Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Mavris, Dimitri N.; Committee Member: Baik, Hojong; Committee Member: DeLaurentis, Daniel; Committee Member: Lewe, Jung-Ho; Committee Member: Schrage, Daniel. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D. in City and Regional Planning)--University of California, Berkeley, 2003. / "Fall 2003." Includes bibliographical references (p. 173-183). Also available online via the ITS Berkeley web site (www.its.berkeley.edu).

This study utilized (a) actual measured agricultural water use along with (b) geostatistical techniques, (c) crop simulation models, and (d) general circulation models (GCMs) to assess irrigation demand and the uncertainty associated with demand projections at spatial scales relevant to water resources management. In the first part of the study, crop production systems in Southwest Georgia are characterized and the crop simulation model error that may be associated with aggregated model inputs is estimated for multiple spatial scales. In the second portion of this study, a methodology is presented for characterizing regional irrigation strategies in the Lower Flint River basin and estimating regional water demand. Regional irrigation strategies are shown to be well represented with the moisture stress threshold (MST) algorithm, metered annual agricultural water use, and crop management data. Crop coefficient approaches applied at the regional scale to estimate agricultural water demand are shown to lack the interannual variability observed with this novel approach. In the third portion of this study, projections of regional agricultural demand under climate change in the Lower Flint River basin are presented. GCMs indicate a range of possible futures that include the possibility of relatively small changes in irrigation demand in the Lower Flint River basin. However, most of the GCMs utilized in this work project significant increases in median water demand towards the end of this century. In particular, results suggest that peak agricultural water demands in July and August may increase significantly. Overall, crop simulation models are shown to be useful tools for representing the intra-annual and interannual variability of regional irrigation demand. The novel approach developed may be applied to other locations in the world as agricultural water metering programs become more common.

A “smarter grid” is expected to be more flexible and more reliable than traditional electric power grids. Among technologies required for the “smarter grid” deployment, this dissertation presents a sustainable microgrid and a spatial and temporal model of plug-in electric vehicle charging demand for the “smarter grid”. First, this dissertation proposes the dynamic modeling technique and operational strategies for a sustainable microgrid primarily powered by wind and solar energy resources. Multiple-input dc-dc converters are used to interface the renewable energy sources to the main dc bus. The intended application for such a microgrid is an area in which there is interest in achieving a sustainable energy solution, such as a telecommunication site or a residential area. Wind energy variations and rapidly changing solar irradiance are considered in order to explore the effect of such environmental variations to the intended microgrid. The proposed microgrid can be operated in an islanded mode in which it can continue to generate power during natural disasters or grid outages, thus improving disaster resiliency of the “smarter grid”. In addition, this dissertation presents the spatial and temporal model of electric vehicle charging demand for a rapid charging station located near a highway exit. Most previous studies have assumed a fixed charging location and fixed charging time during the off-peak hours for anticipating electric vehicle charging demand. Some other studies have based on limited charging scenarios at typical locations instead of a mathematical model. Therefore, from a distribution system perspective, electric vehicle charging demand is still unidentified quantity which may vary by space and time. In this context, this study proposes a mathematical model of electric vehicle charging demand for a rapid charging station. The mathematical model is based on the fluid dynamic traffic model and the M/M/s queueing theory. Firstly, the arrival rate of discharged vehicles at a charging station is predicted by the fluid dynamic model. Then, charging demand is forecasted by the M/M/s queueing theory with the arrival rate of discharged vehicles. The first letter M of M/M/s indicates that discharged vehicles arrive at a charging station with the Poisson distribution. The second letter M denotes that the time to charge each EV is exponentially distributed, and the third letter s means that there are s identical charging pumps at a charging station. This mathematical model of charging demand may allow grid’s distribution planners to anticipate charging demand at a specific charging station. / text

