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Results for “monitoring systems”
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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NNSS Drinking Water Systems and Wastewater Systems Monitoring
Presentation of NNSS Drinking Water and Wastewater 2021 monitoring
Comprehensive Wind Turbine Health Monitoring System
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TXRF Real-Time Low-Cost Monitoring System for Selenium, Mercury and Arsenic
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Method of making a distributed optical fiber sensor having enhanced Rayleigh scattering and enhanced temperature stability, and monitoring systems employing same
A method of making an optical fiber sensor device for distributed sensing includes generating a laser beam comprising a plurality of ultrafast pulses, and focusing the laser beam into a core of an optical fiber to form a nanograting structure within the core, wherein the nanograting structure includes a plurality of spaced nanograting elements each extending substantially parallel to a longitudinal axis of optical fiber. Also, an optical fiber sensor device for distributed sensing includes an optical fiber having a longitudinal axis, a core, and a nanograting structure within the core, wherein the nanograting structure includes a plurality of spaced nanograting elements each extending substantially parallel to the longitudinal axis of the optical fiber. Also, a distributed sensing method and system and an energy production system that employs such an optical fiber sensor device.
Reference electrode and electrochemical monitoring system
A reference electrode includes a metal body, a lead disposed within the metal body, an insulator disposed between the lead and the metal body, the insulator including a ceramic material, and a porous metal chamber coupled to the metal body, the lead extending into the porous metal chamber. The porous metal chamber is configured to maintain an electrolyte solution within the porous metal chamber to establish a redox couple with the lead.
The Amplify Monitoring Team: Initial Design, Development, and Deployment of Seismic Monitoring Systems for Near- Field EGS Well Stimulation.
Abstract not provided.
Development of monitoring system of helium leakage from canister
This paper presents a computational method for the helium leakage from a canister. The governing equations for compressible fluids consist of mass conservation equation in Eulerian description, momentum equations and energy equation. The numerical procedures are divided into three phases, advection, diffusion and acoustic phases, and the equations of compressible fluids are discretized with a finite volume method. Thus, the mass conservation law is sufficiently satisfied in the calculation region. In particular, our computational method enables us to predict the change of the temperature distributions around the canister boundaries by calculating the governing equations for the compressible gas flows, which are leaked out from a slight crack on the canister boundary. In order to confirm the validity of our method, it was applied to the basic problem, 2-dimensional natural convection flows in a rectangular cavity. As a result, it was shown that the naturally convected flows can be reasonably simulated by our method. Furthermore, numerical experiments were conducted for the helium leakage from canister and we derived a close relationship between the inner pressure and the boundary temperature distributions.
Core Monitoring System for TSN EPR Reactors
In the context of Chinese (TSN) EPR reactors project, a new on-line support system was introduced to give information, either continuously or upon request, to the plant operators about some advanced physics parameters corresponding to the current state of the nuclear core. This document provides a description of the functions that are available and the advantages provided by using their results. For each function the Human Machine Interface (HMI) is illustrated. (authors)
Efficiency Calculation for an In-situ Beta Nuclide Monitoring System Based on a Plastic Scintillator - 18193
A plastic scintillator performance for an in-situ measurement system was analyzed using both simulation and experimental methods. The measurement results of four major pure beta-emitting radionuclides - namely H-3. C-14, P-32 and Sr-90/Y-90 - were compared with those from a Monte Carlo N-particle (MCNP) code simulation. Good agreement between the simulation and experimental results was observed for P-32 and Sr-90/Y-90. However, due to the short range of their beta particles in water, the efficiency for both H-3 and C-14 was rather low, and these radionuclides could not be detected. The optimal thickness for the plastic scintillator was identified, as was its suggested diameter. The effect of water depth on system performance was also considered. (authors)
“Development of Fiber Optic Dry Cask Monitoring System to Enhance Safety and Security of Spent Fuel Transportation and Storage
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In-Line Monitoring System for Membrane and Electrode Assembly Manufacturing
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Designing a Molten Salt Reactor Feed Monitoring System
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Networked Powerline Monitoring System
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Using Metal-Organic Frameworks and Enriching Pressure Swing Adsorption Cycles for Future Radionuclide Monitoring Systems
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The Design of an Optimum System for Monitoring the Operational Status of a Spacecraft
The design of a spacecraft monitoring system based on a Neyman-Pearson Detection Criterion is discussed. Each noncatastrophic state of the spacecraft is indicated by the transmission of a specific signal to the ground station. Complete failure of the spacecraft is indicated by the transmission of no signal. The set of signals chosen to represent the spacecraft states consists of a group of orthogonally spaced (in frequency) carriers each with unknown (random) phase.
Inductive System Health Monitoring
The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.