This research develops superior approaches to the traditional site assessment process, as well as novel strategies that offer a distinct advantage over the traditional process. Two major contributions are presented: new analysis approaches for site assessment, and new technical approaches to wind resource monitoring. Two new analysis approaches for wind energy site assessment are developed. The first is a method for site assessment uncertainty analysis. Analytical expressions for the sensitivity factors of the Weibull parameters are developed, which yield exact values for any combination of wind resource, power curve, and energy losses. This enables better determination of the uncertainty in the annual energy production estimate. The second approach is a decision making strategy to determine whether or not to stop measuring the wind resource at any point in the process. In contrast, in the standard approach, the wind resource is almost always measured for a full year, which can be inefficient in many cases. The results show that this approach is just as accurate as measuring for a year, but saves significant time and money. Two new technical approaches for measuring the wind resource are developed. The first measures multiple sites in a year using one ground-based device, which is brought back and forth between sites, resulting in two discontinuous measured data sets, each distributed over the year. The accuracy and uncertainty of the predictions of the wind resource are equivalent to those using a full year of measured data. The second new technical approach can improve shear extrapolation. It relies on short-term data from a ground-based device at a site where a met tower is installed for a year. The short-term data are used to correct the year-long shear parameter. The results show substantial improvements in the accuracy and uncertainty of shear predictions. These new analysis approaches and technical monitoring strategies are unified into a comprehensive "Streamlined Site Assessment Methodology." It provides a flexible, unified approach for executing the site assessment process in which the specific priorities and constraints of the project dictate the resulting approach. This methodology can drastically alter and improve site assessment.

Abstract not available

Abstract not available

This work discusses procedures for predicting the performance of wind powered heating systems for residential applications. In these systems, a wind machine dissipates its output (via electrical resistance heaters or a fluid dissipation device) either directly to the load or indirectly via a thermal storage medium. Both the energy contribution to the heating load and the economic viability of wind heating systems are examined. Two procedures are developed for estimating the useful energy contributed by the wind heating system. The first involves a detailed hour by hour computer model. This computer model includes the option of interchangeable subroutines, which make possible simulation experiments with various types of wind machines and heating loads. Special attention is given to the effect of wind on the heating requirement. The second procedure is a simplified design method which allows estimation of system performance with a minimum of site, wind turbine, and system input parameters. The procedure also incorporates a graphical formulation (WF-chart) for further simplifying its use. Economic viability of wind heating systems is investigated, using a simplified procedure for life cycle costing. By coupling these economic procedures with the simplified method for estimating system performance, optimum system configurations may be found.

<p> Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&amp;P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers&rsquo; preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker&rsquo;s knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and techniques that can provide more flexibility and inclusiveness in the decision making process, such as Multi-Criteria Decision Making (MCDM) methods. However, it can be observed that the MCDM literature: 1) is primarily focused on suggesting certain MCDM techniques to specific problems without providing sufficient evidence for their selection, 2) is inadequate in addressing MCDM in E&amp;P portfolio selection and prioritization compared with other fields, and 3) does not address prioritizing brownfields (i.e., developed oilfields). This research study aims at addressing the above drawbacks through combining three MCDM methods (i.e., AHP, PROMETHEE and TOPSIS) into a single decision making tool that can support optimal oilfield portfolio investment decisions by helping determine the share of each oilfield of the total development resources allocated. Selecting these methods is reinforced by a pre-deployment and post-deployment validation framework. In addition, this study proposes a two-dimensional consistency test to verify the output coherence or prioritization stability of the MCDM methods in comparison with an intuitive approach. Nine scenarios representing all possible outcomes of the internal and external consistency tests are further proposed to reach a conclusion. The methodology is applied to a case study of six major oilfields in Iraq to generate percentage shares of each oilfield of a total production target that is in line with Iraq&rsquo;s aspiration to increase oil production. However, the methodology is intended to be applicable to other E&amp;P portfolio investment prioritization scenarios by taking the specific contextual characteristics into consideration.</p>

