Density-Matching for Turbomachinery Optimization Under Uncertainty
Applications
2016-05-25 v1 Optimization and Control
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.
Cite
@article{arxiv.1510.04162,
title = {Density-Matching for Turbomachinery Optimization Under Uncertainty},
author = {Pranay Seshadri and Geoffrey Parks and Shahrokh Shahpar},
journal= {arXiv preprint arXiv:1510.04162},
year = {2016}
}
Comments
9 pages