For computationally inexpensive limit state functions it can be feasible to tackle the structural reliability analysis with Monte Carlo simulation (MCS). To employ MCS in COMREL, you need to (i) set up a stochastic model, (ii) define a limit state function based on the random variables contained in the stochastic model and (iii) set
IMET to Crude Monte Carlo Sampling in the Computation Options Dialog. Thereafter, you can directly start the stochastic simulation by clicking on the menu button Run Reliability Analysis.
You can use our Online Tool for post-processing of MCS to quantify the uncertainty about the estimated probability of failure based on a conducted MCS.
When performing a MCS in COMREL, the options
IXLS from the Computation Options Dialog can be helpful. These options are discussed in the following.
The computation option
NSIMUL specifies the total number of samples to use in the MCS. The default value of 1000 is probably not large enough for a MCS. Thus, you might want to increase this value.
Through the computation option
SIMSTA a seed can be specified for the random number generator. Working with a fixed seed value might be helpful for debugging purposes, as each time you run the stochastic simulation, the same random numbers will be generated and the outcome of the analysis should therefore be the same. For productive simulation runs and in case you repeatedly initiate multiple simulation runs, you should not work with a fixed seed value.
To work with a randomized seed value in STRUREL, set
SIMSTA to Random.
The computation option
IXLS allows you to export the samples of the MCS to a file. By default, this option is set to No Samples, which means that the export is deactivated. To export the samples to a file, you have two options: (i) Just Samples in Failure Region (which will write only the samples for which the failure event occurred into the external file) and (ii) All Samples (which will write all samples used in the MCS to the external file). The computation option
IXLS can be helpful if you intend to apply your own post-processing routines to the generated Monte Carlo samples. The generated export file has the same name as your iti-file, fill ending .csv and contains the sample coordinates as well as the associated value of the limit state function.