Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensor Utilization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Introduction of Chalcogenide Glasses to Additive Manufacturing: Nanoparticle Ink Formulation, Inkjet Printing, and Phase Change Devices Fabrication

Abstract Chalcogenide glasses are one of the most versatile materials that have been widely researched because of their flexible optical, chemical, electronic, and phase change properties. Their application is usually in the form of thin films, which work as active layers in sensors and memory devices. In this work, we investigate the formulation of nanoparticle ink of Ge–Se chalcogenide glasses and its potential applications. The process steps reported in this work describe nanoparticle ink formulation from chalcogenide glasses, its application via inkjet printing and dip-coating methods and sintering to manufacture phase change devices. We report data regarding nanoparticle production by ball milling and ultrasonication along with the essential characteristics of the formed inks, like contact angle and viscosity. The printed chalcogenide glass films were characterized by Raman spectroscopy, X-ray diffraction, energy dispersive spectroscopy and atomic force microscopy. The printed films exhibited similar compositional, structural, electronic and optical properties as the thermally evaporated thin films. The crystallization processes of the printed films are discussed compared to those obtained by vacuum thermal deposition. We demonstrate the formation of printed thin films using nanoparticle inks, low-temperature sintering and proof for the first time, their application in electronic and photonic temperature sensors utilizing their phase change property. This work adds chalcogenide glasses to the list of inkjet printable materials, thus offering an easy way to form arbitrary device structures for optical and electronic applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Matrix Completion for Improved Observability in Low-Voltage Distribution Grids

This paper considers the problem of recovering missing entries in a partially observed matrix from relatively few measurements (i.e., the so-called matrix completion problem) with the aim of increasing the presently limited observability of low-voltage distribution grids. To this end, the partially observed matrix is formed using scarce voltage magnitude measurements while accounting for their spatial information. Voltage readings are assumed to be collected from distribution utility sensors and/or geographically-distributed cable television network sensors located in immediate proximity to distribution grid nodes. A matrix completion approach built on the parameter-less singular value shrinkage technique is used to estimate voltage magnitudes at otherwise non-observable low-voltage nodes using a small number of single- or multiple-snapshot data. The effectiveness of the proposed approach is demonstrated using a U.S.-style distribution test system from the synthetic SMART- DS data set under very low- to moderate-observability conditions.

low-rank matrix completion↗
DOE OSTI2021

Selective volatile organic compound gas sensor based on carbon nanotubes functionalized with ZnO nanoparticles

Here this paper describes the theory and results for a new class of low-cost chemoresistive gas sensors designed for selective hydrocarbon gas detection. The sensors utilize a multiwalled carbon nanotube (MWCNT) backbone functionalized with metal oxide nanocrystals. Specifically, nanoparticles were grown on the surface of the MWCNTs using atomic layer deposition. The crystallinity of the ZnO-MWCNTs' heterostructure was examined by using a high-resolution transmission electron microscope. The structure of the ZnO/MWCNTs was analyzed using a scanning electron microscope and energy dispersive x ray. The Hall effect measurement shows p-type characteristics of the MWCNTs, supporting the typical PN junction formation with n-type ZnO nanocrystals. The electron-donating ability of ZnO provided a strong response to the ppm levels of toluene at room temperature (25 °C) and showed strong selectivity with other volatile organic compound gases such as benzene, methane, and formaldehyde.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Metal nanoparticle-decorated nanotubes for gas sensing

Disclosed herein are embodiments of compositions for gas sensing and sensors utilizing the same. In one embodiment, a composition comprises carbon nanotubes and and polymer-coated metal nanoparticles bound to the carbon nanotubes.

