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Description
Many physical phenomena and industrial applications involve multiphase fluid flows and hence it is of high importance to be able to simulate various aspects of these flows accurately. The Dynamic Contact Angles (DCA) and the contact lines at the wall boundaries are a couple of such important aspects. In the past few decades, many mathematical models were developed for predicting the contact angles of the inter-face with the wall boundary under various flow conditions. These models are used to incorporate the physics of DCA and contact line motion in numerical simulations using various interface capturing/tracking techniques. In the current thesis, a simple approach to incorporate the static and dynamic contact angle boundary conditions using the level set method is developed and implemented in multiphase CFD codes, LIT (Level set Interface Tracking) (Herrmann (2008)) and NGA (flow solver) (Desjardins et al (2008)). Various DCA models and associated boundary conditions are reviewed. In addition, numerical aspects such as the occurrence of a stress singularity at the contact lines and grid convergence of macroscopic interface shape are dealt with in the context of the level set approach.
ContributorsPendota, Premchand (Author) / Herrmann, Marcus (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Waste heat energy conversion remains an inviting subject for research, given the renewed emphasis on energy efficiency and carbon emissions reduction. Solid-state thermoelectric devices have been widely investigated, but their practical application remains challenging because of cost and the inability to fabricate them in geometries that are easily compatible with heat sources. An intriguing alternative to solid-state thermoelectric devices is thermogalvanic cells, which include a generally liquid electrolyte that permits the transport of ions. Thermogalvanic cells have long been known in the electrochemistry community, but have not received much attention from the thermal transport community. This is surprising given that their performance is highly dependent on controlling both thermal and mass (ionic) transport. This research will focus on a research project, which is an interdisciplinary collaboration between mechanical engineering (i.e. thermal transport) and chemistry, and is a largely experimental effort aimed at improving fundamental understanding of thermogalvanic systems. The first part will discuss how a simple utilization of natural convection within the cell doubles the maximum power output of the cell. In the second part of the research, some of the results from the previous part will be applied in a feasibility study of incorporating thermogalvanic waste heat recovery systems into automobiles. Finally, a new approach to enhance Seebeck coefficient by tuning the configurational entropy of a mixed-ligand complex formation of copper sulfate aqueous electrolytes will be presented. Ultimately, a summary of these results as well as possible future work that can be formed from these efforts is discussed.
ContributorsGunawan, Andrey (Author) / Phelan, Patrick E (Thesis advisor) / Buttry, Daniel A (Committee member) / Mujica, Vladimiro (Committee member) / Chan, Candace K. (Committee member) / Wang, Robert Y (Committee member) / Arizona State University (Publisher)
Created2015
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
Uranium Dioxide (UO2) is a significant nuclear fission fuel, which is widely used
in nuclear reactors. Understanding the influence of microstructure on thermo-mechanical behavior of UO2 is extremely important to predict its performance. In particular, evaluating mechanical properties, such as elasticity, plasticity and creep at sub-grain length scales is key to developing this understanding as well as building multi-scale models of fuel behavior with predicting capabilities. In this work, modeling techniques were developed to study effects of microstructure on Young’s modulus, which was selected as a key representative property that affects overall mechanical behavior, using experimental data obtained from micro-cantilever bending testing as benchmarks. Beam theory was firstly introduced to calculate Young's modulus of UO2 from the experimental data and then three-dimensional finite element models of the micro-cantilever beams were constructed to simulate bending tests in UO2 at room temperature. The influence of the pore distribution was studied to explain the discrepancy between predicted values and experimental results. Results indicate that results of tests are significantly affected by porosity given that both pore size and spacing in the samples are of the order of the micro-beam dimensions. Microstructure reconstruction was conducted with images collected from three-dimensional serial sectioning using focused ion beam (FIB) and electron backscattering diffraction (EBSD) and pore clusters were placed at different locations along the length of the beam. Results indicate that the presence of pore clusters close to the substrate, i.e., the clamp of the micro-cantilever beam, has the strongest effect on load-deflection behavior, leading to a reduction of stiffness that is the largest for any location of the pore cluster. Furthermore, it was also found from both numerical and i
analytical models that pore clusters located towards the middle of the span and close to the end of the beam only have a very small effect on the load-deflection behavior, and it is concluded that better estimates of Young's modulus can be obtained from micro- cantilever experiments by using microstructurally explicit models that account for porosity in about one half of the beam length close to the clamp. This, in turn, provides an avenue to simplify micro-scale experiments and their analysis.
in nuclear reactors. Understanding the influence of microstructure on thermo-mechanical behavior of UO2 is extremely important to predict its performance. In particular, evaluating mechanical properties, such as elasticity, plasticity and creep at sub-grain length scales is key to developing this understanding as well as building multi-scale models of fuel behavior with predicting capabilities. In this work, modeling techniques were developed to study effects of microstructure on Young’s modulus, which was selected as a key representative property that affects overall mechanical behavior, using experimental data obtained from micro-cantilever bending testing as benchmarks. Beam theory was firstly introduced to calculate Young's modulus of UO2 from the experimental data and then three-dimensional finite element models of the micro-cantilever beams were constructed to simulate bending tests in UO2 at room temperature. The influence of the pore distribution was studied to explain the discrepancy between predicted values and experimental results. Results indicate that results of tests are significantly affected by porosity given that both pore size and spacing in the samples are of the order of the micro-beam dimensions. Microstructure reconstruction was conducted with images collected from three-dimensional serial sectioning using focused ion beam (FIB) and electron backscattering diffraction (EBSD) and pore clusters were placed at different locations along the length of the beam. Results indicate that the presence of pore clusters close to the substrate, i.e., the clamp of the micro-cantilever beam, has the strongest effect on load-deflection behavior, leading to a reduction of stiffness that is the largest for any location of the pore cluster. Furthermore, it was also found from both numerical and i
analytical models that pore clusters located towards the middle of the span and close to the end of the beam only have a very small effect on the load-deflection behavior, and it is concluded that better estimates of Young's modulus can be obtained from micro- cantilever experiments by using microstructurally explicit models that account for porosity in about one half of the beam length close to the clamp. This, in turn, provides an avenue to simplify micro-scale experiments and their analysis.
