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At least 613 records · Page 34

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Organic Vacuum Pump Fluids for the Vacuum Pumping of Fusion Power Plants

Vacuum pumps are the heart of the fusion fuel cycle, but most currently proposed pumping technologies are not capable of handling the required flow rates and vacuum pressures. Oil-containing vacuum pumps can readily meet the flow requirements, but vacuum fluids will degrade in fusion-relevant environments due to contact with tritium and exposure to high-energy radiation. Here, in this study, we describe a methodology to screen vacuum fluid candidates and purify these candidate fluids post oxidation, post exposure to deuterium, and post exposure to gamma radiation (<7.5 MGy) to simulate a process in which vacuum fluids can be recovered and regenerated during the fusion fuel cycle. A series of oils, including a highly purified mineral oil, phenyl silicone oil, and a polyphenyl ether, are shown to be suitable candidates for vacuum pumping. Additionally, we describe a simple purification methodology to remove oxidized functionalities and the associated isotopologues induced by contact with deuterium from the candidate vacuum fluids This purification methodology can also be applied to radiological damage with moderate effect. Finally, we demonstrate that the sorbents can be regenerated through electromagnetic microwave digestion.

oxidation↗

Plasma confinement state classification in fusion power plants: Profile reflectometer and ensemble diagnostics

As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99% test accuracy.

Clark, Randall [Univ. of California, San Diego, CA↗

Process-based balance of system cost modeling for offshore wind power plants in the United States

This paper describes the development of a process-based and open-source balance of system cost model that provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays caused by weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation. Installation times show reasonable agreement with real data. Project cost sensitivities are investigated to compute the system-level impact of different design choices. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. These values quantify the cost-benefit tradeoffs and show a net-cost savings of decreasing numbers of turbines, increased turbine spacing, and fewer turbine terminations. These results demonstrate that the balance of system model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗

Ultrasonic Measurements of Temperature Distribution in Extreme Environments: Results of Power Plant Testing

The most hardened insertion sensors do not perform reliably in extreme environmental conditions. We address this problem by developing an ultrasonic thermometry system for the measurements of segmental temperature distributions (MSTD) in solid materials and, specifically, across containments of energy conversion processes. The MSTD approach uses an echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features. In pulse-echo mode, these features produce a train of echoes in response to an external pulse of ultrasonic excitation created and acquired by a transducer located outside the extreme environment. The delays between the echoes encode the information on the temperature distribution in the corresponding segments of the ultrasonic propagation path, which we use to reconstruct an unknown temperature profile. This note describes the preliminary results and initial experience in applying the developed MSTD ultrasonic thermometry system to the measurements of temperatures in a utility-scale 500MW coal-fired boiler.

John, Mason↗