{"title":"Fatigue Life Prediction of Structures with Interval Uncertainty","authors":"Michael Desch, M. Modares","doi":"10.1115/1.4053940","DOIUrl":null,"url":null,"abstract":"\n A new method for reliable fatigue life prediction in metal structural components is developed which quantifies uncertainties using interval variables. Using this crack-initiation-based method, first, the uncertainties in laboratory test data for the fatigue failure of a structural detail are enumerated. This uncertainty quantification is performed through an interval-based enveloping procedure that relates the interval stress ranges to the number of cycles to failure. This will lead to the construction of an interval S-N relationship. Next, the uncertainties in field test data are enumerated in the extremum values of each stress range, as intervals, leading to the construction of interval stress ranges. For both the laboratory and field data uncertainty analyses, the mean stress effects are considered. Next, the interval damage accumulated over the duration of the field data is determined using the constructed interval S-N relationship and the obtained interval stress ranges. Then, the interval existing damage and interval remaining life are determined. Finally, as a conservative measure, the minimum remaining fatigue life is obtained in which, all uncertainties are considered. A numerical example illustrating the developed method is presented, and the results are compared with results obtained by both Monte Carlo simulation and optimization. Using this method, for the numerical example considered, it is shown that the results for bounds on the existing damage and the remaining fatigue life are sharp. Moreover, due to its set-based approach, the method is significantly more computationally efficient when compared with iterative procedures.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4053940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
A new method for reliable fatigue life prediction in metal structural components is developed which quantifies uncertainties using interval variables. Using this crack-initiation-based method, first, the uncertainties in laboratory test data for the fatigue failure of a structural detail are enumerated. This uncertainty quantification is performed through an interval-based enveloping procedure that relates the interval stress ranges to the number of cycles to failure. This will lead to the construction of an interval S-N relationship. Next, the uncertainties in field test data are enumerated in the extremum values of each stress range, as intervals, leading to the construction of interval stress ranges. For both the laboratory and field data uncertainty analyses, the mean stress effects are considered. Next, the interval damage accumulated over the duration of the field data is determined using the constructed interval S-N relationship and the obtained interval stress ranges. Then, the interval existing damage and interval remaining life are determined. Finally, as a conservative measure, the minimum remaining fatigue life is obtained in which, all uncertainties are considered. A numerical example illustrating the developed method is presented, and the results are compared with results obtained by both Monte Carlo simulation and optimization. Using this method, for the numerical example considered, it is shown that the results for bounds on the existing damage and the remaining fatigue life are sharp. Moreover, due to its set-based approach, the method is significantly more computationally efficient when compared with iterative procedures.