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.
Displaying 61 - 66 of 66
Description
Extensive efforts have been devoted to understanding material failure in the last several decades. A suitable numerical method and specific failure criteria are required for failure simulation. The finite element method (FEM) is the most widely used approach for material mechanical modelling. Since FEM is based on partial differential equations, it is hard to solve problems involving spatial discontinuities, such as fracture and material interface. Due to their intrinsic characteristics of integro-differential governing equations, discontinuous approaches are more suitable for problems involving spatial discontinuities, such as lattice spring method, discrete element method, and peridynamics. A recently proposed lattice particle method is shown to have no restriction of Poisson’s ratio, which is very common in discontinuous methods. In this study, the lattice particle method is adopted to study failure problems. In addition of numerical method, failure criterion is essential for failure simulations. In this study, multiaxial fatigue failure is investigated and then applied to the adopted method. Another critical issue of failure simulation is that the simulation process is time-consuming. To reduce computational cost, the lattice particle method can be partly replaced by neural network model.First, the development of a nonlocal maximum distortion energy criterion in the framework of a Lattice Particle Model (LPM) is presented for modeling of elastoplastic materials. The basic idea is to decompose the energy of a discrete material point into dilatational and distortional components, and plastic yielding of bonds associated with this material point is assumed to occur only when the distortional component reaches a critical value. Then, two multiaxial fatigue models are proposed for random loading and biaxial tension-tension loading, respectively. Following this, fatigue cracking in homogeneous and composite materials is studied using the lattice particle method and the proposed multiaxial fatigue model. Bi-phase material fatigue crack simulation is performed. Next, an integration of an efficient deep learning model and the lattice particle method is presented to predict fracture pattern for arbitrary microstructure and loading conditions. With this integration, computational accuracy and efficiency are both considered. Finally, some conclusion and discussion based on this study are drawn.
ContributorsWei, Haoyang (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Jiang, Hanqing (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2021
Description
Accurate knowledge and understanding of thermal conductivity is very important in awide variety of applications both at microscopic and macroscopic scales. Estimation,however varies widely with respect to scale and application. At a lattice level, calcu-lation of thermal conductivity of any particular alloy require very heavy computationeven for a relatively small number of atoms. This thesis aims to run conventionalmolecular dynamic simulations for a particular supercell and then employ a machinelearning based approach and compare the two in hopes of developing a method togreatly reduce computational costs as well as increase the scale and time frame ofthese systems. Conventional simulations were run using interatomic potentials basedon density function theory-basedab initiocalculations. Then deep learning neuralnetwork based interatomic potentials were used run similar simulations to comparethe two approaches.
ContributorsDabir, Anirudh (Author) / Zhuang, Houlong (Thesis advisor) / Nian, Qiong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
Damage and failure of advanced composite materials and structures are often manifestations of nonlinear deformation that involve multiple mechanisms and their interactions at the constituent length scale. The presence and interactions of inelastic microscale constituents strongly influence the macroscopic damage anisotropy and useful residual life. The mechano-chemical interactions between constituents at the atomistic length scale play a more critical role with nanoengineered composites. Therefore, it is desirable to link composite behavior to specific microscopic constituent properties explicitly and lower length scale features using high-fidelity multiscale modeling techniques.In the research presented in this dissertation, an atomistically-informed multiscale modeling framework is developed to investigate damage evolution and failure in composites with radially-grown carbon nanotube (CNT) architecture. A continuum damage mechanics (CDM) model for the radially-grown CNT interphase region is developed with evolution equations derived using atomistic simulations. The developed model is integrated within a high-fidelity generalized method of cells (HFGMC) micromechanics theory and is used to parametrically investigate the influence of various input micro and nanoscale parameters on the mechanical properties, such as elastic stiffness, strength, and toughness. In addition, the inter-fiber stresses and the onset of damage in the presence of the interphase region are investigated to better understand the energy dissipation mechanisms that attribute to the enhancement in the macroscopic out-of-plane strength and toughness. Note that the HFGMC theory relies heavily on the description of microscale features and requires many internal variables, leading to high computational costs. Therefore, a novel reduced-order model (ROM) is also developed to surrogate full-field nonlinear HFGMC simulations and decrease the computational time and memory requirements of concurrent multiscale simulations significantly.
The accurate prediction of composite sandwich materials' thermal stability and durability remains a challenge due to the variability of thermal-related material coefficients at different temperatures and the extensive use of bonded fittings. Consequently, the dissertation also investigates the thermomechanical performance of a complex composite sandwich space structure subject to thermal cycling. Computational finite element (FE) simulations are used to investigate the intrinsic failure mechanisms and damage precursors in honeycomb core composite sandwich structures with adhesively bonded fittings.
