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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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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Microstrip patch antenna for simultaneous temperature sensing and superstrate characterization

This paper investigates a microstrip patch antenna for measuring the thickness and dielectric constant of the medium above the antenna (i.e. the superstrate) as well as the temperature. The intended application is simultaneous sensing of ash accumulation and temperature inside a boiler, with the aim of enhancing safety, improving efficiency, and reducing downtime associated with maintenance. A patch antenna, consisting of a dielectric substrate, a radiation patch, and a ground plane, functions as an electromagnetic resonator with specific fundamental frequencies. A dielectric medium placed above the patch antenna changes its effective dielectric constant and thus its resonant frequencies. Meanwhile, temperature also influences the antenna frequencies because of the thermal expansion of the conductors (i.e. the radiation patch and ground plane), and the dielectric constant of dielectric materials due to their temperature dependency. Since a rectangular patch antenna has two fundamental frequencies, it enables determining these two parameters simultaneously. Once the temperature and superstrate thickness are determined, the dielectric constant of the superstrate and its temperature dependency can also be extracted. To demonstrate this capability, a dual-frequency patch antenna was designed, fabricated, and characterized with a superstrate of various thicknesses and at different temperatures. By fitting the antenna resonant frequencies as functions of the superstrate thickness and temperature, these two parameters were inversely determined from the measured antenna frequencies. Using ash from charcoal briquettes as a superstrate, the measurement uncertainties were determined to be ±0.58 °C and ±58.05 μ m for the temperature and the superstrate thickness respectively. The dielectric constant of the ash was found to be 2.64 at room temperature and its thermal coefficient of dielectric constant (TCD k ) was found to be 918 ppm °C –1 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analytic Thermal Model of an Optical Fiber Based Gamma Thermometer and its Application in a University Research Reactor

This paper describes and validates, by comparison with numerical modeling results, an analytical model of thermal transport in an optical fiber based gamma thermometer (OFBGT) that is appropriate for use in university research reactors. The maximum temperature difference between the thermal mass and the outer sheath ( &#x0394;<!-- Δ --> T ) for the OFBGT design that we have considered is approximately 50 &#x2218;<!-- ° --> C , for the OFBGT in the Central Irradiation Facility of the Ohio State University Research Reactor (OSURR) with the reactor operating at full power (450 kW). The maximum value of &#x0394;<!-- Δ --> T that is predicted by the analytic model for the OFBGT design is smaller by approximately 1.1 °C than the value of &#x0394;<!-- Δ --> T which is predicted by the numerical model, for the same OFBGT design, but including all the details of the design. We have used the analytical model of thermal transport in an OFBGT to determine a normalized Modulation Transfer Function M T F &#x2032; ( k ) ) for the OFBGT. We conclude that MTF &#x2032;<!-- ' --> ( k OSU ) > 0.99 , where k OSU is the spatial frequency for the axial dependence of the reactor power distribution in the

47 OTHER INSTRUMENTATION↗
NASA NTRS1983

Improved 02/H2 Gas Mixture Sensor

Monitor of mixture concentrations uses catalyzed and uncatalyzed temperature probe. Sensor includes Pt-catalyzed temperature probe mounted in line with similar uncatalyzed temperature probe. Use of common temperature probes and standard, flareless, high-pressure tubefittings resulted in design conductive to installation in almost any system. Suitable for use in regenerative fuel cells, life-support systems, and other closed systems.

Moulthrop, L. C.↗
NASA NTRS2015

Comparison of Computational Results with a Low-g, Nitrogen Slosh and Boiling Experiment

This paper compares a fluid/thermal simulation, in Fluent, with a low-g, nitrogen slosh and boiling experiment. In 2010, the French Space Agency, CNES, performed cryogenic nitrogen experiments in a low-g aircraft campaign. From one parabolic flight, a low-g interval was simulated that focuses on low-g motion of nitrogen liquid and vapor with significant condensation, evaporation, and boiling. The computational results are compared with high-speed video, pressure data, heat transfer, and temperature data from sensors on the axis of the cylindrically shaped tank. These experimental and computational results compare favorably. The initial temperature stratification is in good agreement, and the two-phase fluid motion is qualitatively captured. Temperature data is matched except that the temperature sensors are unable to capture fast temperature transients when the sensors move from wet to dry (liquid to vapor) operation. Pressure evolution is approximately captured, but condensation and evaporation rate modeling and prediction need further theoretical analysis.

