This study has evaluated the degradation processes which will potentially affect the reinforced concrete structures of a nuclear power generation facility during and beyond its original design life. This task was undertaken in consideration of the feasibility of extending the life of nuclear power plants beyond their current license expiration dates. Following the identification of deterioration mechanisms which are expected to occur, an inspection system was developed to correctly assess and document the condition of the reinforced concrete components during their service life. Twenty-eight out of thirty-nine possible degradation modes are deemed likely to affect Surry’s reinforced concrete structures. The majority of these modes are visually evident in their incipient stages. Currently available nondestructive testing methods were assessed to determine their applicability to detect modes which are not visually evident or to determine the extent of deterioration due to other modes. It was found that many nondestructive testing methods are currently lacking in reliability, portability, or ease of application. Consequently, the developed inspection program is based primarily on visual inspections performed by qualified inspectors. This report was prepared under the authority of Virginia Power Company in conjunction with the Surry Unit One life extension study. It is the conclusion of this report that reinforced concrete degradation will in no way impair the usefulness or safety of the concrete structures of a nuclear facility during the 40 year design life provided actions are taken to implement a concrete inspection program similar to that which is described within. This program will allow the detection of potentially critical situations thereby directing the maintenance and repair activities necessary to insure the feasibility of extended life. / Master of Science

In this work, a thermoelectric energy harvester system aimed at harvesting energy for locally powering sensor nodes in nuclear power plant coolant loops has been designed, fabricated and tested. Different mathematical modeling methods have been validated by comparing with experimental results. The model developed by this work has the best accuracy in low temperature range and can be adapted and used with any heat sink, heat pipe, or thermoelectric system, and have proven to provide results closely matching experimental data. Using the models, an optimization of the thermoelectric energy harvesting system has been performed which is applicable to any energy harvester of this variety. With experimental validation, the system is capable of generating sufficient energy to power all the sensors and electronical circuits designed for this application. The effect of gamma radiation on this thermoelectric harvester has also been proved to be small enough through radiation experiment. / Master of Science

Electrical cabinet fires occur frequently in commercial and industrial facilities. However, the severity of these fire events varies widely, making it difficult to estimate the fire growth and size with certainty. This study aims to identify the significant parameters that affect electrical cabinet fires, which are quantified as the heat release rate (HRR), and properly categorize them. With this knowledge, optimal parameter-response relationships can be developed to predict the electrical cabinet fire behavior. Statistical analysis conducted in this study on historical fire incident data revealed that the fires in Nuclear Power Plants (NPP) were primarily associated with electrical cabinets. The database used in this research was an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute, including 2,111 fire events. 540 of these events were labeled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. Electrical cabinets were found to represent a majority (40.7%) of all the challenging fire events. Although historically conducted electrical cabinet fire experiments sought to explore the influence of parameters on HRR, the parameters were not systematically varied to statistically quantify which parameters were most important/relevant. Research in this study used statistical analysis on a series of simulation results on electrical cabinet fires from the computational fluid dynamics code Fire Dynamic Simulator (FDS). Simulation matrices were developed and evaluated using fractional factorial Design of Experiments (DOE) to screen the importance of different parameters on the electric cabinet HRR. Based on statistical analysis of the results, the combustible material surface area was found to be the most significant parameter followed by cabinet volume, combustible configuration, burning duration, and combustible material heat release rate per unit area. Material ignition temperature was found to not be statistically significant. The last phase of this research assessed the robustness of the electrical cabinet parameters on the predicted HRR with more detailed simulations. Two investigations were undertaken. To identify the nonlinear effects of parameters on the electrical cabinet fire HRR, a Response Surface Methodology (RSM) based Central Composite Design (CCD) was used to create a simulation matrix that would allow statistical analysis of important parameters as well as their effects on the fire heat release rate while keeping the combustible configuration inside the cabinet constant. A series of simulations were conducted to explore the impact of combustible configuration and ignition source location while keeping all other variables consistent. The analysis revealed that all variables had a statistically significant effect on peak HRR. For the average HRR, both the ventilation area into the cabinet and the ignition source HRR were found to be statistically insignificant. For both output variables, the cabinet volume, material heat release rate per unit area, and material surface area were the most significant parameters. Combustible configuration and ignition source location were also found to be statistically significant. / Master of Science / Electrical cabinet fires are a significant concern for industries, commercial electric plants, telecommunication buildings, and nuclear power plant (NPP) facilities. These cabinets typically represent a metallic enclosure of varying sizes. Additionally, several different electronic components of heterogenous composition and configuration are included within this cabinet. As a result, the fires within the cabinet can propagate to several other nearby components, resulting in large fires that are difficult to suppress. Thus, it becomes necessary to understand the fire behavior of electrical cabinets and the factors influencing fire propagation. Knowing the factors influencing the electrical cabinet fires will enable facilities to have better fire resilience and further prevent multiple components and structures from being damaged by these fires. Statistical analysis of historic fire events validated that the most frequently challenging fires in NPP involve electrical cabinets.Therefore, aA detailed study was conducted to investigate what parameters most significantly affect the size of the electrical cabinet fire, which is quantified as the heat release rate (HRR). The parameters in the study included cabinet volume, ventilation area, combustible fuel detail (ignition temperature, heat release rate per unit area (HRRPUA), burning duration), fuel configuration inside the cabinet, and size of the ignition source. To determine which of these factors significantly impacted the electrical cabinet HRR, a computational fluid dynamics code Fire Dynamic Simulator (FDS), was used to predict the fire growth of electrical cabinet fires. After employing a rigorous statistical analysis of the FDS results, the combustible material surface area was found to be the most significant parameter, followed by cabinet volume, combustible configuration, burning duration, and flammable material HRRPUA. The last phase of the research sought to explore the significance of the parameters while developing a nonlinear expression to predict the fire HRR based on cabinet parameters. Given the wide range of electrical cabinet parameters, especially combustible configuration, two studies were conducted where the configuration was fixed or varying with respect to other parameters. For fixed combustible configuration, simulations were conducted with FDS systematically varying the other parameters so their importance could be ranked. Simulations were also performed with all parameters fixed except the combustible configuration and ignition source location. The analysis revealed that all variables had a statistically significant impact on peak HRR. For the average HRR, both the ventilation area into the cabinet and the ignition source HRR were found to be statistically insignificant. For both output variables, the cabinet volume, material heat release rate per unit area, and material surface area were found to be the most significant parameters. Combustible configuration and ignition source location were also found to be statistically significant.

