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- All Subjects: Mechanical Engineering
- Creators: Oswald, Jay
- Creators: Rykaczewski, Konrad
Description
Shock loading is a complex phenomenon that can lead to failure mechanisms such as strain localization, void nucleation and growth, and eventually spall fracture. Studying incipient stages of spall damage is of paramount importance to accurately determine initiation sites in the material microstructure where damage will nucleate and grow and to formulate continuum models that account for the variability of the damage process due to microstructural heterogeneity. The length scale of damage with respect to that of the surrounding microstructure has proven to be a key aspect in determining sites of failure initiation. Correlations have been found between the damage sites and the surrounding microstructure to determine the preferred sites of spall damage, since it tends to localize at and around the regions of intrinsic defects such as grain boundaries and triple points. However, considerable amount of work still has to be done in this regard to determine the physics driving the damage at these intrinsic weak sites in the microstructure. The main focus of this research work is to understand the physical mechanisms behind the damage localization at these preferred sites. A crystal plasticity constitutive model is implemented with different damage criteria to study the effects of stress concentration and strain localization at the grain boundaries. A cohesive zone modeling technique is used to include the intrinsic strength of the grain boundaries in the simulations. The constitutive model is verified using single elements tests, calibrated using single crystal impact experiments and validated using bicrystal and multicrystal impact experiments. The results indicate that strain localization is the predominant driving force for damage initiation and evolution. The microstructural effects on theses damage sites are studied to attribute the extent of damage to microstructural features such as grain orientation, misorientation, Taylor factor and the grain boundary planes. The finite element simulations show good correlation with the experimental results and can be used as the preliminary step in developing accurate probabilistic models for damage nucleation.
ContributorsKrishnan, Kapil (Author) / Peralta, Pedro (Thesis advisor) / Mignolet, Marc (Committee member) / Sieradzki, Karl (Committee member) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2013
Description
Recently, the use of zinc oxide (ZnO) nanowires as an interphase in composite materials has been demonstrated to increase the interfacial shear strength between carbon fiber and an epoxy matrix. In this research work, the strong adhesion between ZnO and carbon fiber is investigated to elucidate the interactions at the interface that result in high interfacial strength. First, molecular dynamics (MD) simulations are performed to calculate the adhesive energy between bare carbon and ZnO. Since the carbon fiber surface has oxygen functional groups, these were modeled and MD simulations showed the preference of ketones to strongly interact with ZnO, however, this was not observed in the case of hydroxyls and carboxylic acid. It was also found that the ketone molecules ability to change orientation facilitated the interactions with the ZnO surface. Experimentally, the atomic force microscope (AFM) was used to measure the adhesive energy between ZnO and carbon through a liftoff test by employing highly oriented pyrolytic graphite (HOPG) substrate and a ZnO covered AFM tip. Oxygen functionalization of the HOPG surface shows the increase of adhesive energy. Additionally, the surface of ZnO was modified to hold a negative charge, which demonstrated an increase in the adhesive energy. This increase in adhesion resulted from increased induction forces given the relatively high polarizability of HOPG and the preservation of the charge on ZnO surface. It was found that the additional negative charge can be preserved on the ZnO surface because there is an energy barrier since carbon and ZnO form a Schottky contact. Other materials with the same ionic properties of ZnO but with higher polarizability also demonstrated good adhesion to carbon. This result substantiates that their induced interaction can be facilitated not only by the polarizability of carbon but by any of the materials at the interface. The versatility to modify the magnitude of the induced interaction between carbon and an ionic material provides a new route to create interfaces with controlled interfacial strength.
