Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- All Subjects: Packing
- All Subjects: Pipe Conveying Fluid
Description
In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD) employed to generate the packing ensembles will be discussed. A large number of 2D packing configurations of superdisks are subsequently analyzed, through which a relatively accurate theoretical scheme for packing-fraction prediction based on local particle contact configurations is proposed and validated via additional numerical simulations. Moreover, the studies on binary ellipsoid packing in 3D are briefly discussed and the effects of different geometrical parameters on the final packing fraction are analyzed.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Oswald, Jay (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
This investigation is focused on the consideration of structural uncertainties in nearly-straight pipes conveying fluid and on the effects of these uncertainties on the dynamic response and stability of those pipes. Of interest more specifically are the structural uncertainties which affect directly the fluid flow and its feedback on the structural response, e.g., uncertainties on/variations of the inner cross-section and curvature of the pipe. Owing to the complexity of introducing such uncertainties directly in finite element models, it is desired to proceed directly at the level of modal models by randomizing simultaneously the appropriate mass, stiffness, and damping matrices. The maximum entropy framework is adopted to carry out the stochastic modeling of these matrices with appropriate symmetry constraints guaranteeing that the nature, e.g., divergence or flutter, of the bifurcation is preserved when introducing uncertainty.
To support the formulation of this stochastic ROM, a series of finite element computations are first carried out for pipes with straight centerline but inner radius varying randomly along the pipe. The results of this numerical discovery effort demonstrate that the dominant effects originate from the variations of the exit flow speed, induced by the change in inner cross-section at the pipe end, with the uncertainty on the cross-section at other locations playing a secondary role. Relying on these observations, the stochastic reduced order model is constructed to model separately the uncertainty in inner cross-section at the pipe end and at other locations. Then, the fluid related mass, damping, and stiffness matrices of this stochastic reduced order model (ROM) are all determined from a single random matrix and a random variable. The predictions from this stochastic ROM are found to closely match the corresponding results obtained with the randomized finite element model. It is finally demonstrated that this stochastic ROM can easily be extended to account for the small effects due to uncertainty in pipe curvature.
To support the formulation of this stochastic ROM, a series of finite element computations are first carried out for pipes with straight centerline but inner radius varying randomly along the pipe. The results of this numerical discovery effort demonstrate that the dominant effects originate from the variations of the exit flow speed, induced by the change in inner cross-section at the pipe end, with the uncertainty on the cross-section at other locations playing a secondary role. Relying on these observations, the stochastic reduced order model is constructed to model separately the uncertainty in inner cross-section at the pipe end and at other locations. Then, the fluid related mass, damping, and stiffness matrices of this stochastic reduced order model (ROM) are all determined from a single random matrix and a random variable. The predictions from this stochastic ROM are found to closely match the corresponding results obtained with the randomized finite element model. It is finally demonstrated that this stochastic ROM can easily be extended to account for the small effects due to uncertainty in pipe curvature.
ContributorsShah, Shrinil (Author) / Mignolet, Marc P (Thesis advisor) / Liu, Yongming (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2017