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.
Filtering by
- All Subjects: Composite Materials
- Creators: Chattopadhyay, Aditi
- Creators: Mobasher, Barzin
Under an applied stress, the cyclooctane-rings in the Di-AC particles revert back to their fluorescent anthracene form, which linearly enhances the overall fluorescence of the composite in response to the applied strain. The fluorescent signal further allows for stress sensing in the elastic region of the stress-strain curve, which is considered to be a form of damage precursor detection. This behavior was further analyzed at the molecular scale with corresponding molecular dynamics simulations. Following the successful application of Di-AC to an epoxy matrix, the mechanophore particles were incorporated into a polyurethane matrix to show the universal nature of Di-AC as a stress-sensitive particle filler. Interestingly, in polyurethane Di-AC could successfully detect damage with less applied strain compared to the epoxy system.
While mechanophores of varying chemistries have been covalently incorporated into elastomeric and thermoplastic polymer systems, they have not yet been covalently incorporated a thermoset network polymer. Thus, following the study of mechanophore particles as stress-sensitive fillers, two routes of grafting mechanophore units into an epoxy system to form a self-sensing nanocomposite were explored. These involved the mechanophore precursor and mechanophore, cinnamamide and di-cinnamamide, respectively. With both molecules, the free amine groups can directly bond to epoxy resin to covalently incorporate themselves within the thermoset network to form a self-sensing nanocomposite.
The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.