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 1 - 10 of 103
Description
Production from a high pressure gas well at a high production-rate encounters the risk of operating near the choking condition for a compressible flow in porous media. The unbounded gas pressure gradient near the point of choking, which is located near the wellbore, generates an effective tensile stress on the porous rock frame. This tensile stress almost always exceeds the tensile strength of the rock and it causes a tensile failure of the rock, leading to wellbore instability. In a porous rock, not all pores are choked at the same flow rate, and when just one pore is choked, the flow through the entire porous medium should be considered choked as the gas pressure gradient at the point of choking becomes singular. This thesis investigates the choking condition for compressible gas flow in a single microscopic pore. Quasi-one-dimensional analysis and axisymmetric numerical simulations of compressible gas flow in a pore scale varicose tube with a number of bumps are carried out, and the local Mach number and pressure along the tube are computed for the flow near choking condition. The effects of tube length, inlet-to-outlet pressure ratio, the number of bumps and the amplitude of the bumps on the choking condition are obtained. These critical values provide guidance for avoiding the choking condition in practice.
ContributorsYuan, Jing (Author) / Chen, Kangping (Thesis advisor) / Wang, Liping (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.
ContributorsHensberry, Kevin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012
Description
Aluminum alloys and their composites are attractive materials for applications requiring high strength-to-weight ratios and reasonable cost. Many of these applications, such as those in the aerospace industry, undergo fatigue loading. An understanding of the microstructural damage that occurs in these materials is critical in assessing their fatigue resistance. Two distinct experimental studies were performed to further the understanding of fatigue damage mechanisms in aluminum alloys and their composites, specifically fracture and plasticity. Fatigue resistance of metal matrix composites (MMCs) depends on many aspects of composite microstructure. Fatigue crack growth behavior is particularly dependent on the reinforcement characteristics and matrix microstructure. The goal of this work was to obtain a fundamental understanding of fatigue crack growth behavior in SiC particle-reinforced 2080 Al alloy composites. In situ X-ray synchrotron tomography was performed on two samples at low (R=0.1) and at high (R=0.6) R-ratios. The resulting reconstructed images were used to obtain three-dimensional (3D) rendering of the particles and fatigue crack. Behaviors of the particles and crack, as well as their interaction, were analyzed and quantified. Four-dimensional (4D) visual representations were constructed to aid in the overall understanding of damage evolution. During fatigue crack growth in ductile materials, a plastic zone is created in the region surrounding the crack tip. Knowledge of the plastic zone is important for the understanding of fatigue crack formation as well as subsequent growth behavior. The goal of this work was to quantify the 3D size and shape of the plastic zone in 7075 Al alloys. X-ray synchrotron tomography and Laue microdiffraction were used to non-destructively characterize the volume surrounding a fatigue crack tip. The precise 3D crack profile was segmented from the reconstructed tomography data. Depth-resolved Laue patterns were obtained using differential-aperture X-ray structural microscopy (DAXM), from which peak-broadening characteristics were quantified. Plasticity, as determined by the broadening of diffracted peaks, was mapped in 3D. Two-dimensional (2D) maps of plasticity were directly compared to the corresponding tomography slices. A 3D representation of the plastic zone surrounding the fatigue crack was generated by superimposing the mapped plasticity on the 3D crack profile.
