0. Example 4
This example has a linear limit state function in physical space as Eq. (1) [1,2].
Table 1 shows correlation matrix, the number and statistical moment of random variables for this example.
The probability density function for random variables is in accordance with Eq. (2) to Eq. (4).
1. Steps to prepare this example in BI (before analysis):
1.1 Generate Random Variable object: Define > Variable > RandomVariable
1.2 Generate Correlation Coefficient object: Define > Correlation
1.3 Generate Limit State Function object: Define > Limit State Function
2. Prepare for FORM Analysis
2.1 Generate Nataf Transformation object: Analysis > Transformer
2.2 Generate Convergence Checker object: Analysis > Convergence Checker
2.3 Generate Step Direction Searcher object: Analysis > Step Direction Searcher
2.4 Generate Merit Checker object: Analysis > Merit Checker
2.5 Generate Step Size Searcher object: Analysis > Step Size Searcher
In this part, you need to insert name of previous object, which is created in step 2.4.
2.6 Generate Solver object: Analysis > Solver
In this part, you need to insert names of previous objects, which are created in steps 2.1, 2.2, 2.3, and 2.5.
2.7 Generate Output object: Analysis > Output
2.8 Generate FORM Analysis object: Analysis > FORM Analysis
2.9 Run this FORM Analysis object.
2.10 Show Plot result:
2.11 Show text result:
3. Prepare for FOTM Analysis
3.1 Use Solver object in FORM Analysis. Step 2.5 show this object.
3.2 Generate Output object: Analysis > Output
3.3 Generate FOTM Analysis object: Analysis > FOTM Analysis
3.4 Run this FOTM Analysis object.
3.5 Show Plot result:
3.6 Show text result:
4. Prepare for Sampling Analysis
4.1 Use Nataf Transformer object in FORM Analysis. Step 2.1 show this object.
4.2 Generate Random Number Generator object: Analysis > Random Number Gen
4.3 Generate Accumulator (Failure Probability) object: Analysis > Accumulator
4.4 Generate Output object: Analysis > Output
4.5 Generate Sampling Analysis object: Analysis > Sampling Analysis
4.6 First Run Form Analysis, then run this Sampling Analysis object. (For fast convergence)
4.7 Show Plot result:
4.8 Show text result:
5. Prepare for Optimization Analysis
5.1 Generate Output object: Analysis > Output
5.2 Generate Optimization Analysis object: Analysis > Optimization
5.3 Run this Optimization object.
5.4 Show Plot and Text result of each method:
 Lu Z-H, Cai C-H, Zhao Y-G. Structural Reliability Analysis Including Correlated Random Variables Based on Third-Moment Transformation. J Struct Eng 2017;143:04017067. https://doi.org/10.1061/(asce)st.1943-541x.0001801.
 Fan W, Wei J, Ang AH-S, Li Z. Adaptive estimation of statistical moments of the responses of random systems. Probabilistic Eng Mech 2016;43:50–67. https://doi.org/10.1016/j.probengmech.2015.10.005.