scholarly journals HIRESSS: a physically based slope stability simulator for HPC applications

2013 ◽  
Vol 13 (1) ◽  
pp. 151-166 ◽  
Author(s):  
G. Rossi ◽  
F. Catani ◽  
L. Leoni ◽  
S. Segoni ◽  
V. Tofani
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Slope Stability ◽  
Real Time ◽  
Unsaturated Soil ◽  
Hydrological Model ◽  
Pressure Head ◽  
Stability Model ◽  
Physically Based ◽  
Geotechnical Stability

Abstract. HIRESSS (HIgh REsolution Slope Stability Simulator) is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and on large areas using parallel computational techniques. The physical model proposed is composed of two parts: hydrological and geotechnical. The hydrological model receives the rainfall data as dynamical input and provides the pressure head as perturbation to the geotechnical stability model that computes the factor of safety (FS) in probabilistic terms. The hydrological model is based on an analytical solution of an approximated form of the Richards equation under the wet condition hypothesis and it is introduced as a modeled form of hydraulic diffusivity to improve the hydrological response. The geotechnical stability model is based on an infinite slope model that takes into account the unsaturated soil condition. During the slope stability analysis the proposed model takes into account the increase in strength and cohesion due to matric suction in unsaturated soil, where the pressure head is negative. Moreover, the soil mass variation on partially saturated soil caused by water infiltration is modeled. The model is then inserted into a Monte Carlo simulation, to manage the typical uncertainty in the values of the input geotechnical and hydrological parameters, which is a common weak point of deterministic models. The Monte Carlo simulation manages a probability distribution of input parameters providing results in terms of slope failure probability. The developed software uses the computational power offered by multicore and multiprocessor hardware, from modern workstations to supercomputing facilities (HPC), to achieve the simulation in reasonable runtimes, compatible with civil protection real time monitoring. A first test of HIRESSS in three different areas is presented to evaluate the reliability of the results and the runtime performance on large areas.

scholarly journals Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach

2014 ◽  
Vol 18 (12) ◽  
pp. 4913-4931 ◽  
Author(s):  
D. J. Peres ◽  
A. Cancelliere
Keyword(s):  
Monte Carlo ◽  
Slope Stability ◽  
Power Law ◽  
Rainfall Intensity ◽  
Antecedent Rainfall ◽  
Rainfall Events ◽  
Physically Based ◽  
Power Law Equation ◽  
Triggering Rainfall ◽  
Landslide Triggering

Abstract. Assessment of landslide-triggering rainfall thresholds is useful for early warning in prone areas. In this paper, it is shown how stochastic rainfall models and hydrological and slope stability physically based models can be advantageously combined in a Monte Carlo simulation framework to generate virtually unlimited-length synthetic rainfall and related slope stability factor of safety data, exploiting the information contained in observed rainfall records and field-measurements of soil hydraulic and geotechnical parameters. The synthetic data set, dichotomized in triggering and non-triggering rainfall events, is analyzed by receiver operating characteristics (ROC) analysis to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. Moreover, the specific modeling framework implemented in this work, based on hourly analysis, enables one to analyze the uncertainty related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall). A specific focus is dedicated to the widely used power-law rainfall intensity–duration (I–D) thresholds. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. Remarkably, when a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a I–D power-law equation, while a representation of rainfall as constant–intensity hyetographs globally leads to non-conservative results. This indicates that the I–D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and thus gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part. These conditions are more likely to occur in hillslopes of low specific upslope contributing area, relatively high hydraulic conductivity and high critical wetness ratio. Otherwise, rainfall time history occurring before single rainfall events influences landslide triggering, determining whether a threshold based only on rainfall intensity and duration may be sufficient or it needs to be improved by the introduction of antecedent rainfall variables. Further analyses show that predictability of landslides decreases with soil depth, critical wetness ratio and the increase of vertical basal drainage (leakage) that occurs in the presence of a fractured bedrock.

scholarly journals Analysis of the Bearing Capacity of Shallow Foundation in Unsaturated Soil Using Monte Carlo Simulation

2017 ◽  
Vol 08 (10) ◽  
pp. 1231-1250 ◽  
Author(s):  
Nadarajah Ravichandran ◽  
Vahidreza Mahmoudabadi ◽  
Shweta Shrestha
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Bearing Capacity ◽  
Unsaturated Soil ◽  
Shallow Foundation

Theoretical Line Loss Calculation of Distribution Network Considering Wind Turbine Power Constraint

2014 ◽  
Vol 986-987 ◽  
pp. 630-634 ◽  
Author(s):  
Ke Li ◽  
Zhen Quan Sun ◽  
Meng Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Wind Turbine ◽  
Real Time ◽  
Power Flow ◽  
Time Measurement ◽  
Power Constraint ◽  
Real Time Measurement ◽  
Theoretical Line ◽  
Line Loss

This paper presents a theoretical line loss calculation of distribution network containing an uncertainty power of wind turbine. First, this paper establishes the theoretical line loss mathematical model considering wind turbine power constraint within the sampling period. Then this paper gets multi group wind turbine output data satisfied the power constraints through Monte Carlo simulation. By combining with the first power coefficient method and Monte Carlo simulation technique, this paper also generates multi groups load pseudo measurement test of non real time. By combining the real-time measurement of power flow calculation, a group of simulated data with minimum error between the power flow results and the real time measurement are selected. Finally based on the selected pseudo measurement, the theoretical line loss within the given time period based on periodic accumulative calculation of real-time measurement are calculated. 14 nodes example is given to verify the accuracy and practicality of the algorithm.

scholarly journals Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model

2019 ◽  
Author(s):  
Johnnatan Palacio Cordoba ◽  
Martin Mergili ◽  
Edier Aristizábal
Keyword(s):  
Slope Stability ◽  
Landslide Susceptibility ◽  
Confusion Matrix ◽  
Hazard Mapping ◽  
Infinite Slope ◽  
Susceptibility Analysis ◽  
Colombian Andes ◽  
Infinite Slope Stability Model ◽  
Stability Model ◽  
Physically Based

Abstract. Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes, one of the regions most affected by landslides every year. Currently in Colombia, physically based methods for landslide hazard mapping are mandatory for land use planning in urban areas. In this work, we perform probabilistic analyses with r.slope.stability, a spatially distributed, physically based model for landslide susceptibility analysis, available as an open-source tool coupled to GRASS GIS. This model considers alternatively the infinite slope stability model or the 2.5D geometry of shallow planar and deep-seated landslides with ellipsoidal or truncated failure surfaces. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment. Finally, the model results are evaluated against a landslide inventory using a confusion matrix and Receiver Operating Characteristic (ROC) analysis. The model performs reasonably well, the infinite slope stability model showing a better performance. The outcomes are, however, rather conservative, pointing to possible challenges with regard to the geotechnical and geo-hydraulic parameterization. The results also highlight the importance to perform probabilistic instead of – or in addition to – deterministic slope stability analyses.

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