A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and their respective temperatures established simultaneously. Polystyrene and silica nanoparticles are synthesized with a variety of temperature-sensitive dyes such as BODIPY, rose Bengal, Rhodamine dyes 6G, 700, and 800, and Nile Blue A and Nile Red. Photographs are taken with a QImaging QM1 Questar EXi Retiga camera while particles are heated from 25 to 70 C and excited at 532 nm with a Coherent DPSS-532 laser. Photographs are converted to intensity images in MATLAB and analyzed for fluorescence intensity, and plots are generated in MATLAB to describe each dye's intensity vs temperature. Regression curves are created to describe change in fluorescence intensity over temperature. Dyes are compared as nanoparticle core material is varied. Large particles are also created to match the camera's optical resolution capabilities, and it is established that intensity values increase proportionally with nanoparticle size. Nile Red yielded the closest-fit model, with R2 values greater than 0.99 for a second-order polynomial fit. By contrast, Rhodamine 6G only yielded an R2 value of 0.88 for a third-order polynomial fit, making it the least reliable dye for temperature measurements using the polynomial model. Of particular interest in this work is Nile Blue A, whose fluorescence-temperature curve yielded a much different shape from the other dyes. It is recommended that future work describe a broader range of dyes and nanoparticle sizes, and use multiple excitation wavelengths to better quantify each dye's quantum efficiency. Further research into the effects of nanoparticle size on fluorescence intensity levels should be considered as the particles used here greatly exceed 2 ìm. In addition, Nile Blue A should be further investigated as to why its fluorescence-temperature curve did not take on a characteristic shape for a temperature-sensitive dye in these experiments.

While much effort in Stirling engine development is placed on making the high-temperature region of the Stirling engine warmer, this research explores methods to lower the temperature of the cold region by improving heat transfer in the cooler. This paper presents heat transfer coefficients obtained for a Stirling engine heat exchanger with oscillatory flow. The effects of oscillating frequency and input heat rate on the heat transfer coefficients are evaluated and details on the design and development of the heat exchanger test apparatus are also explained. Featured results include the relationship between overall heat transfer coefficients and oscillation frequency which increase from 21.5 to 46.1 Wm-2K-1 as the oscillation frequency increases from 6.0 to 19.3 Hz. A correlation for the Nusselt number on the inside of the heat exchange tubes in oscillatory flow is presented in a concise, dimensionless form in terms of the kinetic Reynolds number as a result of a statistical analysis. The test apparatus design is proven to be successful throughout its implementation due to the usefulness of data and clear trends observed. The author is not aware of any other publicly-available research on a Stirling engine cooler to the extent presented in this paper. Therefore, the present results are analyzed on a part-by-part basis and compared to segments of other research; however, strong correlations with data from other studies are not expected. The data presented in this paper are part of a continuing effort to better understand heat transfer properties in Stirling engines as well as other oscillating flow applications.

Thermal interface materials (TIMs) are extensively used in thermal management applications especially in the microelectronics industry. With the advancement in microprocessors design and speed, the thermal management is becoming more complex. With these advancements in microelectronics, there have been parallel advancements in thermal interface materials. Given the vast number of available TIM types, selection of the material for each specific application is crucial. Most of the metrologies currently available on the market are designed to qualify TIMs between two perfectly flat surfaces, mimicking an ideal scenario. However, in realistic applications parallel surfaces may not be the case. In this study, a unique characterization method is proposed to address the need for TIMs characterization between non-parallel surfaces. Two different metrologies are custom-designed and built to measure the impact of tilt angle on the performance of TIMs. The first metrology, Angular TIM Tester, is based on the ASTM D5470 standard with flexibility to perform characterization of the sample under induced tilt angle of the rods. The second metrology, Bare Die Tilting Metrology, is designed to validate the performance of TIM under induced tilt angle between the bare die and the cooling solution in an "in-situ" package testing format. Several types of off-the-shelf thermal interface materials were tested and the results are outlined in the study. Data were collected using both metrologies for all selected materials. It was found that small tilt angles, up to 0.6°, have an impact on thermal resistance of all materials especially for in-situ testing. In addition, resistance change between 0° and the selected tilt angle was found to be in close agreement between the two metrologies for paste-based materials and phase-change material. However, a clear difference in the thermal performance of the tested materials was observed between the two metrologies for the gap filler materials.

