Today's technological systems are expected to perform at very high standards throughout their operational phase. The cost associated with unavailability of these systems is very high and especially with the defense systems or medical equipment which can directly affect human lives. The maintenance system plays an important role in achieving higher performance targets. In order to manage maintenance activities in more informed and rational manner, it is very important to understand the inherently complex and dynamic structure of the system. Traditionally maintenance policies are derived from reliability characteristics of individual components or sub-systems. This research makes an attempt to understand the system from the forest level and suggest better maintenance policies for achieving higher availability and lower system degradation. The leverage is gained from System Dynamics framework's ability to model complex systems and capture various feedback loops. The simulation results reveal that with the limited preventive maintenance capacity and within the given assumptions of the model, there exists and optimal preventive maintenance interval which is not the minimum. The simulation results also reflect that frequent preventive maintenance is required at higher load factors. / Master of Science

System Dynamics has been applied to various fields in the natural and social sciences. There still remain countless problems and issues where understanding is lacking and the dominant theories are event-oriented rather than dynamic in nature. One such research area is the application of the traditional systems engineering process in new technology development. The Navy has been experiencing large cost overruns in projects dealing with the implementation of new technologies on complex ship systems. We believe that there is a lack of understanding of the dynamic nature of the technology development process undertaken by aircraft-carrier builders and planners. Our research effort is to better understand the dynamics prevalent in the new technology development process and we use a dynamic modeling technique, namely, System Dynamics in our study. We provide a comprehensive knowledge elicitation process in which members from the Newport News Shipbuilding, the Naval Sea Command Cost Estimating Group, and the Virginia Tech System Performance Laboratory take part in a group model building exercise. We build a System Dynamics model based on the information and data obtained from the experts. Our investigation of the dynamics yields two dominant behaviors that characterize the technology development process. These two dynamic behaviors are damped oscillation and goal seeking. Furthermore, we propose and investigate four dynamic hypotheses in the system. For the current structure of the model, we see that an increase in the complexity of new technologies leads to an increase in the total costs, whereas a increase in the technology maturity leads to a decrease in the total costs in the technology development process. Another interesting insight is that an increase in training leads to a decrease in total costs. / Master of Science

The primary question that the thesis investigates is: what impacts could climate change have on cattle water demand and supply in Khurutshe, Botswana. This thesis is pursued in light of the fact that there is a lack of knowledge on climate change and cattle water demand and supply. Thus, this thesis aims at filling the gap in knowledge on climate change and cattle water resources in Botswana and other semi-arid environments. A cattle water demand and supply model is developed to investigate the primary question of the thesis. The model is driven by rainfall and temperature over time as these variables largely determine cattle water supply and demand, respectively. Climate scenarios for 2050 are constructed using SimCLIM (developed by the International Global Change Institute of the University of Waikato) based on HadCM3 and CSIRO Mk2 General Circulation Models (GCMs). Three Special Report on Emission Scenarios (SRES) are used: A1B, A1FT and A1T. These emission scenarios were selected based on their coverage for possible future Greenhouse Gas emissions (GHG). Climate scenarios show that by 2050 the temperature for the Khurutshe area could increase by as much as 3 oC depending on the GCM and SRES emission scenario and that there could be a decline in rainfall of up to 14% per month. CSIRO Mk2 displayed the maximum decline in rainfall while HadCM3 depicted the maximum increase in temperature. The model is implemented in the Khurutshe of the Kgatleng District, Botswana. The results reported are for Masama Ranch and also for the whole of the Khurutshe area. The results show that climate change could lead to an annual increase of more than 20% in cattle water demand by 2050 due to an increase in temperature. In addition, climate change could lead to a decline in the contribution of surface pan water to cattle water supply. Overall, there could be an increase in abstraction of groundwater for cattle by 2050 due to an increase in demand and a decline in forage water content and surface pan water. Observations in semi-arid environments of Africa indicate that farmers encounter problems of declining borehole yields and local depletion in groundwater in summer and drought years when demand peaks. In addition, it has been observed that during drought more cattle are lost as a result of lack of water, particularly for those whose cattle are reliant on surface water. Thus, the results from this study indicate that climate change could enhance this problem. In the thesis I have shown the importance of integrating climate change impacts on water demand and supply when assessing water resources, which has been ignored in the past. Some of the policy options that are discussed are tradable pumping permits for controlling abstraction and allocation issues in the Khurutshe aquifer and, controlling stocking numbers. This is in recognition of the fact that climate change could result in more reliance on groundwater for both cattle farming and urban water supply hence compromising sustainability and allocation issues especially for the Khurutshe aquifer which is earmarked to supply the city of Gaborone and surrounding villages in drought periods.