ContributorsHruby, Peter (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
ContributorsHasan, Zeaid (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
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
The focus of this investigation is on the formulation and a validation of reduced order models (ROMs) for the prediction of the response of structures with embedded piezoelectric actuators. The ROMs considered here are those constructed in a nonintrusive manner from a commercial finite element software, NASTRAN is adopted here. Notwithstanding the popularity of piezoelectric materials in structural dynamics related applications such as structural health monitoring and energy harvesting, not all commercial finite element software allow directly their modeling. In such cases, e.g., with NASTRAN, one can proceed with an analogy and replace the electric actuation in the piezoelectric material by a fictitious thermal effect producing the same strain. This process recasts the determination of a ROM for a structure with embedded piezoelectric actuator into a similar ROM but for a heated structure, the framework of which has recently been developed. Yet, the temperature field resulting from the analogy would be quite different from the one considered in past effort and would excite a broad array of structural modes. Accordingly, as a preamble to considering a beam with a piezoelectric layer, a simpler plate model is considered that is subjected to a uniform temperature but a complex pressure loading that excites the entire set of modes of the plate in the broad frequency band considered. The very good match of the predictions obtained by this ROM in comparison to their full finite element counterparts provides the necessary confidence to next address a beam with embedded piezoelectic actuator. The test model considered for this validation is a built-up nano beam analyzed recently in nonlinear geometric conditions by full finite elements and by a non-intrusive ROM procedure under harmonic variations of the piezoelectic voltage. This structural model and its loading conditions are very different from those considered in past applications of nonintrusive ROMs, thus the excellent results obtained here provide further support of the broad generality of the nonintrusive ROM methodology, including of the appropriateness of the "dual modes" basis functions.
ContributorsVyas, Varun (Author) / Mignolet, Marc (Thesis advisor) / Hollkamp, Joseph (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
Nanostructured materials show signicant enhancement in the thermoelectric g-
ure of merit (zT) due to quantum connement eects. Improving the eciency of
thermoelectric devices allows for the development of better, more economical waste
heat recovery systems. Such systems may be used as bottoming or co-generation
cycles in conjunction with conventional power cycles to recover some of the wasted
heat. Thermal conductivity measurement systems are an important part of the char-
acterization processes of thermoelectric materials. These systems must possess the
capability of accurately measuring the thermal conductivity of both bulk and thin-lm
samples at dierent ambient temperatures.
This paper discusses the construction, validation, and improvement of a thermal
conductivity measurement platform based on the 3-Omega technique. Room temperature
measurements of thermal conductivity done on control samples with known properties
such as undoped bulk silicon (Si), bulk gallium arsenide (GaAs), and silicon dioxide
(SiO2) thin lms yielded 150 W=m􀀀K, 50 W=m􀀀K, and 1:46 W=m􀀀K respectively.
These quantities were all within 8% of literature values. In addition, the thermal
conductivity of bulk SiO2 was measured as a function of temperature in a Helium-
4 cryostat from 75K to 250K. The results showed good agreement with literature
values that all fell within the error range of each measurement. The uncertainty in
the measurements ranged from 19% at 75K to 30% at 250K. Finally, the system
was used to measure the room temperature thermal conductivity of a nanocomposite
composed of cadmium selenide, CdSe, nanocrystals in an indium selenide, In2Se3,
matrix as a function of the concentration of In2Se3. The observed trend was in
qualitative agreement with the expected behavior.
i
ure of merit (zT) due to quantum connement eects. Improving the eciency of
thermoelectric devices allows for the development of better, more economical waste
heat recovery systems. Such systems may be used as bottoming or co-generation
cycles in conjunction with conventional power cycles to recover some of the wasted
heat. Thermal conductivity measurement systems are an important part of the char-
acterization processes of thermoelectric materials. These systems must possess the
capability of accurately measuring the thermal conductivity of both bulk and thin-lm
samples at dierent ambient temperatures.
This paper discusses the construction, validation, and improvement of a thermal
conductivity measurement platform based on the 3-Omega technique. Room temperature
measurements of thermal conductivity done on control samples with known properties
such as undoped bulk silicon (Si), bulk gallium arsenide (GaAs), and silicon dioxide
(SiO2) thin lms yielded 150 W=m􀀀K, 50 W=m􀀀K, and 1:46 W=m􀀀K respectively.
