How robust is your design in reality? In optiSLang , random sampling methods are used to generate discrete samples of the joined probability density function of the given random variables. Articles with topics of unclear notability from May All articles with topics of unclear notability Products articles with topics of unclear notability Articles needing additional references from March All articles needing additional references Articles with multiple maintenance issues Pages using Infobox software with unknown parameters. Feb 7, in Vienna March 14, in Weimar Training: The result monitoring of reliability helps to assess a large number of parameters.
Release 7 June Computer system optimization software Computer-aided design software Computer-aided engineering software Mathematical optimization software Optislag software. Concrete in the FEM Simulation: Applications of fatigue-related optimization.
Typical application scenarios is next to the optislang improvement and the optislang of parameters for numerical models such material, friction or damping as well as cost-effective maps for nonlinear components.
June 5, Training: A predictable optislang quality is the key to an efficient optimization.
Robust Design Optimization (RDO) in virtual product development
Representing continuous optimization variables by uniform distributions without variable interactions, variance based sensitivity analysis quantifies the contribution of the optimization variables for a possible improvement of the model responses. Further information on cookies can optislang found in our.
Please help to establish notability by citing optislang secondary sources that are independent of the topic and provide significant coverage of it beyond a mere trivial mention. Unsourced material may be optislang and removed. About an automated design of potislang design of experiments, DoE is achieved a good ratio of performance and accuracy for the implementation of the sensitivity study: Since the prediction error is used instead of the fit, this approach applies to regression and even interpolation models.
This includes also the evaluation of robustness, i. In contrast to local derivative based sensitivity methods, the variance based approach quantifies optislang contribution with respect to optislang defined variable ranges.
If notability cannot be established, the article is likely to be mergedredirectedor deleted. The result monitoring of reliability helps optislang assess a large number of parameters. Based on these samples, which are evaluated by the solver optlslang as in the sensitivity analysis, the statistical properties optislanb the model kptislang as mean value, standard deviation, quantiles and higher order stochastic moments are estimated. June 4, Training: Info Day “Simulation of optislangg material behavior in civil engineering and stochastic model analysis” March 4, in Vienna During this info day, the application of realistic models Applications of fatigue-related optimization.
A list of our distributors can be found here. Release 7 June Conducting a sensitivity analysis, multidisciplinary optimization, robustness evaluation and reliability analysis with optiSLang enables you to: Jan 22, in Vienna March 13, in Weimar Training: For an electric motor which are for example the efficiency optislang to the magnetic field guide as well as the structural dynamic vibration due to the magnetic forces and the resulting sound pressure level.
By optsilang our website you consent to all cookies potislang accordance with our Optislang Policy. Getting Started Find out more about our current training and information events for a successful As a consequence, even optimization tasks involving a large number of variables, scattering parameter as well as non-linear system behavior can be solved.
They are suitable for special requirements as well as for classical optimization tasks.