Efficient performance of gas turbines depends, among several parameters, on the mainstream gas entry temperature. At the same time, transport of this high temperature gas into the rotor-stator cavities of turbine stages affects the durability of rotor disks. This transport is usually countered by installing seals on the rotor and stator disk rims and by pressurizing the cavities by injecting air (purge gas) bled from the compressor discharge. The configuration of the rim seals influences the magnitude of main gas ingestion as well as the interaction of the purge gas with the main gas. The latter has aerodynamic and hub endwall heat transfer implications in the main gas path. In the present work, experiments were performed on model single-stage and 1.5-stage axial-flow turbines. The turbines featured vanes, blades, and rim seals on both the rotor and stator disks. Three different rim seal geometries, viz., axially overlapping radial clearance rim seals for the single-stage turbine cavity and the 1.5-stage turbine aft cavity, and a rim seal with angular clearance for the single-stage turbine cavity were studied. In the single-stage turbine, an inner seal radially inboard in the cavity was also provided; this effectively divided the disk cavity into a rim cavity and an inner cavity. For the aft rotor-stator cavity of the 1.5-stage turbine, a labyrinth seal was provided radially inboard, again creating a rim cavity and an inner cavity. Measurement results of time-average main gas ingestion into the cavities using tracer gas (CO2), and ensemble-averaged trajectories of the purge gas flowing out through the rim seal gap into the main gas path using particle image velocimetry are presented. For both turbines, significant ingestion occurred only in the rim cavity. The inner cavity was almost completely sealed by the inner seal, at all purge gas flow rates for the single-stage turbine and at the higher purge gas flow rates for 1.5-stage turbine. Purge gas egress trajectory was found to depend on main gas and purge gas flow rates, the rim seal configuration, and the azimuthal location of the trajectory mapping plane with respect to the vanes.

Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.

Evacuated tube solar thermal collector arrays have a wide range of applications. While most of these applications are limited in performance due to relatively low maximum operating temperatures, these collectors can still be useful in low grade thermal systems. An array of fifteen Apricus AP-30 evacuated tube collectors was designed, assembled, and tested on the Arizona State University campus in Tempe, AZ. An existing system model was reprogrammed and updated for increased flexibility and ease of use. The model predicts the outlet temperature of the collector array based on the specified environmental conditions. The model was verified through a comparative analysis to the data collected during a three-month test period. The accuracy of this model was then compared against data calculated from the Solar Rating and Certification Corporation (SRCC) efficiency curve to determine the relative performance. It was found that both the original and updated models were able to generate reasonable predictions of the performance of the collector array with overall average percentage errors of 1.0% and 1.8%, respectively.

Energy efficient design and management of data centers has seen considerable interest in the recent years owing to its potential to reduce the overall energy consumption and thereby the costs associated with it. Therefore, it is of utmost importance that new methods for improved physical design of data centers, resource management schemes for efficient workload distribution and sustainable operation for improving the energy efficiency, be developed and tested before implementation on an actual data center. The BlueTool project, provides such a state-of-the-art platform, both software and hardware, to design and analyze energy efficiency of data centers. The software platform, namely GDCSim uses cyber-physical approach to study the physical behavior of the data center in response to the management decisions by taking into account the heat recirculation patterns in the data center room. Such an approach yields best possible energy savings owing to the characterization of cyber-physical interactions and the ability of the resource management to take decisions based on physical behavior of data centers. The GDCSim mainly uses two Computational Fluid Dynamics (CFD) based cyber-physical models namely, Heat Recirculation Matrix (HRM) and Transient Heat Distribution Model (THDM) for thermal predictions based on different management schemes. They are generated using a model generator namely BlueSim. To ensure the accuracy of the thermal predictions using the GDCSim, the models, HRM and THDM and the model generator, BlueSim need to be validated experimentally. For this purpose, the hardware platform of the BlueTool project, namely the BlueCenter, a mini data center, can be used. As a part of this thesis, the HRM and THDM were generated using the BlueSim and experimentally validated using the BlueCenter. An average error of 4.08% was observed for BlueSim, 5.84% for HRM and 4.24% for THDM. Further, a high initial error was observed for transient thermal prediction, which is due to the inability of BlueSim to account for the heat retained by server components.