ContributorsVenkatesan, Karthik Rajan (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Yekani Fard, Masoud (Committee member) / Stoumbos, Tom (Committee member) / Arizona State University (Publisher)
Created2021
Description
Special thermal interface materials are required for connecting devices that operate at high temperatures up to 300°C. Because devices used in power electronics, such as GaN, SiC, and other wide bandgap semiconductors, can reach very high temperatures (beyond 250°C), a high melting point, and high thermal & electrical conductivity are required for the thermal interface material. Traditional solder materials for packaging cannot be used for these applications as they do not meet these requirements. Sintered nano-silver is a good candidate on account of its high thermal and electrical conductivity and very high melting point. The high temperature operating conditions of these devices lead to very high thermomechanical stresses that can adversely affect performance and also lead to failure. A number of these devices are mission critical and, therefore, there is a need for very high reliability. Thus, computational and nondestructive techniques and design methodology are needed to determine, characterize, and design the packages. Actual thermal cycling tests can be very expensive and time consuming. It is difficult to build test vehicles in the lab that are very close to the production level quality and therefore making comparisons or making predictions becomes a very difficult exercise. Virtual testing using a Finite Element Analysis (FEA) technique can serve as a good alternative. In this project, finite element analysis is carried out to help achieve this objective. A baseline linear FEA is performed to determine the nature and magnitude of stresses and strains that occur during the sintering step. A nonlinear coupled thermal and mechanical analysis is conducted for the sintering step to study the behavior more accurately and in greater detail. Damage and fatigue analysis are carried out for multiple thermal cycling conditions. The results are compared with the actual results from a prior study. A process flow chart outlining the FEA modeling process is developed as a template for the future work. A Coffin-Manson type relationship is developed to help determine the accelerated aging conditions and predict life for different service conditions.
ContributorsAmla, Tarun (Author) / Chawla, Nikhilesh (Thesis advisor) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Zhuang, Houlong (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2020
Description
Atmospheric water extraction (AWE) is an emerging technology to tackle water resource shortage challenges. One such approach to provide fresh water utilizes stimuli-responsive hydrogel-based desiccants to capture the moisture from the air and release it into the liquid form. Typical gel desiccants are composed of a hygroscopic agent for capturing and a hydrophilic gel matrix for storage. The desorption process can be completed by elevating the temperature above the upper or lower critical solution temperature point to initiate the volume phase transition of either thermo-responsive or photothermal types. This thesis focuses on investigating the structural effect of hydrogels on moisture uptake. Firstly, the main matrix of gel desiccant, poly(N-isopropylacrylamide) hydrogel, was optimized via tuning synthesis temperature and initial monomer concentration. Secondly, a series of hydrogel-based desiccants consisting of a hygroscopic material, vinyl imidazole, and optimized poly(N-isopropylacrylamide) gel matrix were synthesized with different network structures. The moisture uptake result showed that the gel desiccant with an interpenetrating polymeric network (IPN) resulted in the best-performing moisture capturing. The gel desiccant with the best performance will be used as a primary structural unit to evaluate the feasibility of developing a light-responsive gel desiccant to materialize light-trigger moisture desorption for AWE technology in the future.
ContributorsZhao, Xingbang (Author) / Dai, Lenore (Thesis advisor) / Westerhoff, Paul (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
Aluminum alloys are commonly used for engineering applications due to their high strength to weight ratio, low weight, and low cost. Pitting corrosion, accelerated by saltwater environments, leads to fatigue cracks and stress corrosion cracking during service. Two-dimensional (2D) characterization methods are typically used to identify and characterize corrosion; however, these methods are destructive and do not enable an efficient means of quantifying mechanisms of pit initiation and growth. In this study, lab-scale x-ray microtomography was used to non-destructively observe, quantify, and understand pit growth in three dimensions over a 20-day corrosion period in the AA7075-T651 alloy. The XRT process, capable of imaging sample volumes with a resolution near one micrometer, was found to be an ideal tool for large-volume pit examination. Pit depths were quantified over time using renderings of sample volumes, leading to an understanding of how inclusion particles, oxide breakdown, and corrosion mechanisms impact the growth and morphology of pits. This process, when carried out on samples produced with two different rolling directions and rolling extents, yielded novel insights into the long-term macroscopic corrosion behaviors impacted by alloy production and design. Key among these were the determinations that the alloy’s rolling direction produces a significant difference in the average growth rate of pits and that the corrosion product layer loses its passivating effect as a result of cyclic immersion. In addition, a new mechanism of pitting corrosion is proposed which is focused on the pseudo-random spatial distribution of iron-rich inclusion particles in the alloy matrix, which produces a random distribution of pit depths based on the occurrence of co-operative corrosion near inclusion clusters.
ContributorsSinclair, Daniel Ritchie (Author) / Chawla, Nikhilesh (Thesis director) / Jiao, Yang (Committee member) / Bale, Hrishikesh (Committee member) / School of International Letters and Cultures (Contributor) / Materials Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05