The heat and mass transfer phenomena in micro-scale for the mass transfer phenomena on drug in cylindrical matrix system, the simulation of oxygen/drug diffusion in a three dimensional capillary network, and a reduced chemical kinetic modeling of gas turbine combustion for Jet propellant-10 have been studied numerically. For the numerical analysis of the mass transfer phenomena on drug in cylindrical matrix system, the governing equations are derived from the cylindrical matrix systems, Krogh cylinder model, which modeling system is comprised of a capillary to a surrounding cylinder tissue along with the arterial distance to veins. ADI (Alternative Direction Implicit) scheme and Thomas algorithm are applied to solve the nonlinear partial differential equations (PDEs). This study shows that the important factors which have an effect on the drug penetration depth to the tissue are the mass diffusivity and the consumption of relevant species during the time allowed for diffusion to the brain tissue. Also, a computational fluid dynamics (CFD) model has been developed to simulate the blood flow and oxygen/drug diffusion in a three dimensional capillary network, which are satisfied in the physiological range of a typical capillary. A three dimensional geometry has been constructed to replicate the one studied by Secomb et al. (2000), and the computational framework features a non-Newtonian viscosity model for blood, the oxygen transport model including in oxygen-hemoglobin dissociation and wall flux due to tissue absorption, as well as an ability to study the diffusion of drugs and other materials in the capillary streams. Finally, a chemical kinetic mechanism of JP-10 has been compiled and validated for a wide range of combustion regimes, covering pressures of 1atm to 40atm with temperature ranges of 1,200 K - 1,700 K, which is being studied as a possible Jet propellant for the Pulse Detonation Engine (PDE) and other high-speed flight applications such as hypersonic missiles. The comprehensive skeletal mechanism consists of 58 species and 315 reactions including in CPD, Benzene formation process by the theory for polycyclic aromatic hydrocarbons (PAH) and soot formation process on the constant volume combustor, premixed flame characteristics.

It is possible in a properly controlled environment, such as industrial metrology, to make significant headway into the non-industrial constraints on image-based position measurement using the techniques of image registration and achieve repeatable feature measurements on the order of 0.3% of a pixel, or about an order of magnitude improvement on conventional real-world performance. These measurements are then used as inputs for a model optimal, model agnostic, smoothing for calibration of a laser scribe and online tracking of velocimeter using video input. Using appropriate smooth interpolation to increase effective sample density can reduce uncertainty and improve estimates. Use of the proper negative offset of the template function has the result of creating a convolution with higher local curvature than either template of target function which allows improved center-finding. Using the Akaike Information Criterion with a smoothing spline function it is possible to perform a model-optimal smooth on scalar measurements without knowing the underlying model and to determine the function describing the uncertainty in that optimal smooth. An example of empiric derivation of the parameters for a rudimentary Kalman Filter from this is then provided, and tested. Using the techniques of Exploratory Data Analysis and the "Formulize" genetic algorithm tool to convert the spline models into more accessible analytic forms resulted in stable, properly generalized, KF with performance and simplicity that exceeds "textbook" implementations thereof. Validation of the measurement includes that, in analytic case, it led to arbitrary precision in measurement of feature; in reasonable test case using the methods proposed, a reasonable and consistent maximum error of around 0.3% the length of a pixel was achieved and in practice using pixels that were 700nm in size feature position was located to within ± 2 nm. Robust applicability is demonstrated by the measurement of indicator position for a King model 2-32-G-042 rotameter.

The ability to shift the photovoltaic (PV) power curve and make the energy accessible during peak hours can be accomplished through pairing solar PV with energy storage technologies. A prototype hybrid air conditioning system (HACS), built under supervision of project head Patrick Phelan, consists of PV modules running a DC compressor that operates a conventional HVAC system paired with a second evaporator submerged within a thermal storage tank. The thermal storage is a 0.284m3 or 75 gallon freezer filled with Cryogel balls, submerged in a weak glycol solution. It is paired with its own separate air handler, circulating the glycol solution. The refrigerant flow is controlled by solenoid valves that are electrically connected to a high and low temperature thermostat. During daylight hours, the PV modules run the DC compressor. The refrigerant flow is directed to the conventional HVAC air handler when cooling is needed. Once the desired room temperature is met, refrigerant flow is diverted to the thermal storage, storing excess PV power. During peak energy demand hours, the system uses only small amounts of grid power to pump the glycol solution through the air handler (note the compressor is off), allowing for money and energy savings. The conventional HVAC unit can be scaled down, since during times of large cooling demands the glycol air handler can be operated in parallel with the conventional HVAC unit. Four major test scenarios were drawn up in order to fully comprehend the performance characteristics of the HACS. Upon initial running of the system, ice was produced and the thermal storage was charged. A simple test run consisting of discharging the thermal storage, initially ~¼ frozen, was performed. The glycol air handler ran for 6 hours and the initial cooling power was 4.5 kW. This initial test was significant, since greater than 3.5 kW of cooling power was produced for 3 hours, thus demonstrating the concept of energy storage and recovery.

