Uncertainty quantification with maximum entropy method for fatigue life estimation

TY - GEN

T1 - Uncertainty quantification with maximum entropy method for fatigue life estimation

AU - Nielsen, S. M.

AU - Hougaard, H. A.

AU - Balling, O.

N1 - Publisher Copyright: Copyright © 2020 ASME.

PY - 2020

Y1 - 2020

N2 - Use of high-fidelity fatigue models that incorporate not only material uncertainty but also part variability and operational uncertainties can improve the accuracy of predictive maintenance and thus decrease operational cost. However, due to the large number of computationally expensive cost function evaluations necessary, little work has been done to explore this field. In this research, the expected life probability distributions with low computational cost is estimated through a general statistical framework that applies Maximum Entropy Method (MEM), fractional statistical moments and Multiplicative Dimensional Reduction (M-DRM). The framework is tested on advanced models of a 6204 SKF ball bearing. The influence of critical part tolerances and load conditions on fatigue life with a probability density function with only 80 function evaluations is quantified in both a finite element analysis and a non-linear analytical model. The number of function evaluations is one order of magnitude lower than necessary for a comparable accuracy achieved by Monte Carlo simulation.

AB - Use of high-fidelity fatigue models that incorporate not only material uncertainty but also part variability and operational uncertainties can improve the accuracy of predictive maintenance and thus decrease operational cost. However, due to the large number of computationally expensive cost function evaluations necessary, little work has been done to explore this field. In this research, the expected life probability distributions with low computational cost is estimated through a general statistical framework that applies Maximum Entropy Method (MEM), fractional statistical moments and Multiplicative Dimensional Reduction (M-DRM). The framework is tested on advanced models of a 6204 SKF ball bearing. The influence of critical part tolerances and load conditions on fatigue life with a probability density function with only 80 function evaluations is quantified in both a finite element analysis and a non-linear analytical model. The number of function evaluations is one order of magnitude lower than necessary for a comparable accuracy achieved by Monte Carlo simulation.

UR - https://www.scopus.com/pages/publications/85096186110

U2 - 10.1115/DETC2020-22728

DO - 10.1115/DETC2020-22728

M3 - Article in proceedings

AN - SCOPUS:85096186110

BT - Volume 5: 24th Reliability, Stress Analysis, and Failure Prevention Conference (RSAFP)

T2 - ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020

Y2 - 17 August 2020 through 19 August 2020

ER -