Sensitivity Analysis

By means of a global sensitivity analysis and the automatic generation of the Metamodel of Optimal Prognosis (MOP), optimization potential and the corresponding important variables are identified. With this previous knowledge, task-related objective functions and constraints can be defined as well as suitable algorithms can be selected.

Multidisciplinary Optimization

optiSLang provides powerful optimization algorithms and automated workflows for an efficient determination of optimal design parameters regarding various multidisciplinary, nonlinear and multicriteria optimization tasks.

Robustness Evaluation

optiSLang quantifies the robustness of designs by generating a set of possible design realizations on the basis of scattering input variables. Optimized Latin Hypercube Sampling and the quantification of the prognosis quality of the result variation by the Coefficient of Prognosis (CoP) ensure the reliability of the variation and correlation values with a minimum of design calculations.



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