ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
The fatigue resistance of asphalt concrete (AC) plays an important role in the service life of a pavement. For predicting the fatigue life of AC, there are several existing empirical and mechanistic models. However, the assessment and quantification of the ‘reliability’ of the predictions from these models is a substantial knowledge gap. The importance of reliability in AC material performance predictions becomes all the more important in light of limited monetary and material resources. The goal of this dissertation research is to address these shortcomings by developing a framework for incorporating reliability into the prediction of mechanical models for AC and to improve the reliability of AC material performance prediction by using Fine Aggregate Matrix (FAM) phase data. The goal of the study is divided into four objectives; 1) development of a reliability framework for fatigue life prediction of AC materials using the simplified viscoelastic continuum damage (S-VECD) model, 2) development of test protocols for FAM in similar loading conditions as AC, 3) evaluation of the mechanical linkages between the AC and FAM mix through upscaling analysis, and 4) investigation of the hypothesis that the reliability of fatigue life prediction of AC can be improved with FAM data modeling.
In this research effort, a reliability framework is developed using Monte Carlo simulation for predicting the fatigue life of AC material using the S-VECD model. The reliability analysis reveals that the fatigue life prediction is very sensitive to the uncertainty in the input variables. FAM testing in similar loading conditions as AC, and upscaling of AC modulus and damage response using FAM properties from a relatively simple homogenized continuum approach shows promising results. The FAM phase fatigue life prediction and upscaling of FAM results to AC show more reliable fatigue life prediction than the fatigue life prediction of AC material using its experimental data. To assess the sensitivity of fatigue life prediction model to uncertainty in the input variables, a parametric sensitivity study is conducted on the S-VECD model. Overall, the findings from this research show promising results both in terms of upscaling FAM to AC properties and the reliability of fatigue prediction in AC using experimental data on FAM.
In this research effort, a reliability framework is developed using Monte Carlo simulation for predicting the fatigue life of AC material using the S-VECD model. The reliability analysis reveals that the fatigue life prediction is very sensitive to the uncertainty in the input variables. FAM testing in similar loading conditions as AC, and upscaling of AC modulus and damage response using FAM properties from a relatively simple homogenized continuum approach shows promising results. The FAM phase fatigue life prediction and upscaling of FAM results to AC show more reliable fatigue life prediction than the fatigue life prediction of AC material using its experimental data. To assess the sensitivity of fatigue life prediction model to uncertainty in the input variables, a parametric sensitivity study is conducted on the S-VECD model. Overall, the findings from this research show promising results both in terms of upscaling FAM to AC properties and the reliability of fatigue prediction in AC using experimental data on FAM.
ContributorsGudipudi, Padmini Priyadarsini (Author) / Underwood, Benjamin S (Thesis advisor) / Kaloush, Kamil (Committee member) / Mamlouk, Michael (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2016
Description
Composite materials are widely used in various structural applications, including within the automotive and aerospace industries. Unidirectional composite layups have replaced other materials such as metals due to composites’ high strength-to-weight ratio and durability. Finite-element (FE) models are actively being developed to model response of composite systems subjected to a variety of loads including impact loads. These FE models rely on an array of measured material properties as input for accuracy. This work focuses on an orthotropic plasticity constitutive model that has three components – deformation, damage and failure. The model relies on the material properties of the composite such as Young’s modulus, Poisson’s ratio, stress-strain curves in the principal and off-axis material directions, etc. This thesis focuses on two areas important to the development of the FE model – tabbing of the test specimens and data processing of the tests used to generate the required stress-strain curves. A comparative study has been performed on three candidate adhesives using double lap-shear testing to determine their effectiveness in composite specimen tabbing. These tests determined the 3M DP460 epoxy performs best in shear. The Loctite Superglue with 80% the ultimate stress of the 3M DP460 epoxy is acceptable when test specimens have to be ready for testing within a few hours. JB KwikWeld is not suitable for tabbing. In addition, the Experimental Data Processing (EDP) program has been improved for use in post-processing raw data from composites test. EDP has improved to allow for complete processing with the implementation of new weighted least squares smoothing options, curve averaging techniques, and new functionality for data manipulation.
ContributorsSchmidt, Nathan William (Author) / Rajan, Subramaniam D. (Thesis advisor) / Neithalath, Narayanan (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2016