ContributorsGalan Vera, Magdian Ulises (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2013
Description
The goal of this research is to compare the mechanical properties of CP-Ti and Ti-O and to understand the relationship between a material's microstructure and its response to fatigue. Titanium has been selected due to its desirable properties and applicability in several engineering fields. Both samples are polished and etched in order to visualize and characterize the microstructure and its features. The samples then undergo strain-controlled fatigue tests for several thousand cycles. Throughout testing, images of the samples are taken at zero and maximum load for DIC analysis. The DIC results can be used to study the local strains of the samples. The DIC analysis performed on the CP-Ti sample and presented in this study will be used to understand how the addition of oxygen in the Ti-O impacts fatigue response. The outcome of this research can be used to develop long-lasting, high strength materials.
ContributorsRiley, Erin Ashland (Author) / Solanki, Kiran (Thesis director) / Oswald, Jay (Committee member) / School of Art (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
In nature, it is commonly observed that animals and birds perform movement-based thermoregulation activities to regulate their body temperatures. For example, flapping of elephant ears or plumage fluffing in birds. Taking inspiration from nature and to explore the possibilities of such heat transfer enhancements, augmentation of heat transfer rates induced by the vibration of solid and well as novel flexible pinned heatsinks were studied in this research project. Enhancement of natural convection has always been very important in improving the performance of the cooling mechanisms. In this research, flexible heatsinks were developed and they were characterized based on natural convection cooling with moderately vibrating conditions. The vibration of heated surfaces such as motor surfaces, condenser surfaces, robotic arms and exoskeletons led to the motivation of the development of heat sinks having flexible fins with an improved heat transfer capacity. The performance of an inflexible, solid copper pin fin heat sink was considered as the baseline, current industry standard for the thermal performance. It is expected to obtain maximum convective heat transfer at the resonance frequency of the flexible pin fins. Current experimental results with fixed input frequency and varying amplitudes indicate that the vibration provides a moderate improvement in convective heat transfer, however, the flexibility of fins had negligible effects.
ContributorsPrabhu, Saurabh (Author) / Rykaczewski, Konrad (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
An approach for modeling resistance spot welding of thin-gauge, dissimilar metal sheets with high electrical conductivity is presented in this work. In this scenario, the electrical and thermal contact resistances play a dominant role in heat generation and temperature evolution within the workpieces; these interactions ultimately control the weld geometry. Existing models are limited in modeling these interactions, especially for dissimilar and thin-gauge metal sheets, and at higher temperatures when the multiphysics becomes increasingly interdependent. The approach presented here uses resistivity measurements, combined with thermal modeling and known bulk resistance relationships to infer the relationship between electrical contact resistance and temperature for each of the different material interfaces in the welding process. Corresponding thermal contact resistance models are developed using the Wiedemann-Franz law combined with a scaling factor to account for nonmetallic behavior. Experimental and simulation voltage histories and final weld diameter were used to validate this model for a Cu/Al/Cu and a Cu/Al/Cu/Al/Cu stack-ups. This model was then used to study the effect of Ni-P coating on resistance spot welding of Cu and Al sheets in terms of weld formation, mechanical deformation, and contact resistance. Contact resistance and current density distribution are highly dependent on contact pressure and temperature distribution at the Cu/Al interface in the presence of alumina. The Ni-P coating helps evolve a partially-bonded donut shaped weld into a fully-bonded hourglass-shaped weld by decreasing the dependence of contact resistance and current density distribution on contact pressure and temperature distribution at the Cu/Al interface. This work also provides an approach to minimize distortion due to offset-rolling in thin aluminum sheets by optimizing the stiffening feature geometry. The distortion is minimized using particle swarm optimization. The objective function is a function of distortion and smallest radius of curvature in the geometry. Doubling the minimum allowable radius of curvature nearly doubles the reduction in distortion from the stadium shape for a quarter model. Reduction in distortion in the quarter model extends to the full-scale model with the best design performing 5.3% and 27% better than the corresponding nominal design for a quarter and full-scale model, respectively.
