Department: School of Engineering and Applied Science - Manufacturing Engineering ![Remove this limiter [clear]](close-x.png)
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Mejia, Paloma Yasmin.
Smart Systems for Damage Detection and Prognosis.
Degree: BS, School of Engineering and Applied Science - Manufacturing Engineering, 2005, Miami University Honors Theses
► Health monitoring of structures aims to characterize, asses, and predict damage initiation…
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▼ Health monitoring of structures aims to characterize, asses, and predict damage initiation and propagation. Studies in this field are utilized to provide a damage analysis of structures that allows time-consuming inspections to be avoided. The aim of this work is to use experimental and computational tools to identify key parameters that characterize damage initiation and propagation. More specifically, this thesis will focus on experimental and computational modeling of damaged and healthy automotive exhaustive hangers to determine the main mechanical parameters that will serve to identify damage. The results obtained from computer simulations and laboratory experiments are thoroughly compared and analyzed to observe the changes in mechanical properties of the structure. The evolution of damage in the structure will translate in alterations in its mechanical properties. This report starts by providing a brief introduction to the field of health monitoring and a literature review of available methods for damage identification and prediction. The research approach is also described to introduce the reader to the main tools used in this study. Sections on experimental and computational analysis of the results follow which provides the main findings of this work. Finally, the conclusions and future work section of the report provides a summary of the main findings and the potential usage of these in future studies in the field of prognosis.
Advisors/Committee Members: Shukla, Amit.
Subjects: Engineering, Mechanical
Keywords: damage detection, non-destructive evaluation
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