The focus of transportation planning, until the past three decades or so, was to provide adequate transportation infrastructure supply to meet the mobility needs of the population. Over the past three decades, however, in view of increasing suburban sprawl and auto dependence, the focus of transportation planning has expanded to include the objective of sustainable development. Contemporary efforts toward sustainability include, for example, integrated land-use and transportation planning, travel demand management, congestion pricing, and transit and non-motorized travel oriented development. Consequently, in an effort to understand individuals’ behavioral responses to (and to assess the effectiveness of) these policies, the travel demand modeling field evolved along three distinct directions: (a) Activity-based travel demand modeling, (b) Built environment and travel behavior modeling, and (c) Integrated land-use -- transportation modeling. The three fields of research, however, have progressed in a rather disjoint fashion. The overarching goal of this dissertation is to contribute toward the research needs that are at the intersection of the three fields of research identified above, and to bring the three research areas together into a unified research stream. This is achieved by the simultaneous consideration of the following three aspects, each of which is of high importance in each direction of research identified above: (1) The activity-based and tour-based approaches to travel behavior analysis, (2) Residential self-selection effects, and (3) Integrated modeling of long-term land-use related choices and medium- and short-term travel-related choices. To this end, a series of integrated models of multidimensional choice processes are formulated to jointly analyze long-term residential location decisions and medium- and short-term activity-travel decisions (such as auto ownership, bicycle ownership, commute mode choice, and daily time-use). The models are estimated and applied using data from the 2000 San Francisco Bay Area Travel Survey to understand and disentangle the multitude of relationships between long-, medium-, and short-term choices. This dissertation also formulates a multiple discrete-continuous nested extreme value model that can accommodate inter-alternative correlations and flexible substitution patterns across mutually exclusive subsets (or nests) of alternatives in multiple discrete-continuous choice models. / text

published_or_final_version / Politics and Public Administration / Master / Master of Public Administration

The primary goals of the National Health Planning and Resources Development Act (P.L. 93-641) of 1974 were to (1) contain health care costs and (2) increase the accessibility and quality of health services. Certificate of need (CON) regulation is one attempt to constrain health care costs by limiting the supply of certain medical care facilities. With respect to the nursing home industry, prospective nursing home owners/operators are required to demonstrate that a "need" exists for more nursing home beds. Some States also imposed a construction moratorium that prevented any expansion of existing facilities or construction of new facilities regardless of whether or not a "need" existed. These CON/moratorium programs impose a supply side constraint that creates a potential barrier to entry and in the presence of excess demand may cause a nursing home bed shortage for those residents covered by Medicaid. Even though the Federal CON requirement lapsed in 1986, forty-two St ates and the District of Columbia continue to have a CON, a construction moratorium, or both for nursing home facilities. Yet maintaining these regulations comes with a cost.This paper investigates if differences exist in the quality of care and the access to care between nursing homes in those States without CON and/or construction moratorium and those States that still have such policies. Using data for the years 1991 through 2003 for all freestanding Medicaid-/Medicare-certified nursing home facilities in the United States and employing state and facility fixed effects models we find that Medicaid-eligible residents in those states without CON and/or construction moratorium policies have more access to a nursing home bed than those individuals in states with these policies. With respect to quality of care the results are mixed depending on the measure of quality that is employed. With the risk of becoming a nursing home resident at the age of 65 at 44 percent and at the age of 8 5 at 53 percent (Spillman and Lubitz 2002) coupled with the aging of the current population, the areas of quality of care and access to care remain important policy issues in the nursing home industry.

This thesis describes and discusses the application of System Dynamics methodology as a basis for formulating diversification strategy and control policies of the largest diversifying cement company in the 'United Kingdom. The problems of the industry such as stagnant growth, cyclic and seasonal variations in cement demand, and overcapacity are described. The formulation of a SD model of the situation which captures these problems together with its equations system are presented. The model also simulates the planning and control processes for the selection, initiation and completion of both expansion and diversification investment projects. It is argued and demonstrated that the fact that these processes consist of feedback loops should and could be utilized for understanding these processes, advancing complementary theoretical concepts, and designing and formulating more 'effective systems and decision rules. An intensive analysis of the model in SD frameworks further supports these arguments. These analyses reveal the nature of the system's dynamic properties and its likely developments, the dynamic and situational nature of diversification effectiveness, and the importance of several diversification decision factors. These analyses also show how complex the formulation of a thorough and effective diversification strategy may become together with the ways and means of dealing with these complexities.. It is concluded that the thrust of an effective diversification lies with the broadening of the conventional theoretical concepts and analysis to include the dynamic characteristics of the system. It is also concluded and shown that System Dynamics methodology can provide a strong analytical basis for achieving these ends.

published_or_final_version / Statistics / Master / Master of Social Sciences

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