Implementation of Sobol’s sensitivity analysis to cyclic plasticity model with parameter uncertainty
Source abstract
Abstract
Abstract Though modeling material cyclic plasticity in a probabilistic way can yield a more accurate result than deterministic modelling method, it is quite hard to perform uncertainty quantification for all the material parameters. In this paper, Sobol’s global sensitivity analysis is applied to cyclic plasticity model to investigate how the variation of these parameters affect fatigue reliability evaluation. A machine learning algorithm is proposed to improve the computational efficiency for failure probability assessment. The results of global sensitivity analysis show that fatigue damage parameters, elastic modulus and initial yield stress are very influential to fatigue reliability analysis while others are not.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Probabilistic and Robust Engineering Design · Fatigue and fracture mechanics · Structural Response to Dynamic Loads
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
Show source-provided references
1. Equivalent initial flaw size model for fracture strength prediction of optical fibers with indentation flaws10.1016/j.engfracmech.2019.04.021 ↗
2. Probabilistic fatigue life prediction using an equivalent initial flaw size distribution10.1016/j.ijfatigue.2008.06.005 ↗
3. An energy-based microstructure model to account for fatigue scatter in polycrystals10.1016/j.jmps.2010.12.014 ↗
4. A Microstructure-Based Time-Dependent Crack Growth Model for Life and Reliability Prediction of Turbopropulsion Systems10.1007/s11661-013-1971-9 ↗
5. Joint estimation of E-N curves and their scatter using evolutionary algorithms10.1016/j.ijfatigue.2013.08.005 ↗
6. Estimating S-N curves and their scatter using a differential ant-stigmergy algorithm10.1016/j.ijfatigue.2012.02.015 ↗
7. A methodology to determine a conditional probability density distribution surface from S-N data10.1016/j.ijfatigue.2012.05.008 ↗
8. Determination of fatigue life for low probability of failure for different stress levels using 3-parameter Weibull distribution10.1016/j.ijfatigue.2020.106080 ↗
9. Determination of the fatigue life of a helicopter tail rotor transmission subjected to ballistic damage10.1016/j.engfracmech.2006.07.003 ↗
10. Probabilistic framework for multiaxial LCF assessment under material variability10.1016/j.ijfatigue.2017.06.019 ↗
11. A novel method for structure's fatigue life scatter simulation under material variability10.1016/j.ijfatigue.2021.106296 ↗
12. Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty10.1016/j.ress.2015.10.002 ↗
13. Fatigue probability assessment including aleatory and epistemic uncertainty with application to gas turbine compressor blades10.1016/j.ijfatigue.2016.10.001 ↗
14. A general framework for fatigue reliability analysis of a high temperature component10.1002/qre.2399 ↗
15. Probabilistic simulation of fatigue damage and life scatter of metallic components10.1016/j.ijplas.2012.11.001 ↗
16. A reliability-based fatigue design for mechanical components under material variability10.1002/qre.2586 ↗
17. An efficient computational method for global sensitivity analysis and its application to tree growth modelling10.1016/j.ress.2011.07.001 ↗
18. Antoniadis · 2021 · 107312
19. Local and Global Sensitivity Analysis for a Reactor Design with Parameter Uncertainty10.1205/026387604323142630 ↗
20. The role of sensitivity analysis in ecological modelling10.1016/j.ecolmodel.2005.10.045 ↗
21. Supporting the design of railway systems by means of a Sobol variance-based sensitivity analysis10.1016/j.trc.2013.05.007 ↗
22. Sobol sensitivity analysis for governing variables in design of a plate-fin heat exchanger with serrated fins10.1016/j.ijheatmasstransfer.2017.08.089 ↗
23. Image decomposition and uncertainty quantification for the assessment of manufacturing tolerances in stress analysis10.1177/0309324714533694 ↗
24. A non-intrusive stochastic phase field method for crack propagation in functionally graded materials10.1007/s00707-021-02956-z ↗
25. Constitutive and damage modelling of H11 subjected to low-cycle fatigue at high temperature10.1111/ffe.12632 ↗
26. On the Plastic and Viscoplastic Constitutive Equations—Part I: Rules Developed With Internal Variable Concept10.1115/1.3264257 ↗
27. Lemaitre · 2005
28. Sensitivity analysis for volcanic source modeling quality assessment and model selection10.1016/j.cageo.2012.03.008 ↗
29. Making best use of model evaluations to compute sensitivity indices10.1016/S0010-4655(02)00280-1 ↗
30. Support vector machine based reliability analysis of concrete dams10.1016/j.soildyn.2017.09.016 ↗
31. Optimization of Kernel Function Parameters SVM Based on the GA
32. Modified Metropolis-Hastings algorithm with delayed rejection10.1016/j.probengmech.2010.11.008 ↗
33. An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation10.1016/j.strusafe.2017.04.006 ↗