Numerical investigation on the heat transfer enhancement using micro/nano phase-change particulate flow

The introduction of phase change material fluid and nanofluid in micro-channel heat sink design can significantly increase the cooling capacity of the heat sink because of the unique features of these two kinds of fluids. To better assist the design of a high performance micro-channel heat sink using phase change fluid and nanofluid, the heat transfer enhancement mechanism behind the flow with such fluids must be completely understood. ^ A detailed parametric study is conducted to further investigate the heat transfer enhancement of the phase change material particle suspension flow, by using the two-phase non-thermal-equilibrium model developed by Hao and Tao (2004). The parametric study is conducted under normal conditions with Reynolds numbers of Re = 90–600 and phase change material particle concentrations of ϵp ≤ 0.25, as well as extreme conditions of very low Reynolds numbers (Re < 50) and high phase change material particle concentration (ϵp = 50%–70%) slurry flow. By using the two newly-defined parameters, named effectiveness factor ϵeff and performance index PI, respectively, it is found that there exists an optimal relation between the channel design parameters L and D, particle volume fraction ϵp, Reynolds number Re, and the wall heat flux qw. The influence of the particle volume fraction ϵp, particle size dp, and the particle viscosity μ p, to the phase change material suspension flow, are investigated and discussed. The model was validated by available experimental data. The conclusions will assist designers in making their decisions that relate to the design or selection of a micro-pump suitable for micro or mini scale heat transfer devices. ^ To understand the heat transfer enhancement mechanism of the nanofluid flow from the particle level, the lattice Boltzmann method is used because of its mesoscopic feature and its many numerical advantages. By using a two-component lattice Boltzmann model, the heat transfer enhancement of the nanofluid is analyzed, through incorporating the different forces acting on the nanoparticles to the two-component lattice Boltzmann model. It is found that the nanofluid has better heat transfer enhancement at low Reynolds numbers, and the Brownian motion effect of the nanoparticles will be weakened by the increase of flow speed. ^

Numerical Investigation on the Heat Transfer Enhancement Using Micro/Nano Phase-Change Particulate Flow

The introduction of phase change material fluid and nanofluid in micro-channel heat sink design can significantly increase the cooling capacity of the heat sink because of the unique features of these two kinds of fluids. To better assist the design of a high performance micro-channel heat sink using phase change fluid and nanofluid, the heat transfer enhancement mechanism behind the flow with such fluids must be completely understood. A detailed parametric study is conducted to further investigate the heat transfer enhancement of the phase change material particle suspension flow, by using the two-phase non-thermal-equilibrium model developed by Hao and Tao (2004). The parametric study is conducted under normal conditions with Reynolds numbers of Re=600-900 and phase change material particle concentrations ¡Ü0.25 , as well as extreme conditions of very low Reynolds numbers (Re < 50) and high phase change material particle concentration (0.5-0.7) slurry flow. By using the two newly-defined parameters, named effectiveness factor and performance index, respectively, it is found that there exists an optimal relation between the channel design parameters, particle volume fraction, Reynolds number, and the wall heat flux. The influence of the particle volume fraction, particle size, and the particle viscosity, to the phase change material suspension flow, are investigated and discussed. The model was validated by available experimental data. The conclusions will assist designers in making their decisions that relate to the design or selection of a micro-pump suitable for micro or mini scale heat transfer devices. To understand the heat transfer enhancement mechanism of the nanofluid flow from the particle level, the lattice Boltzmann method is used because of its mesoscopic feature and its many numerical advantages. By using a two-component lattice Boltzmann model, the heat transfer enhancement of the nanofluid is analyzed, through incorporating the different forces acting on the nanoparticles to the two-component lattice Boltzmann model. It is found that the nanofluid has better heat transfer enhancement at low Reynolds numbers, and the Brownian motion effect of the nanoparticles will be weakened by the increase of flow speed.

Life cycle of Deccan trap magma chambers: A crystal scale elemental and strontium isotopic investigation

The Deccan Trap basalts are the remnants of a massive series of lava flows that erupted at the K/T boundary and covered 1-2 million km2 of west-central India. This eruptive event is of global interest because of its possible link to the major mass extinction event, and there is much debate about the duration of this massive volcanic event. In contrast to isotopic or paleomagnetic dating methods, I explore an alternative approach to determine the lifecycle of the magma chambers that supplied the lavas, and extend the concept to obtain a tighter constraint on Deccan’s duration. My method relies on extracting time information from elemental and isotopic diffusion across zone boundaries in individual crystals. I determined elemental and Sr-isotopic variations across abnormally large (2-5 cm) plagioclase crystals from the Thalghat and Kashele “Giant Plagioclase Basalts” from the lowermost Jawhar and Igatpuri Formations respectively in the thickest Western Ghats section near Mumbai. I also obtained bulk rock major, trace and rare earth element chemistry of each lava flow from the two formations. Thalghat flows contain only 12% zoned crystals, with 87 Sr/86Sr ratios of 0.7096 in the core and 0.7106 in the rim, separated by a sharp boundary. In contrast, all Kashele crystals have a wider range of 87Sr/86Sr values, with multiple zones. Geochemical modeling of the data suggests that the two types of crystals grew in distinct magmatic environments. Modeling intracrystalline diffusive equilibration between the core and rim of Thalghat crystals led me to obtain a crystal growth rate of 2.03x10-10 cm/s and a residence time of 780 years for the crystals in the magma chamber(s). Employing some assumptions based on field and geochronologic evidence, I extrapolated this residence time to the entire Western Ghats and obtained an estimate of 25,000–35,000 years for the duration of Western Ghats volcanism. This gave an eruptive rate of 30–40 km3/yr, which is much higher than any presently erupting volcano. This result will remain speculative until a similarly detailed analytical-modeling study is performed for the rest of the Western Ghats formations.