These quantities were all within 8% of literature values. In addition, the thermal
conductivity of bulk SiO2 was measured as a function of temperature in a Helium-
4 cryostat from 75K to 250K. The results showed good agreement with literature
values that all fell within the error range of each measurement. The uncertainty in
the measurements ranged from 19% at 75K to 30% at 250K. Finally, the system
was used to measure the room temperature thermal conductivity of a nanocomposite
composed of cadmium selenide, CdSe, nanocrystals in an indium selenide, In2Se3,
matrix as a function of the concentration of In2Se3. The observed trend was in
qualitative agreement with the expected behavior.
i
ContributorsJaber, Abbas (Author) / Wang, Robert (Thesis advisor) / Wang, Liping (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2014
Description
The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
ContributorsYuan, Rui (Author) / Oswald, Jay (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Solanki, Kiran (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
The rapid progress of solution-phase synthesis has led colloidal nanocrystals one of the most versatile nanoscale materials, provided opportunities to tailor material's properties, and boosted related technological innovations. Colloidal nanocrystal-based materials have been demonstrated success in a variety of applications, such as LEDs, electronics, solar cells and thermoelectrics. In each of these applications, the thermal transport property plays a big role. An undesirable temperature rise due to inefficient heat dissipation could lead to deleterious effects on devices' performance and lifetime. Hence, the first project is focused on investigating the thermal transport in colloidal nanocrystal solids. This study answers the question that how the molecular structure of nanocrystals affect the thermal transport, and provides insights for future device designs. In particular, PbS nanocrystals is used as a monitoring system, and the core diameter, ligand length and ligand binding group are systematically varied to study the corresponding effect on thermal transport.
Next, a fundamental study is presented on the phase stability and solid-liquid transformation of metallic (In, Sn and Bi) colloidal nanocrystals. Although the phase change of nanoparticles has been a long-standing research topic, the melting behavior of colloidal nanocrytstals is largely unexplored. In addition, this study is of practical importance to nanocrystal-based applications that operate at elevated temperatures. Embedding colloidal nanocrystals into thermally-stable polymer matrices allows preserving nanocrystal size throughout melt-freeze cycles, and therefore enabling observation of stable melting features. Size-dependent melting temperature, melting enthalpy and melting entropy have all been measured and discussed.
In the next two chapters, focus has been switched to developing colloidal nanocrystal-based phase change composites for thermal energy storage applications. In Chapter 4, a polymer matrix phase change nanocomposite has been created. In this composite, the melting temperature and energy density could be independently controlled by tuning nanocrystal diameter and volume fractions. In Chapter 5, a solution-phase synthesis on metal matrix-metal nanocrytal composite is presented. This approach enables excellent morphological control over nanocrystals and demonstrated a phase change composite with a thermal conductivity 2 - 3 orders of magnitude greater than typical phase change materials, such as organics and molten salts.
Next, a fundamental study is presented on the phase stability and solid-liquid transformation of metallic (In, Sn and Bi) colloidal nanocrystals. Although the phase change of nanoparticles has been a long-standing research topic, the melting behavior of colloidal nanocrytstals is largely unexplored. In addition, this study is of practical importance to nanocrystal-based applications that operate at elevated temperatures. Embedding colloidal nanocrystals into thermally-stable polymer matrices allows preserving nanocrystal size throughout melt-freeze cycles, and therefore enabling observation of stable melting features. Size-dependent melting temperature, melting enthalpy and melting entropy have all been measured and discussed.
In the next two chapters, focus has been switched to developing colloidal nanocrystal-based phase change composites for thermal energy storage applications. In Chapter 4, a polymer matrix phase change nanocomposite has been created. In this composite, the melting temperature and energy density could be independently controlled by tuning nanocrystal diameter and volume fractions. In Chapter 5, a solution-phase synthesis on metal matrix-metal nanocrytal composite is presented. This approach enables excellent morphological control over nanocrystals and demonstrated a phase change composite with a thermal conductivity 2 - 3 orders of magnitude greater than typical phase change materials, such as organics and molten salts.
ContributorsLiu, Minglu (Author) / Wang, Robert Y (Thesis advisor) / Wang, Liping (Committee member) / Rykaczewski, Konrad (Committee member) / Phelan, Patrick (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2015