Development of a BWR System Fault Simulator Using TRANSFORM/Modelica
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Abstract not provided.
Solvent extraction is used to separate metals or other complexes into two different immiscible liquids and is an essential component of the PUREX Process. Improvements to the solvent extraction process can directly contribute to an organization’s ability to ensure the purity and recovery of special nuclear materials from spent nuclear fuel. Such improvements can benefit nuclear reprocessing efforts, increase fuel reutilization, and limit the concentration of actinides in nuclear waste repositories.
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A system determines the frequency of grid signals corresponding to an electrical grid in real time. The system includes a transient detector that monitors a grid signal from a voltage meter or a current meter connected to the electrical grid. The system produces, in real time and at a sampling rate, a deviation signal indicative of a periodicity of the monitored grid signal. The system determines, over one or more cycles of the monitored grid signal, a measurement signal corresponding to the deviation signal. The system determines a frequency signal that corresponds a frequency estimation of the monitored signal by applying a frequency estimation when values of the measurement signal are less than a deviation threshold and maintaining the frequency signal at a constant value when values of the measured signal equal or exceeds the deviation threshold.
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We propose a novel floating-point encoding scheme that builds on prior work involving fixed-point encodings. We encode floating-point numbers using Two's Complement fixed-point mantissas and Two's Complement integral exponents. We used our proposed approach to develop quantum algorithms for fundamental arithmetic operations, such as bit-shifting, reciprocation, multiplication, and addition. We prototyped and investigated the performance of the floating-point encoding scheme on quantum computer simulations by performing reciprocation on randomly drawn inputs and by solving first-order ordinary differential equations, while varying the number of qubits in the encoding. We observed rapid convergence to the exact solutions as we increased the number of qubits and a significant reduction in the number of ancilla qubits required for reciprocation when compared with similar approaches.
This final report describes the methods and results of applying Spread Spectrum Time Domain Reflectivity (SSTDR) for String Monitoring in PV Power Plants for DE-EE0008169. The project created a new system for both detecting and locating electrical faults in photovoltaic systems. In this work, we address photovoltaic electric faults that are both common and costly. Based on interviews with photovoltaic power plant owners, operators, and maintainers, three types of faults are common and of significant interest: disconnects, ground faults, and arc faults. Disconnects can originate from many sources. They are often due to everyday events, such as lawnmowing (accidentally running over a cable), animals eating through the cables, or degradation that occurs over time due to corrosion or general degradation. Ground faults occur when the cables (for example, due to frayed insolation) connect to the ground, relaying current into the ground. These faults are particularly problematic since the ground faults are often intermittent. That is, ground faults commonly appear during rain storms due to a change in soil conductivity and then disappear when the rain ends. This makes the ground fault difficult to find because while current systems can detect the overall change in voltage and current associated with a ground fault, technicians are necessary to locate the fault. As a result, ground faults may disappear before the technician arrives at the power plant. Hence, locating and fixing ground faults often require multiple trips. We also study arc faults, which can result when nearby conductors create an arc of electrical current through the air. While less common, arc faults can be extremely dangerous. The energetic electrical arc can cause fires and destroy equipment, costing significant damage. Overall all three types of faults cost owners and operators money, either from the destruction of equipment or from technician time. Furthermore, while devices exist for detecting ground faults (ground fault circuit interrupters) and arc faults (arc fault circuit interrupter), these systems only search patterns of electrical current that correspond to each fault. This information cannot be used to locate the fault. In addition, these protection systems experience nuisance trips due to nearby electromagnetic interference, such as from a lawn mower or other motors that produce significant amounts of electromagnetic radiation. Hence, the overall goal of this project is to create an SSTDR tool that provides photovoltaic power plants with more reliable fault detection in addition to the localization of faults. SSTDR works by transmitting electrical signals into the photovoltaic string. Those signals reflect from impedance discontinuities (i.e., disconnects, ground faults, and arc faults). These faults are then detected by measuring the presence of a reflection at the SSTDR and can be located by identifying the location of that reflection in time. In addition, unlike current protection systems, these systems do not experience nuisance trips since their low amplitude, high frequency, and coded signal can by analyzed without interference from the regular operational voltage on the photovoltaic string.