Cryogenic Fluid Storage↗
DOE OSTI2021

High-Temperature Multi-Process Sensor Development and Demonstration at a Full-scale PC Combustion System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution of wall conditions in utility boilers. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of a coal-fired utility boiler in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2021

High-Temperature Multi-Process Sensor Development for a PC-Fired Unit

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, the three mMPMS were installed at a full-scale pulverized coal-fired plant, PacifiCorp’s Hunter 3. The systems were demonstrated over 20,000 hours at the plant during regular operation. Also, the sensor data was fed to the plant’s advanced process control system to evaluate the corrosion control by the operation changes and utilized to understand the impacts of load cycling with different ramping up and down speeds. At the end of the project, the systems were converted to the permanent installation at the power plant to be used with the advanced process control system installed at the plant.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2021

High-Temperature Multi-Process Sensor Development and Demonstration at Coalfired Power Plants

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, the three mMPMS were installed at a full-scale pulverized coal-fired plant, PacifiCorp’s Hunter 3. The systems were demonstrated over 20,000 hours at the plant during regular operation. Also, the sensor data was fed to the plant’s advanced process control system to evaluate the corrosion control by the operation changes and utilized to understand the impacts of load cycling with different ramping up and down speeds. At the end of the project, the systems were converted to the permanent installation at the power plant to be used with the advanced process control system installed at the plant.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2021

High-Temperature Multi-Process Sensor Development and Demonstration at a Full-scale PC Combustion System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, the three mMPMS were installed at a full-scale pulverized coal-fired plant, PacifiCorp’s Hunter 3. The systems were demonstrated over 20,000 hours at the plant during regular operation. Also, the sensor data was fed to the plant’s advanced process control system to evaluate the corrosion control by the operation changes and utilized to understand the impacts of load cycling with different ramping up and down speeds. At the end of the project, the systems were converted to the permanent installation at the power plant to be used with the advanced process control system installed at the plant.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2014

A diamond-based scanning probe spin sensor operating at low temperature in ultra-high vacuum

We present the design and performance of an ultra-high vacuum (UHV) low temperature scanning probe microscope employing the nitrogen-vacancy color center in diamond as an ultrasensitive magnetic field sensor. Using this center as an atomic-size scanning probe has enabled imaging of nanoscale magnetic fields and single spins under ambient conditions. In this article we describe an experimental setup to operate this sensor in a cryogenic UHV environment. This will extend the applicability to a variety of molecular systems due to the enhanced target spin lifetimes at low temperature and the controlled sample preparation under UHV conditions. The instrument combines a tuning-fork based atomic force microscope (AFM) with a high numeric aperture confocal microscope and the facilities for application of radio-frequency (RF) fields for spin manipulation. We verify a sample temperature of <50 K even for strong laser and RF excitation and demonstrate magnetic resonance imaging with a magnetic AFM tip.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Europa Clipper Magnetometer Thermal Design Evolution, Validation, and Verification

Europa Clipper Spacecraft is exposed to a high radiation environment and is limited with power. This makes the thermal design of Europa Clipper magnetometer more challenging. The design is required to be highly insulated and at the same time magnetically clean. This paper describes the thermal design evolution of Europa Clipper Magnetometer. A thermal vacuum test is conducted in Europa Clipper orbit’s relevant environment to characterize the requirements and estimate the power consumption. A flight-like engineering model magnetometer from the University of California at Los Angeles (UCLA) is used for this test. Magnetically clean Cernox temperature measurement sensors with the accuracy of ±0.1ºC are used to measure the temperature value inside the sensor head and across the main frame interfaces. This level of accuracy in temperature measurement is required to capture the temperature gradient across the sensor head in a relevant environment which impacts the magnetometer measurement accuracy. Test data is used to correlate the thermal model and characterize the heat leak across the interfaces. Validated thermal model is used as a verification tool for power consumption and thermal requirements.

Caron, Ryan↗
NASA NTRS2003

A Dry-Etch Process for Low Temperature Superconducting Transition Edge Sensors for Far Infrared Bolometer Arrays

The next generation of ultra-low power bolometer arrays, with applications in far infrared imaging, spectroscopy and polarimetry, utilizes a superconducting bilayer as the sensing element to enable SQUID multiplexed readout. Superconducting transition edge sensors (TES s) are being produced with dual metal systems of superconductinghormal bilayers. The transition temperature (Tc) is tuned by altering the relative thickness of the superconductor with respect to the normal layer. We are currently investigating MoAu and MoCu bilayers. We have developed a dry-etching process for MoAu TES s with integrated molybdenum leads, and are working on adapting the process to MoCu. Dry etching has the advantage over wet etching in the MoAu system in that one can achieve a high degree of selectivity, greater than 10, using argon ME, or argon ion milling, for patterning gold on molybdenum. Molybdenum leads are subsequently patterned using fluorine plasma.. The dry-etch technique results in a smooth, featureless TES with sharp sidewalls, no undercutting of the Mo beneath the normal metal, and Mo leads with high critical current. The effects of individual processing parameters on the characteristics of the transition will be reported.