Iftime, Gabriel↗
DOE OSTI2025

Investigation of the Performance and Explainability Tradeoffs for Machine-Learning Models for Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Predictive maintenance (PdM) has shown great potential for achieving substantial cost savings and enhancing the economic competitiveness of nuclear power plants (NPPs) in today's energy market. Among the different modeling approaches that exist, machine learning (ML) tools in particular have a demonstrated ability to handle high dimensional and multivariate data and to extract hidden relationships within data in industrial environments. While ML methods show great potential, their lack of explainability---especially for black-box models---is a major hurdle to their adoption. Moreover, considering the supposed trade-off between explainability and performance challenges, careful consideration must be made as to which of these quality aspects takes precedence in light of multiple modeling options, resource availability, and domain characteristics. The present work evaluates the performance of six ML models, each with a different degree of explainability, in classifying the conditions of circulating water pumps (CWPs) by utilizing sensor data from nuclear power plants. To determine the drivers behind the trade-offs presented by this array of models, this work also tests different combinations of CWP units as the training and testing data, degrees of data imbalance, and objective functions for hyperparameter tuning. It was found that black-box models tend to afford superior performance in cases where there are far more instances of one type of labeled data than of any other type. It is recommended that a guided procedure be followed for designing and delivering an ML system that is sufficiently explainable to all involved stakeholders.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Use of Micro-Gravity Sensors for External Fluid Level Monitoring in Waste and Nuclear Related Applications - 20315

There are a number of applications in nuclear energy and hazardous waste disposal that require monitoring of fluids under extreme environments, including high levels of temperature, pressure, toxicity and radioactivity. Many of these applications will benefit from a monitoring technique that is external and non-invasive. Currently the sensors used are invasive, must reside inside the pressurized vessels and must penetrate the vessel walls, which can create a weakness in the vessel. Additionally, instruments that are used inside such containers must be exceptionally hardened to the environment. Information Systems Laboratories (ISL) has developed an external mass (gravimetric) measuring technique for monitoring nuclear coolant in Small Modular Reactors (SMRs), which will also work for measuring fluid levels in waste tanks, that avoids the problems inherent in invasive sensors. It utilizes a COTS gravitational sensor of unprecedented accuracy, leveraged via proper sensor placement geometry, to detect fluid changes of small amplitude from an outside position, obviating the need to penetrate the vessel. The technique is called Gravisense{sup TM}. ISL has proven via simulation and experiment that this concept can be usefully applied to monitoring fluid levels in both nuclear reactors and large waste tanks. Numerical simulation algorithms were developed to calculate the gravity effect of small changes in water level, which were verified by experiments at the NIST Physical Simulator facility at the Oregon State University. The measured ultralow noise levels of the superconducting gravimeter type which utilizes a Niobium sphere suspended in a magnetic field to attain its phenomenal accuracy, demonstrated that fluid levels in SMRs can be measured at least to within 3 cm. Furthermore, the method can distinguish between a contained leak (from reactor to containment vessel) from an external leak (from reactor to outside of containment). Additionally, simulations of waste canisters that hold spent fuel rods show that the fluid level measuring accuracy can potentially do better than 1 cm accuracy by measuring from below the vessel, and judicious placement of sensors on top of large waste tanks can potentially achieve a very impressive 2 mm measurement accuracy. These encouraging results prove that the Gravisense{sup TM} technique for fluid determination can be very useful in nuclear energy generation, testing, and research, as well as in waste monitoring situations that are difficult to monitor via traditional sensing technology. We believe that the next step should be to test the technique on canisters of the type that are currently storing waste in various DOE locations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Feasibility Study of Millimeter Wave Radars For Safeguards Applications

Containment and surveillance are fundamental measures in nuclear safeguards. Techniques such as video surveillance and laser curtain for containment provide effective monitoring in areas where maintaining continuity of knowledge is required. These systems, however, can be susceptible to loss of monitoring capabilities under certain environmental conditions such as poor visibility (i.e. low light conditions, smoke, fog, etc.) or extended power loss past the duration that the backup power system is designed for. Brookhaven National Laboratory has been investigating the feasibility of millimeter waves (mmWave) as a new perimeter seal in which radio frequency waves in the range of 60-64 GHz are used to detect and monitor objects of interest. Signals in this frequency range are not susceptible to environmental conditions. For proof-of-concept tests, mmWave sensors from Texas Instruments (TI), specificallyIWR6843, are used in a test bed at BNL's Waste Management facility to simulate the operations at nuclear facilities. The unique design of TI mmWave sensors requires less memory and power consumption compared to counterpart systems. These devices are capable of exporting 3D point-cloud data, which is visualized graphically and compared to videos recorded at the same time to validate the performance of the mmWave sensor. A set of experiments were planned to test the feasibility of the mmWave in this application, including monitoring static containers in a storage area and detecting intrusions at the boundaries of the area. In addition, the experiments also identify potential blind spots relative to sensor position and utilize multiple operating sensors simultaneously to reduce or eliminate such blind spots. The optimal positioning of multiple sensors was determined for the experimental room configuration. In this paper, we will discuss the details of this novel perimeter sealing concept and present the test results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Embedded sensors integrated into critical components for in situ health monitoring of steam turbines

