ETDs

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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Effects of Advanced Material Morphologies on Thermal, Electrical and Thermo-electric Properties

Description
Progressive miniaturization in electronics demands advanced materials with excellent energy conversion and transport properties. Opportunities exist in novel material morphologies such as hierarchical structures, multi-functional composites and nanoscale architectures which may offer mechanical, thermal and electronic properties tailored to a wide range of applications (e.g., aerospace, robotics, biomedical etc.). However,…

Progressive miniaturization in electronics demands advanced materials with excellent energy conversion and transport properties. Opportunities exist in novel material morphologies such as hierarchical structures, multi-functional composites and nanoscale architectures which may offer mechanical, thermal and electronic properties tailored to a wide range of applications (e.g., aerospace, robotics, biomedical etc.). However, the manufacturing capabilities have always posed a grand challenge in realizing the advanced material morphologies. Furthermore, the multi-scale modeling of complex material architectures has been extremely challenging owing to the limitations in computation methodologies and lack of understanding in nano-/micro-meter scale physics. To address these challenges, this work considers the morphology effect on carbon nanotube (CNT)-based composites, CNT fibers and thermoelectric (TE) materials. First, this work reports additively manufacturable TE morphologies and analyzes the thermo-electric transport behavior. This research introduces innovative honeycomb TE architectures that showed ~26% efficiency increase and ~25% density reduction compared to conventional rectangular TE architectures. Moreover, this work presents 3D printable compositionally segmented TE architecture which provides record-high efficiencies (up to 8.7%) over wide temperature ranges if the composition and aspect ratio of multiple TE materials are optimized within a single TE device. Next, this research proposes computationally efficient two-dimensional (2D) finite element model (FEM) to study the electrical and thermal properties in CNT based composites by simultaneously considering the stochastic CNT distributions, CNT fractions (upto 80%) and interfacial resistances. The FEM allows to estimate the theoretical maximum possible conductivities with corresponding interfacial resistances if the CNT morphologies are carefully controlled, along with appreciable insight into the energy transport physics. Then, this work proposes a data-driven surrogate model based on convolutional neural networks to rapidly approximate the composite conductivities in a second with accuracy > 98%, compared to FEM taking >100 minutes per simulation. Finally, this research presents a pseudo 2D FEM to approximate the electrical and thermal properties in CNT fibers at various CNT aspect ratios (up to 10,000) by simultaneously considering CNT-CNT interfacial effects along with the stochastic distribution of inter-bundle voids.
ContributorsEjaz, Faizan (Author) / Kwon, Beomjin (Thesis advisor) / Zhuang, Houlong (Committee member) / Song, Kenan (Committee member) / Wang, Robert (Committee member) / Kang, Wonmo (Committee member) / Arizona State University (Publisher)
Created2023
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Optimizing Pin Fin Shapes In a Heat Sink: Investigating The Impact of Genetic Algorithm Parameters

Description
This research aims to identify optimal pin fin shapes that minimize flow pressuredrop and maximize heat transfer performance while investigating the influence of genetic algorithm (GA) parameters on these shapes. The primary goal is to discover innovative pin fin configurations through the use of a GA, moving away from traditional circular cylindrical designs.…

This research aims to identify optimal pin fin shapes that minimize flow pressuredrop and maximize heat transfer performance while investigating the influence of genetic algorithm (GA) parameters on these shapes. The primary goal is to discover innovative pin fin configurations through the use of a GA, moving away from traditional circular cylindrical designs. The study also examines GA parameters, including population size, generation size, selection methods, crossover rates, tournament size, and elite counts. A physical condition considered in this study is a rectangular channel with a square cross-section integrated with 10 pin fins, operating at a Reynolds number of 2316, and subjected to a heat flux of 5 W/cm2 at the bottom surface. Overall, the research seeks to enhance the energy efficiency of a liquid cooling system, with potential applications in the thermal management of computing devices. By enabling operating at significantly lower power, the optimized cooling system promises to reduce energy consumption and operational costs.
ContributorsKim, Ji Yeon (Author) / Kwon, Beomjin (Thesis advisor) / Wang, Robert (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2024