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Robustness Analysis

Stochastic methods and features for robustness analysis are implemented in LS-OPT.

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Monte Carlo Investigations

  • Direct and metamodel based
  • Estimation of Mean, Std. Deviation
  • Correlation Analysis
  • Confidence Intervals
  • Outlier Analysis
  • Stochastic contribution analysis

Reliability studies

  • Determination of failure probability
  • Methods: FOSM, FORM

Reliability Based Design Optimization

  • Optimization that directly accounts for the variability and the probability of failure

Robust Design Optimization

  • Optimizing design and robustness simultanously

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
 
Examples:
 

 

 

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