Expand/Collapse all
1. Introduction
1.1. optiSLang Documentation Set
2. Sensitivity Analysis
2.1. Scanning the Space of Input Variables
2.2. Variance Based Sensititvity Analysis
2.2.1. First Order and Total Effect Sensitivity Indices
2.2.2. Coefficient of Correlation
2.3. Polynomial Based Sensitivity Analysis
2.3.1. Polynomial Regression
2.3.2. Coefficient of Determination
2.3.3. Coefficient of Importance
2.4. Metamodel of Optimal Prognosis
2.4.1. Moving Least Squares Approximation
2.4.2. Coefficient of Prognosis
2.4.3. Metamodel of Optimal Prognosis
2.5. Comparision With Other Approximation and Selection Methods
3. Multidisciplinary Optimization
3.1. Single-Objective Optimization
3.1.1. Gradient-Based Methods
3.1.2. Response Surface Based Methods
3.1.3. Population Based Methods
3.2. Multi-Objective Optimization
3.2.1. Pareto Optimization
3.3. One-Click Optimization
4. Robust Design
4.1. Definition of Uncertainties
4.1.1. Scalar Random Variables
4.1.2. Multivariate Distributions
4.2. Variance-Based Robustness Analysis
4.3. Robust Design Optimization
5. Reliability Analysis
5.1. Definition of the Reliability Problem
5.2. Standardization and Generation of Random Numbers
5.3. First Order Reliability Method (FORM)
5.4. Monte Carlo Simulation
5.5. Importance Sampling
5.5.1. Adaptive Sampling (ADSAP)
5.5.2. Importance Sampling Using the Design Point (ISPUD)
5.6. Directional Sampling (DS)
5.7. Adaptive Response Surface Method (ARSM-DS) for Reliability Analysis
5.8. Recommendations for Robustness Wizard
A. DOE Schemes
B. Random Variables
B.1. Statistical Moments and Process Capability
B.2. Distribution Types
References