Concrete columns constitute the fundamental supports of buildings, bridges, and various other infrastructures, and their failure could lead to the collapse of the entire structure. As such, great effort goes into improving the fire resistance of such columns. In a time sensitive fire situation, a delay in the failure of critical load bearing structures can lead to an increase in time allowed for the evacuation of occupants, recovery of property, and access to the fire. Much work has been done in improving the structural performance of concrete including reducing column sizes and providing a safer structure. As a result, high-strength (HS) concrete has been developed to fulfill the needs of such improvements. HS concrete varies from normal-strength (NS) concrete in that it has a higher stiffness, lower permeability and larger durability. This, unfortunately, has resulted in poor performance under fire. The lower permeability allows for water vapor to build up causing HS concrete to suffer from explosive spalling under rapid heating. In addition, the coefficient of thermal expansion (CTE) of HS concrete is lower than that of NS concrete. In this study, the effects of introducing a region of crumb rubber concrete into a steel-reinforced concrete column were analyzed. The inclusion of crumb rubber concrete into a column will greatly increase the thermal resistivity of the overall column, leading to a reduction in core temperature as well as the rate at which the column is heated. Different cases were analyzed while varying the positioning of the crumb-rubber region to characterize the effect of position on the improvement of fire resistance. Computer simulated finite element analysis was used to calculate the temperature and strain distribution with time across the column's cross-sectional area with specific interest in the steel - concrete region. Of the several cases which were investigated, it was found that the improvement of time before failure ranged between 32 to 45 minutes.

An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs, when compared with standard industrial resource sharing networks, prove to be of greater public advantage as they offer improved environmental and economic benefits, and higher operational efficiencies both upstream and downstream in their supply chain.

Although there have been many attempts to adapt EIP methodology to existing industrial sharing networks, most of them have failed for various factors: geographic restrictions by governmental organizations on use of technology, cost of technology, the inability of industries to effectively communicate their upstream and downstream resource usage, and to diminishing natural resources such as water, land and non-renewable energy (NRE) sources for energy production.

This paper presents a feasibility study conducted to evaluate the comparative environmental, economic, and geographic impacts arising from the use of renewable energy (RE) and NRE to power EIPs. Life Cycle Assessment (LCA) methodology, which is used in a variety of sectors to evaluate the environmental merits and demerits of different kinds of products and processes, was employed for comparison between these two energy production methods based on factors such as greenhouse gas emission, acidification potential, eutrophication potential, human toxicity potential, fresh water usage and land usage. To complement the environmental LCA analysis, levelized cost of electricity was used to evaluate the economic impact. This model was analyzed for two different geographic locations; United States and Europe, for 12 different energy production technologies.

The outcome of this study points out the environmental, economic and geographic superiority of one energy source over the other, including the total carbon dioxide equivalent emissions, which can then be related to the total number of carbon credits that can be earned or used to mitigate the overall carbon emission and move closer towards a net zero carbon footprint goal thus making the EIPs truly sustainable.

Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.

This is a two-part thesis.

Part 1 of this thesis investigates the influence of spatial temperature distribution on the accuracy of performance data of photovoltaic (PV) modules in outdoor conditions and provides physical approaches to improve the spatial temperature distribution of the test modules so an accurate performance data can be obtained in the field. Conventionally, during outdoor performance testing, a single thermocouple location is used on the backsheet or back glass of a test module. This study clearly indicates that there is a large spatial temperature difference between various thermocouple locations within a module. Two physical approaches or configurations were experimented to improve the spatial temperature uniformity: thermally insulating the inner and outer surface of the frame; backsheet and inner surface of the frame. All the data were compared with un-insulated conventional configuration. This study was performed in an array setup of six modules under two different preconditioning electrical configurations, Voc and MPPT over several clear sunny days. This investigation concludes that the best temperature uniformity and the most accurate I-V data can be obtained only by thermally insulating the inner and outer frame surfaces or by using the average of four thermocouple temperatures, as specified in IEC 61853-2, without any thermal insulation.

Part 2 of this thesis analyzes the field data obtained from old PV power plants using various statistical techniques to identify the most influential degradation modes on fielded PV modules in two different climates: hot-dry (Arizona); cold-dry (New York). Performance data and visual inspection data of 647 modules fielded in five different power plants were analyzed. Statistical tests including hypothesis testing were carried out to identify the I-V parameter(s) that are affected the most. The affected performance parameters (Isc, Voc, FF and Pmax) were then correlated with the defects to determine the most dominant defect affecting power degradation. Analysis indicates that the cell interconnect discoloration (or solder bond deterioration) is the dominant defect in hot-dry climate leading to series resistance increase and power loss, while encapsulant delamination is being the most dominant defect in cold-dry climate leading to cell mismatch and power loss.