File Size: 612 MB

optiSLang automatically identifies the relevant input and output parameters and quantifies the forecast quality with the help of the Coefficient of Prognosis ( CoP) and the Metamodel of Optimal Prognosis (MOP). A predictable prognosis quality is the key to an efficient optimization. Thus, a "no run too much" philosophy can be implemented to minimize solver calls. As a consequence, even optimization tasks involving a large number of variables, scattering parameter as well as non-linear system behavior can be solved.

optiSLang's Best-Practice-Management automatically selects the appropriate algorithms, such as gradient methods, genetic algorithms, evolutionary strategies or Adaptive Response Surface Methods. Furthermore, all methods of optimization and stochastic analysis can be combined in regard to the particular task. optiSLang makes you ready to meet the full range of parametric studies to innovate and accelerate your virtual product development.

optiSLang offers efficient methods of Robust Design optimization for solving your tasks in the CAE-field.
Sensitivity analysis
Multidisciplinary optimization
Parameter identification
Robustness evaluation
Reliability analysis
Robust Design Optimization
Random fields

Simulation processes from different solvers (ANSYS, MATLAB, Excel, Python ...) or pre and post processors can be adapted via a graphic editors and ASCII files making them accessible for parametric sensitivity analysis, optimization or stochastic analysis.

General Features:
Compact overview sensitivity analysis
comprehensive systems
minimal effort for set up
easy process integration
state-of-the-art algorithms
targeted, individual definitions of performance limits
fast parameterization
easy definition of constraints and objectives

Whats New
Kod:
https://www.dynardo.de/en/software/optislang/changelog-ansys-optislang.html
HOMEPAGE
Kod:
https://www.dynardo.de/


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