The safety of nuclear power plants must be proved, certified and improved. Probabilistic safety assessments are used to estimate the core meltdown risk, by means of sequential analyses of accidents. In order to assess probabilities of the appearance of these sequences, it is necessary to specifically assess probabilities of operation failures accomplished by human operators in a degraded mode. For this purpose, EDF, the French producer of electricity, developed a method that models failures of human actions, by means of a systematic determination of scenarios corresponding to different failure modes. This method, called MERMOS, has been used for several probabilistic safety assessments. In order to increase its reproducibility and to make it more robust, example missions and scenarios will be built. This set of example analyses will be used by experts assessing human reliability: they will develop studies and deduce results more easily. The purpose of this study involves the creation of a methodology to model existing analyses and human reliability data used in MERMOS. This study consists of optimizing a second generation human reliability assessment method in order to overpass its current weaknesses in an operational context by means of the identification of a set of example analyses. / Master of Science

Humboldt-Universiẗat, Diss.--Berlin, 2007. / Nebent.: Stilllegung von Kernkraftwerken. Includes bibliographical references (p. 247-264).

Thesis (M. Phil.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf 245-252).

Thesis (MTech (Quality))--Cape Peninsula University of Technology, 2011. / This research project in Procurement Quality Engineering was conducted at a Nuclear Power Generation Company in the Western Cape, South Africa. During the past decade, quality management has become increasingly recognised as highly desirable for all organisations at all levels. All organisations, to varied degrees, can benefit from the application of quality management skills in some parts of their daily operations. The research project will investigate the impact or effect of late deliveries of spares on the operational cost of the organisation. The organisation is not aware what impact the delivery of spares has on operating costs. Against the above background, the problem to be researched within the ambit of this dissertation reads as follows: "Poor product and / or service delivery from Vendors and / or Suppliers have an adverse impact on the output of the Procurement Quality Department" .The primary research objectives of this study are the following: ~ To emphasise the importance of quality within the supply chain. ~ To investigate the impact of non-conforming items delivered to a Nuclear Power Plant. ~ To determine measures which can be put in place to improve communication between suppliers, vendors, buyers and procurement quality engineering. ~ To determine or investigate the cost of poor quality in the organisation. ~ To improve the quality of goods and services through the application of a quality management system within the supply chain. The research method used in this research project involved both qualitative and quantitative research processes. Questionnaires and statistical techniques were used to analyse the data, and to draw conclusions and recommend possible areas for improvement. The research methodology falls within the ambit of a case study.

