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Three Dimensional Shape Optimization with Probabilistic Constraints using Parametric Session Files

Probabilistic analysis is rapidly developing into a desirable tool to improve design processes. Incorporating probabilistics with optimization of three dimensional components is a step towards improving many current deterministic design systems. This paper develops a general purpose method using MSC/PATRAN and MSC/NASTRAN for three dimensional shape optimization that incorporates probabilistic calculations. A parametric finite element model calculates design point responses and semi-analytic geometry sensitivities. The Advanced Mean Value First Order Second Moment Method is used for reliability calculations while sensitivities to the probability constraints are calculated analytically. Demonstration problems are conducted on a cantilever beam, turbine engine disk, and turbine engine blade 2