The primary question that the thesis investigates is: what impacts could climate change have on cattle water demand and supply in Khurutshe, Botswana. This thesis is pursued in light of the fact that there is a lack of knowledge on climate change and cattle water demand and supply. Thus, this thesis aims at filling the gap in knowledge on climate change and cattle water resources in Botswana and other semi-arid environments. A cattle water demand and supply model is developed to investigate the primary question of the thesis. The model is driven by rainfall and temperature over time as these variables largely determine cattle water supply and demand, respectively. Climate scenarios for 2050 are constructed using SimCLIM (developed by the International Global Change Institute of the University of Waikato) based on HadCM3 and CSIRO Mk2 General Circulation Models (GCMs). Three Special Report on Emission Scenarios (SRES) are used: A1B, A1FT and A1T. These emission scenarios were selected based on their coverage for possible future Greenhouse Gas emissions (GHG). Climate scenarios show that by 2050 the temperature for the Khurutshe area could increase by as much as 3 oC depending on the GCM and SRES emission scenario and that there could be a decline in rainfall of up to 14% per month. CSIRO Mk2 displayed the maximum decline in rainfall while HadCM3 depicted the maximum increase in temperature. The model is implemented in the Khurutshe of the Kgatleng District, Botswana. The results reported are for Masama Ranch and also for the whole of the Khurutshe area. The results show that climate change could lead to an annual increase of more than 20% in cattle water demand by 2050 due to an increase in temperature. In addition, climate change could lead to a decline in the contribution of surface pan water to cattle water supply. Overall, there could be an increase in abstraction of groundwater for cattle by 2050 due to an increase in demand and a decline in forage water content and surface pan water. Observations in semi-arid environments of Africa indicate that farmers encounter problems of declining borehole yields and local depletion in groundwater in summer and drought years when demand peaks. In addition, it has been observed that during drought more cattle are lost as a result of lack of water, particularly for those whose cattle are reliant on surface water. Thus, the results from this study indicate that climate change could enhance this problem. In the thesis I have shown the importance of integrating climate change impacts on water demand and supply when assessing water resources, which has been ignored in the past. Some of the policy options that are discussed are tradable pumping permits for controlling abstraction and allocation issues in the Khurutshe aquifer and, controlling stocking numbers. This is in recognition of the fact that climate change could result in more reliance on groundwater for both cattle farming and urban water supply hence compromising sustainability and allocation issues especially for the Khurutshe aquifer which is earmarked to supply the city of Gaborone and surrounding villages in drought periods.

No description available.

Carbon sequestration is paramount to reducing climate change. Grasslands, representing 40% of all terrestrial area, can serve as a primary sequestration location if optimal management strategies can be realized. This study used system dynamics modeling to examine the temporal dynamics of carbon stocks and flows in response to grass species composition, grazing intensity, and temperature and precipitation changes at the landscape level. While there are other biogeochemical models in existence, they are either meant to model large areas, including globally, or are meant to be at a farm level and have limited plot sizes, limiting the options for rangeland managers to test management strategies in larger areas. The aims included conducting a field study of the rangeland, create an initial model; evaluate how the model responded to grazing, temperature, and precipitation changes; and compare the model outcomes to prior work to test the behavior of the model as the start of validation. This thesis used four plant functional groups (C3 and C4 grasses, forbs, and legumes) as the base groups for the model. C4 grasses were not found in in the field study but served to test whether the model detected changes in sequestration when grassland composition is changed. The results demonstrated an approach of using functional groups in system dynamics modeling to optimize carbon sequestration while accounting for diverse management strategies, as has been seen in other biogeochemical models. The model was aligned with prior field research in terms of carbon sequestration levels. The model was able to note differences in grazing regimes, temperature, and precipitation changes in terms of carbon sequestration. Grazing scenarios showed that while increased grazing impacted aboveground litter, it had little impact on sequestration; there was only a 4% increase in carbon with no grazing, Changes in temperature, up to 3°C, were predicted to increase carbon sequestration by 16% from 0.442 to 0.514 kg*m-2*day-1 while decreases in precipitation, both alone and in combination with increasing temperatures, was predicted to decrease sequestration up to 44%. This has to do with the grassland composition, ii especially as this was a C3 dominated grassland which grows in the winter and early spring and required more water but lower temperatures for growth. Future research should continue model validation, test additional functional groups like shrubs, implement more soil carbon pools and flows and add a nitrogen component to the model.

