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Measurement of Hysteresis Energy Using Digital Image Correlation with Application to Energy Based Fatigue Life Prediction and Assessment

Celli, Dino Anthony
http://rave.ohiolink.edu/etdc/view?acc_num=osu1494249217899146

Abstract Details

2017, Master of Science, Ohio State University, Aeronautical and Astronautical Engineering.
A modified experimental method using non-contact digital image correlation (DIC) has been developed for interrogating accumulated tensile and fatigue damage for low and high cycle fatigue (LCF/HCF) at continuum scales. Axial strain of round dogbone specimens of Aluminum 6061-T6 and Inconel 625 has been collected for the purpose of measuring monotonic and hysteresis strain energy and compared with axial extensometer data for validation. Traditional strain measurement methods are limited to averaged strain measurements such as extensometers, which are simple and easy to implement, but require specimens of specific geometry and collect only an averaged strain data. On the other hand, DIC enables measurement of full field strain of surfaces with simple and complicated geometry with minimal preparation Monotonic tensile tests were performed using DIC to determine material properties and strain energy. Unlike an extensometer, the entire true stress-strain curve can be measured with DIC. True fracture stress and strain measurements of DIC and by measuring the reduced area of the specimen after fracture were compared. It was found that the DIC measurements of true stress and strain were consistently lower than traditional methods. The Bridgman correction is used to account for the introduction of radial and hoop stresses in the traditional method, and the results were consistent with DIC. An energy based fatigue damage and life prediction method is also developed for a high temperature material, Inconel 625, and Aluminum 6061-T6. Stress controlled mechanical fatigue tests are performed to construct room temperature stress vs. cycles to failure (S-N) curves and to determine damage progression for the purpose of life prediction. It is assumed failure will occur at a critical, total strain energy density dissipation. Cyclic strain energy density is the finite area within a hysteresis loop caused by plastic deformation and modeled by the Ramberg-Osgood stress-strain relation. By using only two experimental fatigue data points, the presented energy based fatigue life prediction model was able to accurately predict LCF and HCF life. DIC was found to be a reliable and effective method for capturing hysteresis strain energy dissipation and showed the capability of monitoring fatigue life.
M.-H. Herman Shen, Ph.D. (Advisor)
Prasad Mokashi, Ph.D. (Committee Member)
Tommy George, Ph.D. (Committee Member)
Onome Scott-Emuakpor, Ph.D. (Committee Member)
Casey Holycross, Ph.D. (Committee Member)
97 p.
Aerospace Engineering; Aerospace Materials
Fatigue, Strain Energy Density, Life Prediction, Digital Image Correlation

Recommended Citations

Citations

  • Celli, D. A. (2017). Measurement of Hysteresis Energy Using Digital Image Correlation with Application to Energy Based Fatigue Life Prediction and Assessment [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494249217899146

    APA Style (7th edition)

  • Celli, Dino. Measurement of Hysteresis Energy Using Digital Image Correlation with Application to Energy Based Fatigue Life Prediction and Assessment. 2017. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1494249217899146.

    MLA Style (8th edition)

  • Celli, Dino. "Measurement of Hysteresis Energy Using Digital Image Correlation with Application to Energy Based Fatigue Life Prediction and Assessment." Master's thesis, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494249217899146

    Chicago Manual of Style (17th edition)

osu1494249217899146
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© 2017, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.