ContributorsVeeresh, Pawan (Author) / Oswald, Jay (Thesis advisor) / Carlson, Blair (Committee member) / Hoover, Christian (Committee member) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2022
Description
In convective heat transfer processes, heat transfer rate increases generally with a large fluid velocity, which leads to complex flow patterns. However, numerically analyzing the complex transport process and conjugated heat transfer requires extensive time and computing resources. Recently, data-driven approach has risen as an alternative method to solve physical problems in a computational efficient manner without necessitating the iterative computations of the governing physical equations. However, the research on data-driven approach for convective heat transfer is still in nascent stage. This study aims to introduce data-driven approaches for modeling heat and mass convection phenomena. As the first step, this research explores a deep learning approach for modeling the internal forced convection heat transfer problems. Conditional generative adversarial networks (cGAN) are trained to predict the solution based on a graphical input describing fluid channel geometries and initial flow conditions. A trained cGAN model rapidly approximates the flow temperature, Nusselt number (Nu) and friction factor (f) of a flow in a heated channel over Reynolds number (Re) ranging from 100 to 27750. The optimized cGAN model exhibited an accuracy up to 97.6% when predicting the local distributions of Nu and f. Next, this research introduces a deep learning based surrogate model for three-dimensional (3D) transient mixed convention in a horizontal channel with a heated bottom surface. Conditional generative adversarial networks (cGAN) are trained to approximate the temperature maps at arbitrary channel locations and time steps. The model is developed for a mixed convection occurring at the Re of 100, Rayleigh number of 3.9E6, and Richardson number of 88.8. The cGAN with the PatchGAN based classifier without the strided convolutions infers the temperature map with the best clarity and accuracy.
Finally, this study investigates how machine learning analyzes the mass transfer in 3D printed fluidic devices. Random forests algorithm is hired to classify the flow images taken from semi-transparent 3D printed tubes. Particularly, this work focuses on laminar-turbulent transition process occurring in a 3D wavy tube and a straight tube visualized by dye injection. The machine learning model automatically classifies experimentally obtained flow images with an accuracy > 0.95.
ContributorsKang, Munku (Author) / Kwon, Beomjin (Thesis advisor) / Phelan, Patrick (Committee member) / Ren, Yi (Committee member) / Rykaczewski, Konrad (Committee member) / Sohn, SungMin (Committee member) / Arizona State University (Publisher)
Created2022
Description
The thermal conductivity of cadmium sulfide (CdS) colloidal nanocrystals (NCs) and magic-sized clusters (MSCs) have been investigated in this work. It is well documented in the literature that the thermal conductivity of colloidal nanocrystal assemblies decreases as diameter decreases. However, the extrapolation of this size dependence does not apply to magic-sized clusters. Magic-sized clusters have an anomalously high thermal conductivity relative to the extrapolated size-dependence trend line for the colloidal nanocrystals. This anomalously high thermal conductivity could probably result from the monodispersity of magic-sized clusters. To support this conjecture, a method of deliberately eliminating the monodispersity of MSCs by mixing them with colloidal nanocrystals was performed. Experiment results showed that mixtures of nanocrystals and MSCs have a lower thermal conductivity that falls approximately on the extrapolated trendline for colloidal nanocrystal thermal conductivity as a function of size.
ContributorsSun, Ming-Hsien (Author) / Wang, Robert (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2022
Description
Windows are one of the most significant locations of heat transfer through a building envelope. In warm climates, it is important that heat gain through windows is minimized. Heat transfer through a window glazing occurs by all major forms of heat transfer (convection, conduction, and radiation). Convection and conduction effects can be limited by manipulating the thermal properties of a window’s construction. However, radiation heat transfer into a building will always occur if a window glazing is visibly transparent. In an effort to reduce heat gain through the building envelope, a window glazing can be designed with spectrally selective properties. These spectrally selective glazings would possess high reflectivity in the near-infrared (NIR) regime (to prevent solar heat gain) and high emissivity in the atmospheric window, 8-13μm (to take advantage of the radiative sky cooling effect). The objective of this thesis is to provide a comprehensive study of the thermal performance of a visibly transparent, high-emissivity glass window. This research proposes a window constructed by coating soda lime glass in a dual layer consisting of Indium Tin Oxide (ITO) and Polyvinyl Fluoride (PVF) film. The optical properties of this experimental glazing were measured and demonstrated high reflectivity in the NIR regime and high emissivity in the atmospheric window. Outdoor field tests were performed to experimentally evaluate the glazing’s thermal performance. The thermal performance was assessed by utilizing an experimental setup intended to mimic a building with a skylight. The proposed glazing experimentally demonstrated reduced indoor air temperatures compared to bare glass, ITO coated glass, and PVF coated glass. A theoretical heat transfer model was developed to validate the experimental results. The results of the theoretical and experimental models showed good agreement. On average, the theoretical model demonstrated 0.44% percent error during the daytime and 0.52% percent error during the nighttime when compared to the experimentally measured temperature values.