ABSTRACT The heat recovery steam generator (HRSG) is a key component of Combined Cycle Power Plants (CCPP). The exhaust (flue gas) from the CCPP gas turbine flows through the HRSG − this gas typically contains a high concentration of NO and cannot be discharged directly to the atmosphere because of environmental restrictions. In the HRSG, one method of reducing the flue gas NO concentration is to inject ammonia into the gas at a plane upstream of the Selective Catalytic Reduction (SCR) unit through an injection grid (AIG); the SCR is where the NO is reduced to N2 and H2O. The amount and spatial distribution of the injected ammonia are key considerations for NO reduction while using the minimum possible amount of ammonia. This work had three objectives. First, a flow network model of the Ammonia Flow Control Unit (AFCU) was to be developed to calculate the quantity of ammonia released into the flue gas from each AIG perforation. Second, CFD simulation of the flue gas flow was to be performed to obtain the velocity, temperature, and species concentration fields in the gas upstream and downstream of the SCR. Finally, performance characteristics of the ammonia injection system were to be evaluated. All three objectives were reached. The AFCU was modeled using JAVA - with a graphical user interface provided for the user. The commercial software Fluent was used for CFD simulation. To evaluate the efficacy of the ammonia injection system in reducing the flue gas NO concentration, the twelve butterfly valves in the AFCU ammonia delivery piping (risers) were throttled by various degrees in the model and the NO concentration distribution computed for each operational scenario. When the valves were kept fully open, it was found that it led to a more uniform reduction in NO concentration compared to throttling the valves such that the riser flows were equal. Additionally, the SCR catalyst was consumed somewhat more uniformly, and ammonia slip (ammonia not consumed in reaction) was found lower. The ammonia use could be decreased by 10 percent while maintaining the NO concentration limit in the flue gas exhausting into the atmosphere.

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.

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.

In this study, two novel sorbents (zeolite 4A and sodium polyacrylate) are tested to investigate if utilizing ultrasonic acoustic energy could decrease the amount of time and overall energy required to regenerate these materials for use in cooling applications. To do this, an experiment was designed employing a cartridge heater and a piezoelectric element to be simultaneously providing heat and acoustic power to a custom designed desorption bed while measuring the bed mass and sorbent temperature at various locations. The results prove to be promising showing that early in the desorption process ultrasound may expedite the desorption process in zeolite by as much as five times and in sodium polyacrylate as much as three times in comparison to providing heat alone. The results also show that in zeolite desorption utilizing ultrasound may be particularly beneficial to initiate desorption whereas in sodium polyacrylate ultrasound appears most promising in the after a temperature threshold is met. These are exciting results and may prove to be significant in the future as more novel heat-based cooling cycles are developed.

Photovoltaic modules degrade in the field. This thesis aims to answer two questions: 1. Do photovoltaic modules degrade linearly or not? 2. Do soiled modules operate at lower temperatures than clean modules? Answers to these questions are provided in part 1 and part 2 of this thesis respectively.

Part 1: Linearity determination in degradation: The electricity output from PV power plants degrades every year. Generally, a system’s life is considered to last for 20-25 years and rate of degradation is commonly assumed as 1% per year. PV degradation can be found out using Performance Ratio (PR), Performance Index (PI) and raw kWh output. The rate of degradation is considered linear for simplicity of calculations. In this thesis, statistical methods are used to check whether systems in Arizona are degrading linearly or not. Time series modeling such as Winters’ method and ARIMA are used to model the data. Winters’ method and Seasonal ARIMA consider the seasonality component and perform well for small data sets of about 10 years. Rate of degradation is found out as linear for all the evaluated systems.

Part 2: Temperature analysis of clean and soiled modules: Soiling and temperature are important parameters in performance of PV modules. In this paper, an analysis is carried out on a soiling station located in Mesa, Arizona. The soiling station consists of 10 different c-Si coupons with tilt angles varying from 0° to 45° with the difference of 5°. These coupons are cut in half, one is cleaned periodically and the other is remained soiled naturally. The analysis involves data worth for 19 months. 6 dry spells in all four seasons within 19 months were analyzed. The temperature difference between a clean module and a soiled module (ΔT) is compared with the soiling loss factor (SLF). The analysis concludes stating in which season a soiled module is hotter or cooler than a clean module.

A low cost expander, combustor device that takes compressed air, adds thermal energy and then expands the gas to drive an electrical generator is to be designed by modifying an existing reciprocating spark ignition engine. The engine used is the 6.5 hp Briggs and Stratton series 122600 engine. Compressed air that is stored in a tank at a particular pressure will be introduced during the compression stage of the engine cycle to reduce pump work. In the modified design the intake and exhaust valve timings are modified to achieve this process. The time required to fill the combustion chamber with compressed air to the storage pressure immediately before spark and the state of the air with respect to crank angle is modeled numerically using a crank step energy and mass balance model. The results are used to complete the engine cycle analysis based on air standard assumptions and air to fuel ratio of 15 for gasoline. It is found that at the baseline storage conditions (280 psi, 70OF) the modified engine does not meet the imposed constraints of staying below the maximum pressure of the unmodified engine. A new storage pressure of 235 psi is recommended. This only provides a 7.7% increase in thermal efficiency for the same work output. The modification of this engine for this low efficiency gain is not recommended.