Operational flexibility is desired in today’s coal-fired power plants to balance power grids by compensating for the variable electricity supply from renewable energy sources and distributed gensets. This demanding requirement accelerates materials degradation and makes in-situ health monitoring essential. Life monitoring of components and subsystems is thus seen as essential in assessing material and mechanical behavior to estimate system reliability, move to a conditionbased maintenance strategy and determine time to failure of the units in their actual operating conditions. Vibration monitoring can be exploited for blade tip timing to measure blade vibration amplitude and tip clearance to detect any deterioration taking place in the condition of steam turbine blades. A failure of a rotating blade can lead to severe turbine damage followed by extensive repairs and loss of power production. A blade vibration monitoring system can help early detection of abnormal blade vibration behavior. In conjunction with a health monitoring system, the vibration characteristics can be analyzed to support a pro-active maintenance and inspection schedule. While the feasibility of this inspection technique has been amply demonstrated, there is a need to install induction probes to magnetize the blade for signal output. Siemens, in partnership with Raytheon Technologies Research Corporation (RTRC), proposes a holistic approach to develop embedded sensors to utilize radio frequency for not only coupling to sensors, but as the sensing modality. The goal of this project is to “embed” the novel sensing approach by using either additively manufactured or extruded waveguides on rotating blades for recording, evaluation and monitoring of blade vibrations in Low Pressure turbines, with applications extending to aero engines

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

A magnetic sensor using a 2D van der Waals ferromagnetic material

Two-dimensional (2D) van der Waals ferromagnetic materials are emerging as promising candidates for applications in ultra-compact spintronic nanodevices, nanosensors, and information storage. Our recent discovery of the strong room temperature ferromagnetism in single layers of VSe2 grown on graphite or MoS2 substrate has opened new opportunities to explore these ultrathin magnets for such applications. In this paper, we present a new type of magnetic sensor that utilizes the single layer VSe2 film as a highly sensitive magnetic core. The sensor relies in changes in resonance frequency of the LC circuit composed of a soft ferromagnetic microwire coil that contains the ferromagnetic VSe2 film subject to applied DC magnetic fields. We define sensitivity as the slope of the characteristic curve of our sensor, df0/dH, where f0 is the resonance frequency and H is the external magnetic field. The sensitivity of the sensor reaches a large value of 16×106Hz/Oe, making it a potential candidate for a wide range of magnetic sensing applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Technology Maturation of Wireless Harsh Environment Sensors For Improved Condition Based Monitoring Of Coal Fired Power Generation

