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research-article

AFFORDABLE UNCERTAINTY QUANTIFICATION FOR INDUSTRIAL PROBLEMS: APPLICATION TO AERO-ENGINE FANS

[+] Author and Article Information
Tiziano Ghisu

Assistant Professor, Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, 09123 Cagliari, Italy
t.ghisu@unica.it

Shahrokh Shahpar

Engineering Associate Fellow, Aerothermal Design Systems, Rolls-Royce plc, Derby, UK
shahrokh.shahpar@rolls-royce.com

1Corresponding author.

ASME doi:10.1115/1.4038982 History: Received October 23, 2017; Revised December 24, 2017

Abstract

Uncertainty Quantification is an increasingly important area of research. As components and systems become more efficient and optimized, the impact of uncertain parameters. It is fundamental to consider the impact of these uncertainties as early as possible during the design process, with the aim of producing more robust designs (less sensitive to the presence of uncertainties). The cost of UQ with high-fidelity simulations becomes therefore of fundamental importance. This work makes use of Least Squares Approximations in the context of appropriately selected Polynomial Chaos bases. An efficient technique based on QR column pivoting has been employed to reduce the number of evaluations required to construct the approximation, demonstrating the superiority of the method with respect to full tensor and sparse grid quadratures. Orthonormal polynomials used for the PC expansion are calculated numerically based on the given uncertainty distribution, making the approach optimal for any type of input uncertainty. The approach is used to quantify the variability in the performance of two large bypass-ratio jet engine fans in the presence of shape uncertainty due to possible manufacturing processes. The impacts of shape uncertainty on the two geometries are compared, and sensitivities to the location of the blade shape variability are extracted. The mechanisms at the origin of the change in performance are analyzed in detail, as well as the differences between the two configurations. These results provide important information both for controling the manufacturing process, and for designing blades that are less sensitive to the presence of manufacturing uncertainties.

Rolls-Royce plc
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