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ANSYS optiSLang - The optimal combination of parametric modeling and Robust Design Optimization (RDO)

Understand your design!

optiSLang inside ANSYS allows a systematic parametric variation study of all relevant independent variables and thus offers a comprehensive understanding of the physical relationships of all parameters. The resulting sensitivities accelerate optimization and support reliability, Design for Six Sigma, and the comparison between simulation and test.

Among the typical application scenarios, in addition to product improvement, is the determination of parameters for numerical models such as material, friction, or damping, and cost-effective Including Variations in the Game characteristic diagrams for non-linear components. The universal application, for both simple and complex tasks, the high-quality algorithms, and quick turnaround efficiency, all coupled with robust operation make optiSLang inside ANSYS a valuable tool for development engineers.

Technical Informations

  • PC-System up to Windows XP SP2
    (32- and 64-Bit-Systems)
  • ANSYS Workbench up to version 13

optiSLang and ANSYS

The consistent working process within ANSYS Workbench, geared towards parameter studies, is an excellent basis for parametric variation studies and optimization with optiSLang. Its integration into ANSYS Workbench allows optiSLang to combine user-friendliness with high-performance methods.

This facilitates not only a quick introduction, but also an advanced range of tasks with numerous parameters, including difficult non-linearity, or multidisciplinary, multi-objective optimization.

Parametric Sensitivity Analyses

Which independent variables are relevant? How strong is the correlation between parameters? What output range can my design cover?

Parametric sensitivity analyses help to differentiate important parameters from unimportant ones, to understand the relationships between design variables and results, and to define the target domain for an achievable, high-performance design. Automated statistical design of experiments (DoE) ensures a good balance of performance and accuracy for the execution of the sensitivity study: The prognosis quality of the established relationships is quantified (coefficient of prognosis), allowing the observed design space to be recorded at the defined level of accuracy with a minimum number of analyses. The representation of results in optiSLang eases the evaluation of a large number of parameters.


Multidisciplinary optimization

Which design is the best? How are competing goals to be dealt with?

Based on the relationships from the sensitivity analysis, the design can be optimized. This optimization simultaneously takes into account multiple physical disciplines and goals.

For an electrical motor, for instance, that would be efficiency based on the magnetic field generation and the structural dynamic vibrations based on the magnetic forces and resulting sound pressure level.

The optimization methods available in optiSLang inside ANSYS are automatically pre-defined based on the problem, and the user can easily grasp them using a traffic-light rating system. Optimization methods are available for both special requirements and classic optimization tasks.


Tolerance analysis

How do variances affect product behavior? How will my product work under real operating conditions?

Variances in manufacturing processes, stresses, geometries, and material properties all produce variances in component behavior. Numerical tolerance analyses allow testing of compliance with product characteristics even in such situations. This technology, established for assessing geometrical properties, is increasingly used for physical properties as well. Simulation using virtual prototypes is a cost-effective option for analyzing the robustness of a design and verifying the safety of a product under actual operating conditions.


Your start in the world of simulation

Your start in the world of simulation

  • Introduce simulation safely
  • 4 steps to be operational
  • Accompaniment throughout the process


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