MC_IS: MonteCarlo Simulation with importance sampling

In TesiproV: Calculation of Reliability and Failure Probability in Civil Engineering

MonteCarlo Simulation with importance sampling

Description

Method to calculate failure probability for structural engineering using a simulation method with importance sampling (a method to reduce the amount of needed samples)

Usage

MC_IS(
  lsf,
  lDistr,
  cov_user = 0.05,
  n_batch = 16,
  n_max = 1e+06,
  use_threads = 6,
  sys_type = "parallel",
  dataRecord = TRUE,
  beta_l = 100,
  densityType = "norm",
  dps = NULL,
  debug.level = 0
)

Arguments

lsf	objective function with limit state function in form of function(x) x[1]+x[2]...
lDistr	Distributions in input space
cov_user	The Coefficent of variation the simulation should reach
n_batch	Size per batch for parallel computing
n_max	maximum of iteration the MC should do - its like a stop criterion
use_threads	determine how many threads to split the work (1=singlecore, 2^n = multicore)
sys_type	Determine if parallel or serial system (in case MCIS calculates a system)
dataRecord	If True all single steps are recorded and available in the results file afteron
beta_l	In Systemcalculation: LSF´s with beta higher than beta_l wont be considered
densityType	determines what distributiontype should be taken for the h() density
dps	Vector of design points that sould be taken instead of the result of a FORM analysis
debug.level	If 0 no additional info if 2 high output during calculation

Value

The results will be provided within a list with the following objects. Acess them with "$"-accessor

pf probablity of failure

pf_FORM probablity of failure of the FORM Algorithm

var variation

cov_mc coefficent of the monteCarlo

n_mc number of iterations done

Author(s)

(C) 2021 - K. Nille-Hauf, T. Feiri, M. Ricker - Hochschule Biberach, Institut fuer Konstruktiven Ingenieurbau

References

DITLEVSEN O, MADSEN H. Structural reliability methods, vol. 178. New York: Wiley; 1996.

Spaethe, G.: Die Sicherheit tragender Baukonstruktionen, 2. Aufl. Wien: Springer, 1991. – ISBN 3-211-82348-4

TesiproV documentation built on March 26, 2022, 1:11 a.m.