Plasma and cold sprayed aluminum carbon nanotube composites: Quantification of nanotube distribution and multi-scale mechanical properties

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si prealloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al 4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^

Impact of Vegetable Preparation Method and Taste-Test on Vegetable Preference for First Grade Children in the United States

How children rate vegetables may be influenced by the preparation method. The primary objective of this study was for first grade students to be involved in a cooking demonstration and to taste and rate vegetables raw and cooked. First grade children of two classes (N= 52: 18 boys and 34 girls (approximately half Hispanic) that had assented and had signed parental consent participated in the study. The degree of liking a particular vegetable was recorded by the students using a hedonic scale of five commonly eaten vegetables tasted first raw (pre-demonstration) and then cooked (post-demonstration). A food habit questionnaire was filled out by parents to evaluate their mealtime practices and beliefs about their child’s eating habits. Paired sample t-tests revealed significant differences in preferences for vegetables in their raw and cooked states. Several mealtime characteristics were significantly associated with children’s vegetable preferences. Parents who reported being satisfied with how often the family eats evening meals together were more likely to report that their child eats adequate vegetables for their health (p=0.026). Parents who stated that they were satisfied with their child’s eating habits were more likely to report that their child was trying new foods (p<.001). Cooking demonstrations by nutrition professionals may be an important strategy that can be used by parents and teachers to promote vegetable intake. It is important that nutrition professionals provide guidance to encourage consumption of vegetables for parents so that they can model the behavior of healthy food consumption to their children.

Plasma And Cold Sprayed Aluminum Carbon Nanotube Composites: Quantification Of Nanotube Distribution And Multi-Scale Mechanical Properties

Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si pre-alloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

Life Cycle of Deccan Trap Magma Chambers: A Crystal Scale Elemental and Strontium Isotopic Investigation

The Deccan Trap basalts are the remnants of a massive series of lava flows that erupted at the K/T boundary and covered 1-2 million km2 of west-central India. This eruptive event is of global interest because of its possible link to the major mass extinction event, and there is much debate about the duration of this massive volcanic event. In contrast to isotopic or paleomagnetic dating methods, I explore an alternative approach to determine the lifecycle of the magma chambers that supplied the lavas, and extend the concept to obtain a tighter constraint on Deccan’s duration. My method relies on extracting time information from elemental and isotopic diffusion across zone boundary in an individual crystal. I determined elemental and Sr-isotopic variations across abnormally large (2-5 cm) plagioclase crystals from the Thalghat and Kashele “Giant Plagioclase Basalts” from the lowermost Jawhar and Igatpuri Formations respectively in the thickest Western Ghats section near Mumbai. I also obtained bulk rock major, trace and rare earth element chemistry of each lava flow from the two formations. Thalghat flows contain only 12% zoned crystals, with 87Sr/86Sr ratios of 0.7096 in the core and 0.7106 in the rim, separated by a sharp boundary. In contrast, all Kashele crystals have a wider range of 87Sr/86Sr values, with multiple zones. Geochemical modeling of the data suggests that the two types of crystals grew in distinct magmatic environments. Modeling intracrystalline diffusive equilibration between the core and rim of Thalghat crystals led me to obtain a crystal growth rate of 2.03x10-10 cm/s and a residence time of 780 years for the crystals in the magma chamber(s). Employing some assumptions based on field and geochronologic evidence, I extrapolated this residence time to the entire Western Ghats and obtained an estimate of 25,000 – 35,000 years for the duration of Western Ghats volcanism. This gave an eruptive rate of 30 – 40 km3/yr, which is much higher than any presently erupting volcano. This result will remain speculative until a similarly detailed analytical-modeling study is performed for the rest of the Western Ghats formations.

Meshfree Method for Prediction of Thermal Properties of Porous Ceramic Materials

In the presented thesis work, meshfree method with distance fields is applied to create a novel computational approach which enables inclusion of the realistic geometric models of the microstructure and liberates Finite Element Analysis(FEA) from thedependance on and limitations of meshing of fine microstructural feature such as splats and porosity.Manufacturing processes of ceramics produce materials with complex porosity microstructure.Geometry of pores, their size and location substantially affect macro scale physical properties of the material. Complex structure and geometry of the pores severely limit application of modern Finite Element Analysis methods because they require construction of spatial grids (meshes) that conform to the geometric shape of the structure. As a result, there are virtually no effective tools available for predicting overall mechanical and thermal properties of porous materials based on their microstructure. This thesis is a separate handling and controls of geometric and physical computational models that are seamlessly combined at solution run time. Using the proposedapproach we will determine the effective thermal conductivity tensor of real porous ceramic materials featuring both isotropic and anisotropic thermal properties. This work involved development and implementation of numerical algorithms, data structure, and software.