<p> This dissertation discusses the design and scaling characteristics of Tesla &ndash; or so-called &ldquo;friction&rdquo; &ndash; turbines, and offers design solutions for achieving optimum performance given the input specifications. The research covers turbines ranging from sub-watt power scavenging designs to watt-range mobile applications to kilowatt-range renewable energy applications. The characteristics of the turbine are demonstrated using micro fabrication, theoretical analysis, and ANSYS, COMSOL, and MATLAB simulations. A MATLAB GUI is provided for generating design specifications and turbine performance sensitivity. </p><p> In Tesla turbines, the fluid profile and the length of the fluid path inside the rotor control the pressure drop and momentum transfer. In this research, analyses of rotor performance for incompressible flow are developed for different fluid profiles and fluid-path lengths. First, frictional losses in the nozzle and at the rotor-turbine interface are investigated, along with other turbine losses. These losses are then classified and modeled in terms of their relationship to head loss and shaft power loss, and investigated using MATLAB and COMSOL. As the turbine scales down, this scaled performance is evaluated and a constraint list for turbine hardware and operating parameters is derived. These results are used to optimize performance for the full range of millimeter to meter sized turbines. </p><p> Tesla turbines at the scales covered in this dissertation (mm &ndash; m) are relatively easy to manufacture. The experimental mini-turbines presented in this research have two primary components, fabricated using commercially available technologies: 1) four 1 cm-diameter rotors with variation in number of disks, interdisk spacing, and effective area, and 2) a turbine enclosure with eight nozzles of varying area, angle, and shape. </p><p> Test results from different configurations of nozzles and rotors are presented, and observations made on the performance trends of the turbine. Flow through the 1 cm rotors is also simulated in ANSYS to verify the momentum equations. The performance difference between analytical solutions, simulation, and experimental results is then studied, and a mapping of experimental results onto analytical results is proposed. </p><p> In addition, various scaling-down methodologies are investigated. Disk spacing is varied as a power function of radius, and turbine performance is analyzed across the turbine range of 1 mm to 400 mm diameter. Using this approach, constant power density designs are specified that perform at better than 35% mechanical efficiency for the entire range. As the turbine is scaled down, the roughening of the disks must be increased to control the fluid profile. Power density is very sensitive to the rotor spacing and the input head, and efficiency is very sensitive to the operating parameters and turbine design. This dissertation argues that these sensitivities explain the wide discrepancies in published turbine performances. </p><p> A practical design tool is also offered, which inputs user specifications on head, flow, particulate size, and medium to generate a list of possible turbine designs along with a recommendation for four candidate designs. The sensitivities of turbine performance to the input head and input flow variations are also reported. The tool is designed to cover 20 mW to 20 kW power range and 2 mm to 500 mm rotor radius range. Current applications and potential extensions to the research are discussed in the conclusion.</p>

<p> One of the major barriers to expanding the capacity of large-scale electrochemical energy storage within batteries is the threat of a catastrophic failure. Catastrophic battery pack failure can be initiated by a defect within a single battery cell. If the failure of a defective battery cell is not contained, the damage can spread and subsequently compromise the integrity of the entire battery back, as well as the safety of those in its surroundings. Replacing the volatile, flammable liquid electrolyte components found in most current lithium ion batteries with a solid polymer electrolyte (SPE) would significantly improve the cell-level safety of batteries; however, poor ionic conductivity and restricted operating temperatures compared to liquid electrolytes have plagued the practical application of SPEs. Rather than competing with the performance of liquid electrolytes directly, our approach to developing SPEs relies on increasing electrolyte functionality through the use of block copolymer architectures. </p><p> Block copolymers, wherein two or more chemically dissimilar polymer chains are covalently bound, have a propensity to microphase separate into nanoscale domains that have physical properties similar to those of each of the different polymer chains. For instance, the block copolymer, polystyrene-<i>b</i>-poly(ethylene oxide) (SEO), has often been employed as a solid polymer electrolyte because the nanoscale domains of polystyrene (PS) can provide mechanical reinforcement, while the poly(ethylene oxide) microphases can solvate and conduct lithium ions. Block copolymer electrolytes (BCEs) formed from SEO/salt mixtures result in a material with the bulk mechanical properties of a solid, but with the ion conducting properties of a viscoelastic fluid. The efficacy SEO-based BCEs has been demonstrated; the enhanced mechanical functionality provided by the PS domains resist the propagation of dendritic lithium structures during battery operation, thus enabling the use of a lithium metal anode. The increase in the specific energy of a battery upon replacing a graphite anode with lithium metal can offset the losses in performance due to the poor ion conduction of SPEs. However, BCEs that enable the use of a lithium anode and have improved performance would represent a major breakthrough for the development of high capacity batteries. </p><p> The electrochemical performance of BCEs has a complex relationship with the nature of the microphase separated domains, which is not well-understood. The objective of this dissertation is to provide fundamental insight into the nature of microphase separation and self-assembly of block copolymer electrolytes. Specifically, I will focus on how the ion-polymer interactions within a diverse set of BCEs dictate nanostructure. Combining such insight with knowledge of how nanostructure influences ion motion will enable the rational design of new BCEs with enhanced performance and functionality. </p><p> In order to facilitate the study of BCE nanostructure, synchrotron-based X-ray scattering techniques were used to study samples over a wide range of length-scales under conditions relevant to the battery environment. The development of the experimental aspects of the X-ray scattering techniques, as well as an improved treatment of scattering data, played a pivotal role in the success of this work. The dissemination of those developments will be the focus of the first section. </p><p> The thermodynamic impact of adding salt to a neutral diblock copolymer was studied in a model BCE composed of a low molecular weight SEO diblock copolymer mixed with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), a common salt used in lithium batteries. In neutral block copolymers (BCPs), self-assembly is a thermodynamically driven process governed by a balance between unfavorable monomer contacts and the entropy of mixing. When the enthalpic and entropic contributions to free energy are similar in magnitude, a block copolymer can undergo a thermally reversible phase transition from an ordered to a disordered nanostructure. We used temperature-dependent small angle X-ray scattering (SAXS) to observe this transition in the model SEO/LiTFSI system. Unlike neutral BCPs, which to a first approximation are single component systems, the SEO/LiTFSI system demonstrated the thermodynamically stable coexistence phases of ordered lamellae and disordered polymer over a finite temperature window. Analysis of the lamellar domains revealed an increase in salt concentration during the ODT, indicating local salt partitioning due to the presence of nanostructure.</p><p> The performance of BCEs can also be improved by chemically functionalizing one of the polymer blocks by covalently attaching the salt anion. Since the cation is the only mobile species, these materials are coined single-ion conducting block copolymers. Single ion conduction can improve the efficiency of battery operation. In order for cation motion to occur in single-ion conducting block copolymers, it must dissociate from the backbone of the anion-containing polymer block. This direct coupling of ion dissociation (and hence conduction) and nanostructure has interesting implications for BCE performance. (Abstract shortened by ProQuest.) </p>

