Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2876
Title: Stochastic simulation of turbine engine component under aleatory and epistemic uncertainty
Authors: McKeand, A. M.
Görgülüarslan, Recep Muhammed
Choi, S. K.
Keywords: Gas turbines
 simulation
 uncertainty
 aerospace industry
 elastic moduli
 engineering simulation
 computerized tomography
 design
 Ffnite element model
 materials properties
 porosity
 turbine blades
Issue Date: Nov-2019
Publisher: American Society of Mechanical Engineers (ASME)
Source: McKeand, A. M., Gorguluarslan, R. M., and Choi, S. K. Stochastic Simulation of Turbine Engine Component Under Aleatory and Epistemic Uncertainty. In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection.
Abstract: Quantifying the uncertainty associated with material properties in engineering analysis has become more important in the design of many components in the aerospace field. In this study, a new method is proposed to account for the uncertainty associated with the elastic modulus of materials used in aerospace components. A computerized tomography (CT) scanner is used to capture the porosity of the material and the corresponding uncertainty is represented with epistemic uncertainty. A stochastic upscaling method is used to find a homogenized modulus that correctly reflects the effect of defects inside of the material. This homogenized elastic modulus is then applied to a constructed finite-element model of an aerospace component so that the stochastic behavior can be correctly quantified. Simulations of the selected example, i.e., turbine blade, include both aleatory and epistemic uncertainty; thus, a P-Box is introduced to represent the response of the simulations. The stochastic upscaling method is applied again to match the P-Box response of the coarse scale model to that of the fine scale model. The obtained results show that the proposed framework not only significantly reduces complexity of the given engineering problem, but also produces accurate results which include both aleatory and epistemic uncertainty. Copyright © 2019 ASME.
Description: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (2019: Anaheim; United States)
URI: https://hdl.handle.net/20.500.11851/2876
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/59179/V001T02A070/1069710
ISBN: 978-079185917-9
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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