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dc.contributor.advisorKececioglu, Dimitri B.en_US
dc.contributor.authorSun, Feng-Bin, 1963-
dc.creatorSun, Feng-Bin, 1963-en_US
dc.date.accessioned2013-04-18T09:40:18Z
dc.date.available2013-04-18T09:40:18Z
dc.date.issued1997en_US
dc.identifier.urihttp://hdl.handle.net/10150/282309
dc.description.abstractTemperature cycling and random vibration have proven to be the two most effective environmental stress screens. This study presents an extensive research on the physical quantification and optimization of temperature cycling and random vibration screens. For temperature cycling screen, a general model has been proposed to describe a typical temperature response cycle and a typical power-temperature response cycle. The least-squares parameter estimates for the two modified Arrhenius models are derived. Two general models for quantifying the equivalent aging acceleration factor of a typical temperature cycle with or without power cycling, considering both reaction rate stress and temperature change rate stress and also incorporating the temperature dependence of the activation energy, are derived. A closed form solution under the mixed-exponential life distribution assumption and an iteration equation solution under the Weibull distribution assumption, of the optimum number of temperature cycles for a specified post-screen field Mean Residual Life (MRL) goal, are established. For the random vibration screen, the distributions of the cumulative damage and fatigue life, under both stationary narrow-band and stationary wide-band random stressings, are derived under both-normal, semi-normal, and Markov-process assumptions. A bimodal mixed P-S-N diagram is proposed, from the failure physics point of view, to describe the fatigue strength of a non-screened unit. The concepts of the threshold S-N curve and the screening probability for fatigue defect precipitation are proposed to facilitate the quantification of random vibration screens. Finally, the closed form solution of the optimum vibration duration for a specified screening probability is derived under both-normal, semi-normal and Markov-process assumptions, respectively.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectEngineering, Mechanical.en_US
dc.subjectEngineering, Packaging.en_US
dc.titleEnvironmental stress screening (ESS) by thermal cycling and random vibration: A physical investigationen_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.identifier.proquest9729457en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineAerospace and Mechanical Engineeringen_US
thesis.degree.namePh.D.en_US
dc.description.noteThis item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at repository@u.library.arizona.edu.
dc.identifier.bibrecord.b34801443en_US
dc.description.admin-noteOriginal file replaced with corrected file October 2023.
refterms.dateFOA2018-09-05T16:38:35Z
html.description.abstractTemperature cycling and random vibration have proven to be the two most effective environmental stress screens. This study presents an extensive research on the physical quantification and optimization of temperature cycling and random vibration screens. For temperature cycling screen, a general model has been proposed to describe a typical temperature response cycle and a typical power-temperature response cycle. The least-squares parameter estimates for the two modified Arrhenius models are derived. Two general models for quantifying the equivalent aging acceleration factor of a typical temperature cycle with or without power cycling, considering both reaction rate stress and temperature change rate stress and also incorporating the temperature dependence of the activation energy, are derived. A closed form solution under the mixed-exponential life distribution assumption and an iteration equation solution under the Weibull distribution assumption, of the optimum number of temperature cycles for a specified post-screen field Mean Residual Life (MRL) goal, are established. For the random vibration screen, the distributions of the cumulative damage and fatigue life, under both stationary narrow-band and stationary wide-band random stressings, are derived under both-normal, semi-normal, and Markov-process assumptions. A bimodal mixed P-S-N diagram is proposed, from the failure physics point of view, to describe the fatigue strength of a non-screened unit. The concepts of the threshold S-N curve and the screening probability for fatigue defect precipitation are proposed to facilitate the quantification of random vibration screens. Finally, the closed form solution of the optimum vibration duration for a specified screening probability is derived under both-normal, semi-normal and Markov-process assumptions, respectively.


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