abstract: This study explores the potential risks associated with the 65 U.S.-based commercial nuclear power plants (NPPs) and the distribution of those risks among the populations of both their respective host communities and of the communities located in outlying areas. First, I examine the relevant environmental justice issues. I start by examining the racial/ethnic composition of the host community populations, as well as the disparities in socio-economic status that exist, if any, between the host communities and communities located in outlying areas. Second, I estimate the statistical associations that exist, if any, between a population's distance from a NPP and several independent variables. I conduct multivariate ordinary least square (OLS) regression analyses and spatial autocorrelation regression (SAR) analyses at the national, regional and individual-NPP levels. Third, I construct a NPP potential risk index (NPP PRI) that defines four discrete risk categories--namely, very high risk, high risk, moderate risk, and low risk. The NPP PRI allows me then to estimate the demographic characteristics of the populations exposed to each so-defined level of risk. Fourth, using the Palo Verde NPP as the subject, I simulate a scenario in which a NPP experiences a core-damage accident. I use the RASCAL 4.3 software to simulate the path of dispersion of the resultant radioactive plume, and to investigate the statistical associations that exist, if any, between the dispersed radioactive plume and the demographic characteristics of the populations located within the plume's footprint. This study utilizes distributive justice theories to understand the distribution of the potential risks associated with NPPs, many of which are unpredictable, irreversible and inescapable. I employ an approach that takes into account multiple stakeholders in order to provide avenues for all parties to express concerns, and to ensure the relevance and actionability of any resulting policy recommendations. / Dissertation/Thesis / Ph.D. Environmental Social Science 2014

The purpose of this thesis is to analyze: (a) the determinants of the global price of uranium; and (b) how this price could be affected by different nuclear power generation scenarios for 2030. To do this a multivariable regression analysis will be used. Within the model, the price of uranium is the dependent variable and the independent variables are generated nuclear power electricity representing demand (GWh), price of coal as a substitute to generated nuclear power electricity, and the price of oil representing uranium production costs. The empirical results show that generated nuclear electricity and the oil price, to be statistically significant at the 5 percent level. The coal price was not however a statistically significant. The scenarios for 2030 are three possible nuclear power generation demand cases; high, medium and low demand. The results for the high demand generated a price of 255 US$/kg and the medium demand 72US$/kg.

Energy production systems are essential for human progress. They fuel the technologies that underpin economic growth and are prerequisite for efficient food production, education and healthcare. On the flip side, they also incur substantial eco-social costs. Hence, finding and promoting sustainable means of energy production is a key topic within the Environmental Sciences. This thesis examines the sustainability of nuclear power, by comparing its social, economic and ecological impacts to those of wind and solar power. The assessment is performed using Multi-Criteria Analysis (MCA), with a Weighted Sum scoring system and a Distance-To-Target weighting scheme. The selection and the weighting of the indicators are grounded in the Planetary Boundaries framework, the Oxfam Doughnut Economics model and the UN’s Sustainable Development Goals, and the technologies are compared on 9 axes of evaluation; greenhouse gas emissions, land-take requirements, material throughput, non-recyclable wastes, toxic and radioactive wastes, negative health impacts, economic costs, intermittency and energy return on energy invested. The thesis finds nuclear power to be the most sustainable option according to all but three indicators, and in the unified analysis, it outcompetes wind and solar by a factor of 2 and 3 respectively. Also notable is that solar power does not excel in a single impact category; it has the highest greenhouse gas emissions, the largest land-take, and it is costly, intermittent and energy-inefficient. It is also a source of toxic pollution, the effects of which cannot yet be determined. Although wind is more competitive, it consumes vast amounts of physical resources, generates a lot of waste, and its land-take is at least 10 times higher than that of nuclear power. In addition to the MCA, the thesis investigates three perceived threats that are often raised in criticisms of nuclear power; the risk of nuclear fuel depletion, the risk of nuclear weapons proliferation and the risk of catastrophic nuclear accidents. The results show that many popular arguments against the technology are loosely aligned with reality, and the thesis as a whole presents a challenge to the notion that nuclear power is a dangerous and unsustainable energy source.