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arXiv · 1510.04162

Density-Matching for Turbomachinery Optimization Under Uncertainty

Pranay Seshadri·Geoffrey Parks·Shahrokh Shahpar
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Abstract

A monotonic, non-kernel density variant of the density-matching technique for optimization under uncertainty is developed. The approach is suited for turbomachinery problems which, by and large, tend to exhibit monotonic variations in the circumferentially and radially mass-averaged quantities--such as pressure ratio, efficiency and capacity--with common aleatory turbomachinery uncertainties. The method is successfully applied to de-sensitize the effect of an uncertainty in rear-seal leakage flows on the fan stage of a modern jet engine.

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Pranay Seshadri, Geoffrey Parks, Shahrokh Shahpar. 2015-10-14. Density-Matching for Turbomachinery Optimization Under Uncertainty. https://doi.org/10.1016/j.cma.2016.03.006

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