Environmental stress screening (ESS) by thermal cycling and random vibration: A physical investigation
AuthorSun, Feng-Bin, 1963-
AdvisorKececioglu, Dimitri B.
MetadataShow full item record
PublisherThe University of Arizona.
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.
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.
Degree ProgramGraduate College
Aerospace and Mechanical Engineering