Bovine respiratory disease (BRD) is a significant health problem for cattle producers in terms of economic cost and animal welfare. In the United States (US), it is one of the leading causes of sickness and death in beef calves prior to weaning. Although much research has been conducted to develop vaccines for prevention and antibiotics for treatment, the morbidity and mortality of BRD in beef calves prior to weaning has not improved over the years. The identification of risk factors associated with BRD is an area of focus which might ultimately allow producers to minimize morbidity and mortality from BRD. Little research has been performed to understand factors contributing to the risk of BRD in beef calves prior to weaning. BRD affects the beef cattle industry through losses due to mortality, prevention cost, treatment cost, or morbidity effect on productivity. Currently, the economic losses due to BRD for beef calves prior to weaning is not available. Price paid for feeder cattle is a major factor influencing the income of producers. The effect of BRD is a complicated problem since the parameters associated with the cost of BRD in beef cow-calf production are variable and interrelated. To better understand the economic effect of BRD in beef calves prior to weaning, concepts of uncertainty, variability, stochasticity, nonlinearity, and feedback might be involved during the process of assessing risk. The objectives of this dissertation are the following: 1) to test if calf sex, birth weight, and age of dam are associated with BRD of beef calves prior to weaning in different age periods; 2) to identify factors affecting the national market price of beef feeder cattle in the US and how the prices change over time; 3) to investigate the prevention and treatment cost of BRD in beef calves prior to weaning; 4) to estimate the economic cost of BRD in US beef calves prior to weaning; and 5) to understand the effect of BRD occurrence or absence on the national net income of the US beef cow-calf industry.

System dynamics has been used to better understand the dynamics within complex natural and social systems. This understanding enables us to make decisions and define strategies that help to resolve the problematic behaviors associated within these systems. For example within an operating environment such as the US Navy, decisions taken today can have long lasting impact on system performance. The Navy has experienced large cost overruns during the new technology implementation process on ship systems that can also have an impact on total life cycle performance. The integration phase of the implementation process represents most of the cost overruns experienced in the overall new technology life cycle (development, integration, and operation/support/disposal). We have observed a general concern that there is a lack of understanding for the dynamic behavior of those processes which comprise the integration phase, among ship-builders and planners. One of the goals of our research effort has been to better understand the dynamic behavior of the new technology integration processes, using a dynamic modeling technique known as System Dynamics. Our approach has also been to provide a comprehensive knowledge elicitation process in which members from the shipbuilding industry, the US Navy, and the Virginia Tech System Performance Laboratory take part in group model building exercises. The system dynamics model that is developed in this manner is based on data obtained from the experts. An investigation of these dynamics yields a dominant cost behavior that characterizes the technology integration processes. This behavior is S-shaped growth. The following two dynamic hypotheses relative to lifecycle cost and performance of the inserted new technology were confirmed: (1) For the current structure of the model we observe the more the complexity of the new technology, the less affordable a technology becomes; (2) Integration of immature (less developed) technologies is associated with higher costs. Another interesting insight is that cost is very sensitive to the material procurement. Future research can be addressed to a more detailed level of abstraction for various activities included in the technology integration phase, such as testing and evaluation, cost of rework and risks associated with inadequate testing etc. This will add to our evolving understanding of the behavior of individual activities in the technology integration process. / Master of Science