Allen, Christine A.↗
DOE OSTI2023

Testing of fiber optic based sensors for advanced reactors in the Texas A&M University TRIGA reactor

An Optical Fiber Based Gamma Thermometer has been developed and tested at the Texas A&M University reactor as well as the Ohio State Research Reactor. This sensor technology provides temperature measurement of a thermal mass undergoing gamma heating, from which the gamma flux along the length of the sensor may be calculated. The gamma flux data from an array of OFBGTs could allow the determination of local power density within a nuclear reactor core in three dimensions. The design of the sensor makes use of optical fiber as a truly distributed temperature sensor with a spatial resolution less than 1mm and temperature accuracy of ±1°C. The testing program showed that the system provided the expected temperature data for each location. Overall, this sensor technology shows promise for current Light Water Reactors as well as advanced nuclear reactors by providing an unparalleled level of precision in reactor power measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2020

Psyche Magnetometer Engineering Model Test and Thermal Model Correlation to Validate Operational Thermal Requirement

Psyche Fluxgate Magnetometer candidate fabricated by UCLA has a critical temperature gradient requirement inside the magnetometer sensor head. Since the temperature gradient requirement is a driving factor for the magnetometer operation and science data collection at 16 Psyche, it is critical to validate and verify this requirement via modeling and test. In this work, a thermal vacuum test was completed for Psyche flight-like magnetometer engineering model. Flight-like environments were simulated for a hot operational case (after launch), a cold survival case (cruise), and two cold operational cases to characterize thermal performance of the instrument. An additional, non-flight, steady-state test case was completed to better correlate the magnetometer thermal model. During the test, sensitive Cernox temperature sensors with accuracy of ±0.1°C were used to precisely characterize the temperature gradient and correlate the model to the best accuracy. Collected test data indicated power consumption of 28% lower than predicted. The temperature gradient measured met the expected value and the requirement. Test data indicated the magnetometer also met the AFTs in relevant hot and cold environments. Test Results were used to correlate the thermal model. The correlated thermal model will be integrated to the spacecraft thermal model to predict magnetometer thermal performance while collecting science data in Psyche orbits.

Caron, Ryan↗
DOE OSTI2018

Thermal effects of an ICL-based mid-infrared CH 4 sensor within a wide atmospheric temperature range

Here, thermal effects of an interband cascade laser (ICL) based mid-infrared methane (CH 4 ) sensor that uses long-path absorption spectroscopy were studied. The sensor performance in the laboratory at a constant temperature of ~ 25°C was measured for 5 hours and its Allan deviation was ~ 2 ppbv with a 1 s averaging time. A LabVIEW-based simulation program was developed to study thermal effects on infrared absorption and a temperature compensation technique was developed to control such effects. An environmental test chamber was employed to investigate thermal effects that occur in the sensor system with variation of the test chamber temperature between 10 and 30°C. The thermal response of the sensor in a laboratory setting was observed using a 2.1 ppm CH 4 standard gas sample. indoor/outdoor CH 4 measurements were conducted to evaluate the sensor performance within a wide atmospheric temperature range.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2024

Sensor Fault Detection in Smart Extraterrestrial Habitats Using Unsupervised Learning

Various types of sensors are needed to monitor the health state of smart deep-space habitats. However, measured data can be affected by sensor faults, which influence the health management system and consequently the decision-making. In this paper, an unsupervised learning approach based on convolutional autoencoders (CAEs) is developed to detect anomalies in temperature and pressure sensors. The proposed method is systematically investigated using a habitat simulator (HabSim). Several illustrative examples are demonstrated in the nominal and hazardous states of the habitat, including micrometeorite impact and fire scenarios. The performance of the proposed method using CAEs is compared with that of existing methods using auto-associative neural networks (AANNs) and variational autoencoders. This comparison is based on typical evaluation metrics, including precision, recall, F1 score, training time, and testing time. The effect of temperature–pressure coupling on the detection performance of CAEs and AANNs is explored by training different data-driven models, including one with temperature sensors, one with pressure sensors, and one with both temperature and pressure sensors. The effect of the number of faulty sensors on the performance of CAEs is studied, as with an increase in the number of faulty sensors, redundant information among the sensors is reduced. The capability of CAEs to change the number of sensors without redesigning the network architecture and retraining the neural network is investigated and demonstrated. The capabilities and limitations of the proposed solution are discussed.

Zixin Wang↗