Stochastic analysis and validation under aleatory and epistemic uncertainties

Austin M. McKeand, Recep M. Gorguluarslan and Seung-Kyum Choi

Reliability Engineering and System Safety, 2021, vol. 205, issue C

Abstract: An uncertainty quantification and validation framework is presented to account for both aleatory and epistemic uncertainties in stochastic simulations of turbine engine components. The spatial variability of the uncertain geometric parameters obtained from coordinate measuring machine data of manufactured parts is represented as aleatory uncertainty. Porosity and defects in the manufactured parts based on micro CT-scanned images are represented as epistemic uncertainty. A stochastic upscaling method and probability box approach are integrated to propagate both the epistemic and aleatory uncertainties from fine models to coarse models to quantify the homogenized elastic modulus uncertainties. The framework is applied for a turbine blade example and validated by modal frequency experiments of the manufactured blade samples. A validation approach, called mean curve validation method, is utilized to effectively compare the p-box of the predictions with the experimental results. The application results show that the proposed framework can significantly reduce the complexity of the engineering problem as well as produce accurate results when both aleatory and epistemic uncertainties exist in the problem.

Keywords: Uncertainty quantification; Stochastic upscaling; Validation; Turbine blade (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832020307584
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:205:y:2021:i:c:s0951832020307584

DOI: 10.1016/j.ress.2020.107258

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().