Estimating the cost of new technology insertion into an existing (or new) operating environment is of great concern and interest for those entities that own and operate that technology. New technology has many cost requirements associated with it, for instance; design, manufacturing, operation, maintenance and disposal all add to the life-cycle cost of a technology. Estimation and planning methods are needed to better match the costs associated with technology life-cycle requirements (design, manufacturing, etc.) in order to optimize the spending of funds. By optimizing (or closely matching) predicted technology life-cycle costs to a budget the new technology system will have a high probability of operating more efficiently and will minimize costs. System Dynamics has been used to understand and simulate how complex systems of people and technologies operate over time. Decisions (such as how much funding is allocated when in a technology life-cycle) that occur temporally or in a complex environment (i.e., many causes and effects) can be simulated to evaluate the impact the decision may have. Currently, the majority of decision theories and tools are focused on one moment in time (event-focused) rather than including the dynamic nature that decisions can have over time. Evaluating decisions at one instant versus taking into account the life-cycle impact a decision can have, is especially important to the US Government, where investment decisions can involve billions of dollars today, but potentially hundreds of billions later for technology life-cycle requirements. The Navy has experienced large cost overruns in the implementation of new technologies especially in the operations, support and disposal life-cycle phases. There is a lack of detailed knowledge of the dynamic nature of the technology operations, support and disposal (OS&D) processes undertaken by aircraft-carrier builders and planners. This research effort is to better understand and simulate the dynamics prevalent in the new technology implementation process and use a dynamic modeling technique, namely, System Dynamics in our study. A System Dynamics model based on the information and data obtained from experts including; General Dynamics - Newport News Shipbuilding, the Naval Sea Command Cost Estimating Group, and Virginia Polytechnic and State University - System Performance Laboratory. The model was constructed to simulate and predict the cost of operating, maintaining and disposing of a new technology. The investigation of the dynamics yields four dominant behaviors that characterize the technology OS&D process. These four dynamic behaviors are; exponential growth, goal seeking, overshoot & collapse and S-shaped growth with overshoot. Furthermore, seven dynamic hypotheses in the system are investigated. The model predicts an increase in the risk and degradation of new technologies leads to an increase in the total costs in the technology OS&D process. Three interesting insights that lead to increased total OS&D costs were; an inequality between the requirements for OS&D and provided budget, any delay in additional funding being provided and that as the new technology system grew older, it became less costly to maintain. / Master of Science

Globally, the incidence of infection caused by Neisseria gonorrhoeae is the second highest among the bacterial sexually transmitted infections. In Canada, declining rates during the 1990s suggested progress toward curbing gonorrhea; however, those have been increasing since 1999, with rates in Saskatchewan among the highest in the country. Infection can cause serious complications in men and women, and reported resistance to third-generation cephalosporins could lead to potentially untreatable infections. Increased understanding of gonorrhea transmission dynamics, sexual networks, and predictors of antimicrobial resistance development is needed to inform the development of improved approaches to prevention and treatment. The research presented herein draws upon data from Shanghai, China, and Saskatchewan, Canada, to compare and contrast varying epidemiologic approaches to enhancing understanding of gonorrhea in the two settings. Using traditional statistical approaches, multi-level statistical modeling, social network analysis, and dynamic simulation modeling, questions related to sexual behavior, partner presentation, and antimicrobial resistance development are explored. Each technique is evaluated for its potential contribution to overall understanding of the issues related to the ongoing gonorrhea epidemic, globally, and in Saskatchewan. The relative strengths and limitations of the application of the analytical approaches in the different settings are described. Socio-demographic characteristics provided useful indicators of antimicrobial resistant infection among patients with gonorrhea from Shanghai. Further, socio-demographic characteristics were also useful for predicting presentation of a partner for testing and treatment and the use of condoms during intercourse, among this study population. In Saskatchewan, socio-demographic characteristics were useful in predicting coinfection with gonorrhea and chlamydia at the time of diagnosis as well as repeat infection with gonorrhea. Social network analysis of the Saskatchewan dataset provided little additional understanding of the gonorrhea epidemic in the province. This result was largely related to how STI data are collected and stored in the province. The utility of dynamic simulation modeling to investigate the potential impact of antimicrobial resistance in Saskatchewan was also limited due to the same data constraints. However, the insight gained from the model building process and findings from the working model did offer a starting point for conversations around the best ways to postpone the development of antimicrobial resistance in N. gonorrhoeae in Saskatchewan, as well as contribute additional information about how the ways in which STI data are collected and stored in the province considerably restrict the applicability of otherwise powerful epidemiologic tools. With persistently high rates of disease transmission, and the threat of untreatable infections due to antimicrobial resistance, N. gonorrhoeae remains a substantial public health threat locally and globally. The research presented herein describes various approaches to understanding and controlling this disease, applied in contrasting settings. There are a wide variety of elements that should be considered when choosing the appropriate tool(s) to address gonorrhea in a given population; there is no “one size fits all” solution. The local epidemiology of disease, cultural and behavioural norms, the characteristics of the notifiable disease reporting and information systems, and the availability of suitable data all affect the relative strengths and weaknesses of the available analytic methods and disease control approaches.