Skip to content

Analyze: Forward Reliability Assessment

Run forward reliability analysis using the First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), and Monte Carlo simulation to estimate failure probability, reliability index (β), and most probable point (MPP).

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 analyze <profile> [OPTIONS]

Command Options

Reliability Methods

  • --include-sorm, -s: Include second-order reliability method (SORM) analysis

Monte Carlo Options

  • --include-mc, -m: Include Monte Carlo simulation
  • --mc-with-is, -i: Use importance sampling with Monte Carlo (automatically enables --include-mc)

Plotting Options

  • --plot-rfad, -r: Generate reliability-based failure assessment diagram plots
  • --plot-lsf, -l: Generate limit state function plots
  • --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 FORM Analysis

brinkpy analyze default

FORM + SORM with Plots

brinkpy analyze default --include-sorm --plot-rfad --plot-lsf

Complete Analysis with MC

brinkpy analyze default -s -m -i -r -l -p

Using Custom Profile

brinkpy analyze myprofile --include-sorm --plot-rfad

Combining short flags

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

brinkpy analyze default -s -m -i -r -l -p
is equivalent to: 
brinkpy analyze default -smirlp
Both forms are valid. The expanded form is easier to read; the combined form is faster to type.

Aliases

  • analyse: British spelling variant
  • an: Short alias