore, based on the engineering design concept, if the design performed using the CGS data, the engineering design must be very conservative compared to the design using the LiDAR data.
Landslide Analysis Subject to Geological Uncertainty Using Monte Carlo Simulation (A Study Case in Taiwan)
Landslide is the primary driver of the denudational process and sediment source dominantly onsite. Landslides are one of the most disastrous effects in Taiwan; groundwater or flood erosion is highly attributed to the landslide. Water induced to the slope increases driving force and decrease resisting force causing a slope landslide. This condition is generally affecting slope stability. In this study, we attempt to consider the uncertainty of the dip angle in slope stability analysis. In this research, the Monte Carlo simulation was used to quantify the effect of the geological uncertainty. Various sources of dip angles (with mean and standard deviation) were employed to generate 100,000 dip angle samples. All of the dip angles employed in this study were based on Highway no. 3 sliding events in Taiwan. Four different measurement sources, i.e., Central Geological Survey (CGS, Taiwan), Compass measurement before the sliding event, Surface measurement after the event, and LiDAR-derived data, were employed in this study. Further, the measured dip angles were converted to the projected dip angle based on the plane's strike. Simulation results show LiDAR Measurement Source provides the lowest failure probability of 16.9%, and Central Geological Survey (CGS, Taiwan) Measurement provides the highest failure probability of 78%. Therefore, based on the engineering design concept, if the design performed using the CGS data, the engineering design must be very conservative compared to the design using the LiDAR data.
Landslide Analysis Subject to Geological Uncertainty Using Monte Carlo Simulation (A Study Case in Taiwan)
Lecture Notes in Civil Engineering
Kristiawan, Stefanus Adi (editor) / Gan, Buntara S. (editor) / Shahin, Mohamed (editor) / Sharma, Akanshu (editor) / Fitra, Joni (author) / Huang, Wen-Chao (author) / Purwana, Yusep Muslih (author)
International Conference on Rehabilitation and Maintenance in Civil Engineering ; 2021 ; Surakarta, Indonesia
2022-07-19
11 pages
Article/Chapter (Book)
Electronic Resource
English
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