Tool Overview

This tool is designed for conducting reliability and risk analysis in engineering, safety assessments, and related fields. It provides a structured interface for defining variables, creating limit state functions, and selecting appropriate sampling methods, making it easier to assess the reliability of complex systems.

For full documentation, visit here.

1. Variables

Purpose: 

The Variables section allows users to define the key input parameters for the reliability analysis. Each variable is characterized by its statistical properties, which are essential for modeling uncertainty.

Fields:

• Variable Name: The identifier for the variable.
• Standard Deviation: The measure of the variability or dispersion of the variable.
• Mean: The expected value or average of the variable.
• Type of Distribution: The statistical distribution that the variable follows (e.g., Normal distribution).

2. Limit State Functions

Purpose:  

The Limit State Functions section is used to define the mathematical expressions that represent the boundary between the safe and failure states of the system. These functions are central to determining the reliability of the system under various conditions.

Fields:

• Equation: The mathematical expression that defines the limit state function.

3. Linear Correlations

Purpose:  

This section allows users to specify any linear correlations between the variables. This is crucial when the variables are not independent, ensuring that the analysis accurately reflects the relationships between different variables.

Functionality:  

Linear Correlations Checkbox: When checked, it activates the option to define correlations between variables.

4. Sampling Method

Purpose:

The Sampling Method section allows users to select the method for performing reliability analysis. Each method offers different levels of approximation and computational complexity.

Options:

• FORM (First Order Reliability Method): A commonly used approximation method in reliability analysis.
• FOSM (First Order Second Moment): Another approximation method focusing on the first two moments (mean and variance) of the distribution.
• Sampling: A general approach that involves Monte Carlo sampling techniques for more detailed and precise analysis.

Usage Instructions

1. Define Variables: Begin by entering all relevant variables, including their statistical properties and distribution types.
2. Create Limit State Functions: Input the necessary limit state functions to define the failure conditions of the system.
3. Specify Correlations (if any): If the variables are correlated, enable and define the linear correlations.
4. Select Sampling Method: Choose the appropriate sampling method based on the requirements and complexity of your analysis.
5. Run Analysis: Once all inputs are defined, proceed with the analysis to evaluate the reliability of your system.

This tool is designed to facilitate rigorous and systematic reliability analysis, providing users with the flexibility to model complex systems accurately and efficiently.