Uncertainty and global sensitivity analysis of bladed disk statics with material anisotropy and root geometry variations

Rajasekharan, Rahul and Petrov, Evgeny (2019) Uncertainty and global sensitivity analysis of bladed disk statics with material anisotropy and root geometry variations. Engineering Reports, 1 (2). pp. 1-20. ISSN 2577-8196

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Abstract

Monocrystalline blades used in gas turbines exhibit material anisotropy, and the orientation of the anisotropy axis affects the deformation of the bladed disk. Considering the orientation of the anisotropy axis as a random design parameter, the uncertainty and sensitivity analysis for static blade deformations are presented for the first time. The following two cases are analyzed using a realistic bladed disk model with friction contacts: (i) deformation of the tuned bladed disks considering the uncertainty in anisotropy orientation and variations in fir tree root geometry and (ii) deformation of mistuned bladed disks with uncertain blade crystal orientations. For efficient uncertainty and sensitivity analysis, the applicability of the following surrogate models are explored: (i) an ensemble of regression trees (random forest) and (ii) gradient-based polynomial chaos expansion. Faster convergence in statistical characteristics has been obtained using a surrogate model compared to that obtained from finite element model based Monte Carlo simulation. From sensitivity analysis, it has been inferred that the uncertainty in static displacements of a blade in a bladed disk is primarily due to the uncertainty in anisotropy angles of that blade itself and secondarily due to the interaction of different blade anisotropy angles.

Item Type: Article
Additional Information: Open access on the publisher website
Keywords: anisotropy, bladed disk, polynomial chaos, sensitivity analysis, single-crystal blades, surrogate modeling, uncertainty analysis
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Research Centres and Groups: Dynamics, Control and Vehicle Research Group
Subjects: T Technology > TJ Mechanical engineering and machinery
Depositing User: Yevgen Petrov
Date Deposited: 29 Oct 2019 09:17
Last Modified: 11 Dec 2019 11:27
URI: http://sro.sussex.ac.uk/id/eprint/87590

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