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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- Creators: Pan, Rong
- Creators: Oswald, Jay
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
As a first step in developing a fundamental understanding of the cavitation erosion process on polymer surfaces, simulations are performed of the collapse of individual bubbles against a compliant surface e.g. metallic substrates with polyurea coatings. The surface response of collapse-driven impact loads is represented by a idealized, time-dependent, Gaussian pressure distribution on the surface. A two-dimensional distribution of load radii and durations is considered corresponding to characteristic of cavitating flows accelerated erosion experiments. Finite element simulations are performed to fit a response curve that relates the loading parameters to the energy dissipated in the coating and integrated with collapse statistics to generate an expected heat input into the coating.
The impulsive pressure, which is generated due to bubble collapse, impacts the material and generates intense shock waves. The stress waves within the material reflects by interaction with the substrate. A transient region of high tensile stress is produced by the interaction of these waves. Simulations suggests that maximum hydrostatic tension which cause failure of polyurea layer is observed in thick coating. Also, the dissipated viscous energy and corresponding temperature rise in a polyurea is calculated, and it is concluded that temperature has influence on deformation.
The effects of this nonlinear damping mechanism on the post-flutter response is next analyzed on the Goland wing through time-marching of the aeroelastic equations comprising a rational fraction approximation of the linear aerodynamic forces. It is indeed found that the nonlinearity in the damping can stabilize the unstable aerodynamics and lead to finite amplitude limit cycle oscillations even when the stiffness related nonlinear geometric effects are neglected. The incorporation of these latter effects in the model is found to further decrease the amplitude of LCO even though the dominant bending motions do not seem to stiffen as the level of displacements is increased in static analyses.
To help better understand how the football helmet design features effect the brain response during impact, this research develops a validated football helmet model and couples it with a full LS-DYNA human body model developed by the Global Human Body Modeling Consortium (v4.1.1). The human body model is a conglomeration of several validated models of different sections of the body. Of particular interest for this research is the Wayne State University Head Injury Model for modeling the brain. These human body models were validated using a combination of cadaveric and animal studies. In this study, the football helmet was validated by laboratory testing using drop tests on the crown of the helmet. By coupling the two models into one finite element model, the brain response to impact loads caused by helmet design features can be investigated. In the present research, LS-DYNA is used to study a helmet crown impact with a rigid steel plate so as to obtain the strain-rate, strain, and stress experienced in the corpus callosum, midbrain, and brain stem as these anatomical regions are areas of concern with respect to mTBI.