A Probabilistic Design Method for Fatigue Life of Metallic ComponentSource: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:003::page 31005Author:Faghihi, Danial
,
Sarkar, Subhasis
,
Naderi, Mehdi
,
Rankin, Jon E.
,
Hackel, Lloyd
,
Iyyer, Nagaraja
DOI: 10.1115/1.4038372Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In the present study, a general probabilistic design framework is developed for cyclic fatigue life prediction of metallic hardware using methods that address uncertainty in experimental data and computational model. The methodology involves: (i) fatigue test data conducted on coupons of Ti6Al4V material, (ii) continuum damage mechanics (CDM) based material constitutive models to simulate cyclic fatigue behavior of material, (iii) variance-based global sensitivity analysis, (iv) Bayesian framework for model calibration and uncertainty quantification, and (v) computational life prediction and probabilistic design decision making under uncertainty. The outcomes of computational analyses using the experimental data prove the feasibility of the probabilistic design methods for model calibration in the presence of incomplete and noisy data. Moreover, using probabilistic design methods results in assessment of reliability of fatigue life predicted by computational models.
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contributor author | Faghihi, Danial | |
contributor author | Sarkar, Subhasis | |
contributor author | Naderi, Mehdi | |
contributor author | Rankin, Jon E. | |
contributor author | Hackel, Lloyd | |
contributor author | Iyyer, Nagaraja | |
date accessioned | 2019-02-28T11:11:47Z | |
date available | 2019-02-28T11:11:47Z | |
date copyright | 12/12/2017 12:00:00 AM | |
date issued | 2018 | |
identifier issn | 2332-9017 | |
identifier other | risk_004_03_031005.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4253700 | |
description abstract | In the present study, a general probabilistic design framework is developed for cyclic fatigue life prediction of metallic hardware using methods that address uncertainty in experimental data and computational model. The methodology involves: (i) fatigue test data conducted on coupons of Ti6Al4V material, (ii) continuum damage mechanics (CDM) based material constitutive models to simulate cyclic fatigue behavior of material, (iii) variance-based global sensitivity analysis, (iv) Bayesian framework for model calibration and uncertainty quantification, and (v) computational life prediction and probabilistic design decision making under uncertainty. The outcomes of computational analyses using the experimental data prove the feasibility of the probabilistic design methods for model calibration in the presence of incomplete and noisy data. Moreover, using probabilistic design methods results in assessment of reliability of fatigue life predicted by computational models. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | A Probabilistic Design Method for Fatigue Life of Metallic Component | |
type | Journal Paper | |
journal volume | 4 | |
journal issue | 3 | |
journal title | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering | |
identifier doi | 10.1115/1.4038372 | |
journal fristpage | 31005 | |
journal lastpage | 031005-11 | |
tree | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:003 | |
contenttype | Fulltext |