Stochastic Analysis

Direct Monte Carlo Investigations

• Estimation of Mean, Std. Deviation
• Correlation Analysis
• Confidence Intervals
• Outlier Analysis

Distribution Functions

• Normal, Uniform, Lognormal, Weibull, Beta, Binomial
• User-Defined

Reliability studies

• Determination of failure probability
• Methods: FOSM, FORM

Improvement of numerical efficiency using meta models

• Meta-Model based Monte Carlo Simulations
• Stochastic contribution analysis
• Polynomial response surfaces (linear, quadratic)
• Feed Forward Neural Networks, Radial Basis Function (RBF)

Visualization of statistical results on the FE-Model (DYNAstats)

• Fringe of mean and standard deviation on the FE-model utilizing LS-PrePost
• Display of variation of element results such as stress, thinning, plastic strain...
• Correlation of node displacements with respect to any response
• Statistics of time history curves