ContributorsGong, Bowen (Author) / Peralta, Pedro (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2015
Description
Pavement surface temperature is calculated using a fundamental energy balance model developed previously. It can be studied using a one-dimensional mathematical model. The input to the model is changed, to study the effect of different properties of pavement on its diurnal surface temperatures. It is observed that the pavement surface temperature has a microclimatic effect on the air temperature above it. A major increase in local air temperature is caused by heating of solid surfaces in that locality. A case study was done and correlations have been established to calculate the air temperature above a paved surface. Validation with in-situ pavement surface and air temperatures were made. Experimental measurement for the city of Phoenix shows the difference between the ambient air temperature of the city and the microclimatic air temperature above the pavement is approximately 10 degrees Fahrenheit. One mitigation strategy that has been explored is increasing the albedo of the paved surface. Although it will reduce the pavement surface temperature, leading to a reduction in air temperature close to the surface, the increased pavement albedo will also result in greater reflected solar radiation directed towards the building, thus increasing the building solar load. The first effect will imply a reduction in the building energy consumption, while the second effect will imply an increase in the building energy consumption. Simulation is done using the EnergyPlus tool, to find the microclimatic effect of pavement on the building energy performance. The results indicate the cooling energy savings of an office building for different types of pavements can be variable as much as 30%.
ContributorsSengupta, Shawli (Author) / Phelan, Patrick (Thesis advisor) / Kaloush, Kamil (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2015
Description
The demand for miniaturized components with feature sizes as small as tens of microns and tolerances as small as 0.1 microns is on the rise in the fields of aerospace, electronics, optics and biomedical engineering. Micromilling has proven to be a process capable of generating the required accuracy for these features and is an alternative to various non-mechanical micro-manufacturing processes which are limited in terms of cost and productivity, especially at the micro-meso scale. The micromilling process is on the surface, a miniaturized version of conventional milling, hence inheriting its benefits. However, the reduction in scale by a few magnitudes makes the process peculiar and unique; and the macro-scale theories have failed to successfully explain the micromilling process and its machining parameters. One such characteristic is the unpredictable nature of tool wear and breakage. There is a large cost benefit that can be realized by improving tool life. Workpiece rejection can also be reduced by successfully monitoring the condition of the tool to avoid issues. Many researchers have developed Tool Condition Monitoring and Tool Wear Modeling systems to address the issue of tool wear, and to obtain new knowledge. In this research, a tool wear modeling effort is undertaken with a new approach. A new tool wear signature is used for real-time data collection and modeling of tool wear. A theoretical correlation between the number of metal chips produced during machining and the condition of the tool is introduced. Experimentally, it is found that the number of chips produced drops with respect to the feedrate of the cutting process i.e. when the uncut chip thickness is below the theoretical minimum chip thickness.
ContributorsBajaj, Anuj Kishorkumar (Author) / SODEMANN, ANGELA A (Thesis advisor) / Bekki, Jeniffer (Committee member) / Hsu, Keng (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
Description
Design problem formulation is believed to influence creativity, yet it has received only modest attention in the research community. Past studies of problem formulation are scarce and often have small sample sizes. The main objective of this research is to understand how problem formulation affects creative outcome. Three research areas are investigated: development of a model which facilitates capturing the differences among designers' problem formulation; representation and implication of those differences; the relation between problem formulation and creativity.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
ContributorsDinar, Mahmoud (Author) / Shah, Jami J. (Thesis advisor) / Langley, Pat (Committee member) / Davidson, Joseph K. (Committee member) / Lande, Micah (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Hydrogen embrittlement (HE) is a phenomenon that affects both the physical and chemical properties of several intrinsically ductile metals. Consequently, understanding the mechanisms behind HE has been of particular interest in both experimental and modeling research. Discrepancies between experimental observations and modeling results have led to various proposals for HE mechanisms. Therefore, to gain insights into HE mechanisms in iron, this dissertation aims to investigate several key issues involving HE such as: a) the incipient crack tip events; b) the cohesive strength of grain boundaries (GBs); c) the dislocation-GB interactions and d) the dislocation mobility.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
ContributorsAdlakha, Ilaksh (Author) / Solanki, Kiran (Thesis advisor) / Mignolet, Marc (Committee member) / Chawla, Nikhilesh (Committee member) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2015
Description
Nanoparticle suspensions, popularly termed “nanofluids,” have been extensively investigated for their thermal and radiative properties. Such work has generated great controversy, although it is arguably accepted today that the presence of nanoparticles rarely leads to useful enhancements in either thermal conductivity or convective heat transfer. On the other hand, there are still examples of unanticipated enhancements to some properties, such as the reported specific heat of molten salt-based nanofluids and the critical heat flux. Another largely overlooked example is the apparent effect of nanoparticles on the effective latent heat of vaporization (hfg) of aqueous nanofluids. A previous study focused on molecular dynamics (MD) modeling supplemented with limited experimental data to suggest that hfg increases with increasing nanoparticle concentration.
Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.
Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.
ContributorsLee, Soochan (Author) / Phelan, Patrick E (Thesis advisor) / Wu, Carole-Jean (Thesis advisor) / Wang, Robert (Committee member) / Wang, Liping (Committee member) / Taylor, Robert A. (Committee member) / Prasher, Ravi (Committee member) / Arizona State University (Publisher)
Created2015