English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the optimization of turbomachinery components, shape sensitivities forfluid dynamical objective functions have been used for a long time. As peakstress is not a differential func- tional of the shape, such highly efficientprocedures so far have been missing for objective functionals that stem frommechan- ical integrity. This changes, if deterministic lifing criteria arereplaced by probabilistic criteria, which have been introduced recently to thefield of low cycle fatigue (LCF). Here we present a finite element (FEA) basedfirst discretize, then adjoin approach to the calculation of shape gradients(sen- sitivities) for the failure probability with regard to probabilistic LCFand apply it to simple and complex geometries, as e.g. a blisk geometry. Wereview the computation of failure probabilities with a FEA postprocessor andsketch the computation of the relevant quantities for the adjoint method. Wedemonstrate high accuracy and computational efficiency of the adjoint methodcompared to finite difference schemes. We discuss implementation details forrotating components with cyclic boundary conditions. Finally, we shortlycomment on future development steps and on poten- tial applications in multicriteria optimization.

Adjoint Method to Calculate Shape Gradients of Failure Probabilaties for Turbomachinery Components