<p> This thesis focuses on the static optimization of a fuel cell plug-in hybrid electric vehicle. The vehicle is been powered by three (3) sources of electrical energy. These sources of electrical energy are: fuel cell, supercapacitor, and lithium-ion battery. </p><p> The main target of this thesis is to make good the performance of a fuel cell plug-in hybrid electric vehicle. This will be achieved by applying static optimization method on the dynamic equations of a moving hybrid vehicle. </p><p> The optimization model of this plug-in hybrid electric vehicle (PHEV) was formulated bases on multiple objectives. The objective parameters are: cost, volume, and mass. We were able to apply static optimization algorithm to find optimal solutions for both the objective values and decision variables of the multiple energy sources. </p><p> The optimization model formulated from the dynamic equations, objective specifications, and design constrains were found to be feasible, bounded, and optimizable by subjecting the primal optimization model to its equivalent dual optimization test. </p><p> Advanced vehicle simulator (ADVISOR) was used to stimulate vehicle performance of our design on a standard driving cycle. The results provide a better outcome than that of standard driving cycles.</p><p>

<p> This research presents cyber-physical systems (CPS) modeling of the smart charging process to both identify and analyze potential vulnerabilities that may exist during the interaction and integration between an Electric Vehicle (EV) and the Electric Vehicle Service Equipment (EVSE). As EVSEs are increasingly being integrated into building energy management systems and interfaced with electric vehicles, safe and secure integration of these systems is of paramount importance for the safety and security of the nation's critical infrastructure and people. Both the charging station and electric vehicles have electro-mechanical components built from 3rd party providers, and there is no mechanism to check for safe and secure integration of EVs and EVSEs. The overall goal of the proposed research is to apply formal methods to verify and validate the cyber-physical interactions between the EV and EVSE to gain insight into vulnerable system states and their impacts. To that end, each component (EV and EVSE) was considered its own cyber-physical system and then separately broken down into individual states of operation. The states of each system were compared to determine how the EV and EVSE interacted on a fundamental level, with one system's state becoming the catalyst for change within the other system. These individual models were completed and subsequently integrated using the open-source software Ptolemy II. Upon successfully completing the interactions, the model was scrutinized using linear temporal logic (LTL) operators to test its veracity and projectability. The initial EV/EVSE model was then altered to emphasize previously determined vulnerabilities within the integrated system in order to verify their existence and potential for harming the system. Two such vulnerabilities were demonstrated in this research to confirm integrity of the model, which will be a valuable asset going forward to ensure the future safety of both operators and consumers regarding EV and EVSE interaction.</p><p>

<p>Solar photovoltaics (PV), the technology that converts sunlight into electricity, has immense potential to become a significant electricity source. Nevertheless, the laws of economics dictate that to grow from the current 2% of U.S. electricity generation and to achieve large scale adoption of solar PV, the cost needs to be reduced to the point where it achieves grid parity. For silicon solar cells, which form 90% of the PV market, a significant and slowly declining component of the cost is due to the high-temperature (> 900 &deg;C) processing required to form p-n junctions. In this thesis, the replacement of the high-temperature p-n junction with a low-temperature amorphous titanium dioxide (TiO₂)/silicon heterojunction is investigated. The TiO₂/Si heterojunction forms an electron-selective, hole-blocking contact. A chemical vapor deposition method using only one precursor is utilized, leading to a maximum deposition condition of 100 &deg;C. High-quality passivation of the TiO₂/Si interface is achieved, with a minimum surface recombination velocity of 28 cm/s. This passivated TiO₂ is used in a double-sided PEDOT/n-Si/TiO₂ solar cell, demonstrating an open-circuit voltage increase of 45 mV. Further, a heterojunction bipolar transistor (HBT) method is developed to investigate the current mechanisms across the TiO₂/p-Si heterojunction, leading to the determination that 4nm of TiO₂ provides the optimal thickness. And finally, an analytical model is developed to explain the current mechanisms observed across the TiO₂/Si interface. From this model, it is determined that once &#916;E_V (TiO₂/Si) is large enough (400 meV), the two key parameters are the Schottky barrier height (resulting in band-bending in silicon) and the recombination velocity at the TiO₂/Si interface. Data corroborates this, indicating the hole-blocking mechanism is due to band-bending induced by the unpinning of the Al/Si interface and TiO₂ charge, as opposed to due to the TiO₂ valence band edge.