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Simulate: Monte Carlo Simulation with Importance Sampling

Run Monte Carlo simulation with optional importance sampling for rare-event failure probability estimation. Optionally include FORM and SORM analysis alongside the simulation for comparative results.

Before your first run

If you want to test this command with packaged sample problems, first run: 

brinkpy examples copy
Then select a problem file from ./problems/ when the file picker opens.

Basic Usage

Usage: brinkpy simulate <profile> [OPTIONS]

Command Options

Monte Carlo Options

  • --mc-with-is, -i: Use importance sampling with Monte Carlo simulation

Reliability Methods

  • --include-form, -f: Include first-order reliability method (FORM) analysis
  • --include-sorm, -s: Include second-order reliability method (SORM) analysis (automatically enables FORM)

Plotting Options

  • --plot-lsf, -l: Generate limit state function plot
  • --plot-pdfs, -p: Generate probability density function plots

General Options

  • --open-results, -o: Open result files after completion — including the Excel report, the PDF report, and any Matplotlib figures saved as pickle files

Examples

Basic Monte Carlo Simulation

brinkpy simulate default

MC with Importance Sampling

brinkpy simulate default --mc-with-is

MC with FORM/SORM and Plots

brinkpy simulate default -f -s -l -p

Complete Simulation with IS

brinkpy simulate default -i -s -p

Using Custom Profile

brinkpy simulate myprofile --include-form --plot-pdfs

Combining short flags

Short flags can be merged into a single argument. For example: 

brinkpy simulate default -f -s -l -p
is equivalent to: 
brinkpy simulate default -fslp
Both forms are valid. The expanded form is easier to read; the combined form is faster to type.

Notes

  • If --include-sorm is specified without --include-form, FORM is automatically enabled
  • If importance sampling method is set to mpp_normal in the profile, FORM is automatically enabled
  • Monte Carlo sample size is configured in the profile file

Aliases

  • sim: Short alias