scholarly journals Subset simulation and line sampling for advanced Monte Carlo reliability analysis

2009 ◽  
pp. 721-728
Keyword(s):  
Monte Carlo ◽  
Reliability Analysis ◽  
Subset Simulation ◽  
Line Sampling

scholarly journals Impact probability computation of near-Earth objects using Monte Carlo line sampling and subset simulation

2020 ◽  
Vol 132 (8) ◽  
Author(s):  
Matteo Romano ◽  
Matteo Losacco ◽  
Camilla Colombo ◽  
Pierluigi Di Lizia
Keyword(s):  
Monte Carlo ◽  
Accurate Estimate ◽  
Test Cases ◽  
Subset Simulation ◽  
Asteroid Impact ◽  
Line Sampling ◽  
Impact Risk ◽  
The Impact ◽  
Initial Uncertainty ◽  
Near Earth Objects

Abstract This work introduces two Monte Carlo (MC)-based sampling methods, known as line sampling and subset simulation, to improve the performance of standard MC analyses in the context of asteroid impact risk assessment. Both techniques sample the initial uncertainty region in different ways, with the result of either providing a more accurate estimate of the impact probability or reducing the number of required samples during the simulation with respect to standard MC techniques. The two methods are first described and then applied to some test cases, providing evidence of the increased accuracy or the reduced computational burden with respect to a standard MC simulation. Finally, a sensitivity analysis is carried out to show how parameter setting affects the accuracy of the results and the numerical efficiency of the two methods.

Reliability Analysis of Embankment Slope in Yaan-Luku Expressway

2011 ◽  
Vol 71-78 ◽  
pp. 1360-1365
Author(s):  
Jian Quan Ma ◽  
Guang Jie Li ◽  
Shi Bo Li ◽  
Pei Hua Xu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Latin Hypercube Sampling ◽  
Natural State ◽  
State Function ◽  
Embankment Slope ◽  
The Times ◽  
Distribution Type

Take a typical cross-section of rockfill embankment slope in Yaan-Luku highway as the research object, reliability analysis is studied under the condition of water table of 840.85m, 851.50m, and loading condition of natural state and horizontal seismic acceleration of 0.2g, respectively. Raw data use Kolmogorov-Smirnov test (K-S test) to determine the distribution type of parametric variation. And the parameters were sampling with Latin hypercube sampling (LHS) method and Monte Carlo (MC) method, respectively, to obtain state function and determine safety factors and reliability indexes. A conclusion is drawn that the times of simulation based on LHS method were less than Monte Carlo method. Also the convergence of failure probability is better than the Monte Carlo method. The safety factor is greater than one and the failure probability has reached to 35.45% in condition of earthquake, which indicating that the instability of rockfill embankment slope is still possible.

Parameter Study on Subset Simulation for Reliability Assessment

2017 ◽  
Vol 1144 ◽  
pp. 128-135
Author(s):  
Adéla Hlobilová ◽  
Matěj Lepš
Keyword(s):  
Monte Carlo ◽  
Reliability Assessment ◽  
Latin Hypercube Sampling ◽  
Structural Safety ◽  
Parameter Study ◽  
Subset Simulation ◽  
Mathematical Functions ◽  
New Techniques ◽  
Failure Event ◽  
Truss Bridge

Small probability of failure characterizes a good structural design. Prediction of such a structural safety is time consuming considering that sampling methods such as Monte Carlo method or Latin Hypercube sampling are used. Therefore, more specialized methods are developed. A Subset simulation is one of the new techniques based on modifying the failure event as an intersection of nested intermediate events that are easier to solve. This paper deals with a parameter study of the Subset simulation with modified Metropolis algorithm for Markov chain Monte Carlo using distinct proposal distributions. Different setting is then compared on reliability assessment benchmarks, namely on two mathematical functions with different failure probabilities and on a 23-bar planar truss bridge.

Sign in / Sign up

Export Citation Format

Share Document