The overall goal of this project was to demonstrate and develop the usage of high-temperature (HT) harsh-environment (HE) wireless surface acoustic wave resonator (SAWR) sensor technology to promote reliable maintenance through condition-based maintenance (CBM) for field applications in harsh service conditions associated with power plant environments. The project aimed to advance the HT HE wireless SAWR sensor technology from TRL 5 to TRL 7. In addition to HT HE wireless temperature sensing, efforts were dedicated during this project to investigate, develop and increase the TRL from 3 to 5 for the following technologies: (a) HT HE strain sensors to address additional CBM monitoring needs, such as boiler tube mechanical / thermal stresses, which can provide early indications for boiler tube cracking and failure; and (b) HT aluminum nitride (AlN) and scandium aluminum nitride (ScAlN) based piezoelectric thin film fabrication and implementation of SAW sensors, with the goal of releasing the need to use single crystal piezoelectric materials for SAWRs and thus broaden possible technology applications to non-planar and harder to modify surfaces. To achieve the goals mentioned above, UMaine and its partner, Environetix Technologies Corporation, established partnerships with the following power plants: Longview Power (Maidsville, WV), a coal-fired power plant; Penobscot Energy Recovery Corp (PERC, Orrington, ME), a waste-to-energy power plant; and the UMaine Steam Plant (Orono, ME), an oil / natural gas power plant. To realize wireless HT HE SAWR sensor systems in these harsh service conditions, the University of Maine research team worked with Environetix and these power plants to define, design, fabricate, test and validate a mature prototype wireless temperature SAWR sensor system for boiler tube applications within the HT HE of the reheater pass damper chamber to directly and wirelessly monitor the temperature at eighteen independent boiler tube locations. The system included three levels, or “tiers”, of wireless communication to enable remote monitoring: Tier 1, the wireless link in the reheater pass damper chamber directly accessing the sensors on the boilers; Tier 2, the wireless local area network link, transmitting processed sensor information within the power plant to the Tier 3, a commercial wireless signal carrier company for secure remote data monitoring outside of the power plant. Regarding the wireless sensor system installed at Longview Power, temperature information from the boilers was continuously transmitted from the Longview boilers at Maidsville, WV, to Environetix headquarters, Orono, ME, over a 34 month period, when the system was finally decommissioned. Strain sensors and piezoelectric ScAlN thin film sensors were successfully installed on the exhaust duct at the UMaine Steam Power plant. The advances in wireless strain sensors and thin film piezoelectric film fabrication and testing were performed mostly in UMaine laboratories and field tested at the UMaine Steam Plant, due to its close proximity to UMaine/Environetix, access to the plant facility, and due to difficulties in accessing the other power plants during the COVID shut-down period. The project accomplished the TRL level increase of the targeted CBM technologies through the successful fabrication, installation, test, and validation of dedicated and commercial wireless sensor systems, utilizing the three different power plants. The outcomes of this project, including the wireless sensor data capability, are expected to yield an advance for CBM in harsh power plant environments. The reduction of maintenance costs, improved safety during plant operation, and increased power plant efficiency will lead to increased revenues (i.e., fewer forced outages) due to better process monitoring enabled by the wireless HT HE SAWR temperature sensor technology.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Multi-sensor agent devices

Apparatus, methods, and systems implementing multi-sensor agent devices are described herein. The agent devices can each include a plurality of sensors for measuring parameters of interest to an entity such as an electric power utility. The sensors can be organized in individually-IP-addressable sensor clusters, with each sensor cluster including an associated microcontroller. The agent devices can be controlled by a control center of the entity to operate in a coordinated manner, such as to gather and transmit data regarding parameters of interest. The agent devices can be transported to desired areas for data collection by unmanned aerial systems such as drones, and the collected data can be stored in a distributed blockchain ledger.

Fuhr, Peter L.↗
DOE OSTI2024

Sensor Qualification for the Development of Advanced Reactors

A temperature sensor qualification device is undergoing development and testing in order to qualify temperature sensors for advanced reactor metrology applications. This device will provide National Institute of Standards and Technology (NIST) traceable performance testing of temperature sensors while under the high radiation environments experienced while in-core. This is completed by utilizing retractable sensors which transfer the measurements from ex-core to in-core sensors. A detailed discussion of the uncertainty propagation associated with this comparative process is provided. Experimental testing of the temperature distribution occurring in the device has begun and is reported on. It is pertinent to minimize this temperature distribution to prevent variation in sensor measurements. This variation will be indistinguishable from sensor drift for in-pile applications and would result in unnecessarily conservative uncertainty bounds.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2020

