Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains vii, 81 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 79-81).

Studies have shown that over 30 percent of the bridges in the United States are structurally deficient, and/or over 50 years old. The majority of the highway bridges have reinforced concrete decks supported on steel or concrete girders. Over the years, weathering and deicing chemicals have caused spalling of the concrete surrounding the reinforcing steel, deteriorating many bridges to levels that often result in closure. Repairing or reconstructing the reinforced concrete deck to meet current design specifications is often not possible or feasible, and at times seems illogical due to the possibility of reoccurrence. Because of reinforced concrete's downfalls, there is a move toward alternative materials and designs for bridge deck replacements. In particular, Reynolds Metals Company has lead the movement toward the use of a shop-extruded aluminum deck system known as ALUMADECKTM. The purpose of this research is to evaluate data collected from full-scale testing under test truck loading of an in-service ALUMADECK bridge system. The bridge is known as the Little Buffalo Creek Bridge and is located in Mecklenburg County, VA. The topics researched from the load tests are the composite action amongst the deck and supporting members, the load distribution amongst supporting members, the dynamic load allowance for supporting members, and the developed deck stresses due to test truck loads. Evaluations of the research topics include comparisons to the methods employed in the design calculations provided by VDOT and to those of the American Association of State Highway and Transportation Officials (AASHTO) design specifications. / Master of Science

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Although power system load modelling is a mature research area, there is a renewed interest in updating available load models and formulating improved load modelling methodologies. The main drivers of this interest are the introduction of new types of non-conventional (e.g. power electronic interfaced) loads, the requirement to operate power supply systems with increasing levels of renewable distributed generation and the implementation of various load control functionalities (e.g. demand side management). As the majority of existing load models do not allow for a full and precise analysis of these new operating conditions, it is essential to develop new load models and update load modelling techniques. This thesis presents a detailed study of modern loads, focussing on the requirements for their correct representation in power system analysis. The developed models of the individual loads are then combined using a new load aggregation methodology for developing aggregate load models, suitable for the analysis of both existing and future power supply systems (so called ’smart grids’). The methodology uses a circuit-based load modelling approach, as this allows reproduction of the instantaneous current waveforms of the modelled load for any given supply voltage. This approach retains all electrical characteristics of the loads and provides a more realistic representation of some important phenomena (e.g. harmonic cancellation and attenuation due to load and supply system interactions) which are often neglected in traditional load modelling procedures. Case studies of the UK residential and commercial load sectors are presented as illustrations of the load aggregation methodology. The results show significant short-term and long-term temporal variations in the load characteristics, which are not available or reported in the existing literature. This information allows for a more comprehensive assessment of demand-side management functionalities and correlation with locally connected distributed generation. Both of these effects are investigated in the thesis by quantifying the possible extent and range of changes in power system performance for some expected near future changes in load configurations and network operating conditions.

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Load testing remains the most integral part of testing and measuring the performance of Large Scale Software Systems (LSS). During the course of a load test, a system under test is closely monitored, resulting in an extremely large amount of logging data, e.g., Performance counters logs. The performance counter log captures run-time system properties such as CPU utilization, disk I/O, queues, and network traffic. Such information is of vital interest to performance analysts. The information helps them to observe the system’s behavior under load by comparing it against the documented behavior of a system or with expected behavior. In practice, for LSS, it is impossible for an analyst to skim through the large amount of performance counters to find the required information. Instead, analysts often use ‘rules of thumb’. In a LSS, there is no single person with complete system knowledge. In this thesis, we present methodologies to help performance analysts to 1) more effectively compare load tests to detect performance deviations, which may, lead to Service Level Agreement (SLA) violations and 2) provide them with a smaller and manageable set of important performance counters to assist in the root cause analysis of the detected deviations. We demonstrate our methodologies through case studies based on load test data obtained from both a large scale industrial system and an open source benchmark system. Our proposed methodologies can provide up to 89% reduction in the set of performance counters while detecting performance deviations with few false positives (i.e., 95% average precision). / Thesis (Ph.D, Computing) -- Queen's University, 2013-08-28 23:04:58.774