ContributorsTrujillo, Antonio Jose (Author) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2022
Description
Dehumidifiers are ubiquitous and essential household appliances in many parts of the world. They are used extensively in tropical and sub-tropical environments to lower humidity in living spaces, where high ambient humidity can lead to numerous negative health effects from mild physical discomfort to more serious conditions such as mold build up in structures and dangerous illnesses in humans. Most common dehumidifiers are based on conventional mechanical refrigeration cycles, where the effects of condensation heat transfer play a critical role in their effectiveness. In these devices, humid ambient air flows over a cold evaporator, which lowers the temperature of the humid ambient air below its dew point temperature and therefore decreases its water content by causing liquid water condensation on the evaporator surface. The rate at which humidity can be extracted from the ambient air is governed in part by how quickly the evaporator can shed the condensed droplets. Recent advances in soft, stretchable, thermally enhanced (through the addition of liquid metals) silicone tubing offer the potential to use these stretchable tubes in place of conventional copper pipe for applications such as dehumidification. Copper is a common material choice for dehumidifier evaporator tubing owing to its ubiquity and its high thermal conductivity, but it has several thermal downsides. Specifically, copper tubes remain static and typically rely on gravity alone to remove water droplets when they reach a sufficient mass. Additionally, copper’s naturally hydrophilic surface promotes film-wise condensation, which is substantially less effective than dropwise condensation. In contrast to copper, thermally enhanced soft stretchable tubes have naturally hydrophobic surfaces that promote the more effective dropwise condensation mode and a soft surface that offers higher nucleation density. However, soft surfaces also increase droplet pinning, which inhibits their departure. This work experimentally explores the effects of periodic axial stretching and retraction of soft tubing internally cooled with water on droplet condensation dynamics on its exterior surface. Results are discussed in terms of overall system thermal performance and real-time condensation imaging. An overall null result is discovered, and recommendations for future experiments are made.
Contributorsnordstog, thomas (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Devasenathipathy, Shankar (Committee member) / Arizona State University (Publisher)
Created2022
Description
Spray flows are important in a myriad of practical applications including fuel injection, ink-jet printing, agricultural sprays, and industrial processes. Two-phase sprays find particular use for spot cooling applications with high heat fluxes as in casting processes and power electronics. Computability of sprays in a cost-effective manner provides a path to optimize the design of nozzles to tune the spray characteristics for the needs of a particular application. Significant research has so far been devoted to understand and characterize spray flows better, be it from a theoretical, experimental or computational standpoint. The current thesis discusses a methodology for modeling primary atomization using the Quadratic Formula which is derived from an integral formulation of the governing equations. The framework is then applied to different examples of flat-fan hydraulic sprays. For each case, the spray is first resolved as a continuous fluid using the volume of fluid method. Atomization criterion is then applied to the velocity flow-field to determine the sites for primary atomization. At each site, local diameters for particle injection is determined using the quadratic formula. The trajectory of injected particles are then monitored through a particle tracking algorithm. The results from the numerical analysis are compared with experimental data to validate the computational framework.
ContributorsBhardwaj, Angshuman (Author) / Lee, T.-W. (Thesis advisor) / Herrmann, Marcus (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2022