A Review of Existing Test Methods for Occupancy Sensors

One of the key new features of connected lighting systems (CLS) is their ability to collect data from various types of integral sensors and share that data with other lighting or building systems. Occupancy and vacancy sensors have been widely adopted as an energy-saving strategy in buildings, yet published test methods for reproducibly characterizing their performance remain few and limited in their sophistication. As a result, it has been difficult to predict the performance of such sensors in a specific application, and in practice, they frequently do not meet energy-savings expectations. Occupants at times remove or otherwise bypass occupancy sensors that hinder their work or otherwise do not perform as expected, thereby compromising the sensors’ potential to reduce energy consumption. Poor performance can result from multiple causes – ranging from fundamental limitations of the sensor technology, to misconfiguration, to poor placement in the room or space. Innovative occupancy sensors, some of them combining multiple sensing technologies (i.e., multimodal), have come on the market over the years, with claims of improved performance compared to their predecessors. However, in practice, their performance has neither differed enough from the performance of previous products to necessitate a test method that facilitated comparison between them, nor has it led to high deployment or high user satisfaction in human-occupied spaces with persistent presence. While the performance of both common and novel occupancy sensors has been the subject of many published research articles, the test methods that have been employed for them typically have been loosely described and have incorporated custom equipment or techniques that render them difficult to reproduce, or have been limited in their ability to fairly characterize devices that utilize varying sensor technology. The lack of a fully described, technology-agnostic test method that yields reproducible results across different implementations has been a barrier to the commercial success of new occupancy-sensor products, as users and specifiers who have been disappointed with previous products are often unwilling to take a chance with new ones. Motivated by a desire to fairly characterize new technologies that continue to enter the market and claim not only improved occupancy detection but, in some cases, additional capabilities (e.g., the ability to measure traffic or discern between different object types), this report presents the results of a literature review of recently published fully described test methods for characterizing occupancy-sensor performance, as well as research articles containing ad-hoc test methods. The review also identifies and consolidates test conditions for characterizing sensor performance in indoor spaces and identifies apparent test method gaps that need to be filled in order to evaluate emerging technologies and products. The identified test-method conditions are intended to enable the development of a future technology-agnostic test method that facilitates occupancy-sensor performance characterization more-accurately representing performance in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Chalcogenide Glass-Capped Fiber-Optic Sensor for Real-Time Temperature Monitoring in Extreme Environments

We demonstrate a novel chalcogenide glass (ChG)-capped optical fiber temperature sensor capable of operating within harsh environment. The sensor architecture utilizes the heat-induced phase change (amorphous-to-crystalline) property of ChGs, which rapidly (80–100 ns) changes the optical properties of the material. The sensor response to temperature variation around the phase change of the ChG cap at the tip of the fiber provides abrupt changes in the reflected power intensity. This temperature is indicative of the temperature at the sensing node. We present the sensing performance of six different compositions of ChGs and a method to interpret the temperature profile between 440 °C and 600 °C in real-time using an array structure. The unique radiation-hardness property of ChGs makes the devices compatible with high-temperature and high-radiation environments, such as monitoring the cladding temperature of Light Water (LWR) or Sodium-cooled Fast (SFR) reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Acoustic MEMS Sensor Array for Quench Detection of CICC Superconducting Cables

Here, a novel quench detection method using micro-electro-mechanical system (MEMS) sensor technology has been investigated in use for high temperature superconducting (HTS) conductors such REBCO tape cables. The sensor array along a superconducting cable, such as a cable-in-conduit-conductor (CICC), is installed in a cooling channel. It will allow sensitive and quick detection for a local quench of a superconducting cable. This work has confirmed that a quench of a single REBCO tape can be detected in liquid nitrogen by a MEMS piezoelectric microphone sensor. The quench detection design utilizing a MEMS sensor array method is discussed for the case of a toroidal field (TF) magnets of a fusion Tokamak device.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Acoustic MEMS Sensor Array for Quench Detection of CICC Superconducting Cables

A novel quench detection method using microelectro- mechanical system (MEMS) sensor technology has been investigated in use for high temperature superconducting (HTS) conductors such REBCO tape cables. The sensor array along a superconducting cable, such as a cable-in-conduit-conductor (CICC), is installed in a cooling channel. It will allow sensitive and quick detection for a local quench of a superconducting cable. This work has confirmed that a quench of a single REBCO tape can be detected in liquid nitrogen by a MEMS piezoelectric microphone sensor. The quench detection design utilizing a MEMS sensor array method is discussed for the case of a toroidal field (TF) magnets of a fusion Tokamak device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