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dc.contributor.advisorShin, Young
dc.contributor.authorLukens, Richard Walter
dc.dateJune 1983
dc.date.accessioned2012-11-19T23:59:46Z
dc.date.available2012-11-19T23:59:46Z
dc.date.issued1983-06
dc.identifier.urihttp://hdl.handle.net/10945/19953
dc.descriptionApproved for public release; distribution is unlimited
dc.description.abstractA principal mode of failure of structural components in mechanical systems is fatigue. One method of predicting the probability of fatigue failure of a structural component is to determine the probability that the calculated cumulative fatigue damage index is greater than the critical damage index at failure. The cumulative fatigue damage index is represented as a random variable, and the critical damage index is represented by the statistical variance of existing experimental data. A FORTRAN computer code using this failure criteria is presented, which calculates the probability of failure for a structural component in the high- cycle fatigue regime under a random stress response environment, using both the Weibull and log-normal statistical distribution models. The Weibull model has been found to be the more conservative model in the low probability of failure region, which is consistent with failure predictions between the two models using the classical failure criteria of cyclic life.
dc.description.urihttp://archive.org/details/probabilisticfat00luke
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
dc.subject.lcshMechanical engineeringen_US
dc.titleProbabilistic fatigue life predictions of structural components in high-cycle fatigue regimesen_US
dc.typeThesisen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentMechanical Engineering
dc.subject.authorHigh-cycle fatigue
dc.subject.authorProbabilistic analysis
dc.subject.authorFatigue life prediction model
dc.subject.authorWeibull distribution
dc.subject.authorLog-normal distribution
dc.description.serviceLieutenant, United States Navy
etd.thesisdegree.nameM.S. in Mechanical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineMechanical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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