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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Update on Earth Skin Temperature Monitoring From 16 Years of IASI Satellite Observations

Surface parameters such as emissivity and skin temperature have been retrieved from IASI measurements of last 16 years. Monthly and spatially gridded surface skin temperature is produced to show the phenomena of its natural variability, which is also reflected in the surface emissivity and/or soil moisture content derived from the same time series of measurements. The anomalies of surface skin temperature are used to estimate its trend. The IASI global surface skin temperature trend is comparable with the NASA GISTEMP5 global surface air temperature trend. The trend of IASI global surface skin temperature reports that an approximate 0.027 K/yr. increase has evolved during 2007–2023. Attention has been given to the arctic region where an average warming rate is near 3 times higher than the global average. In some arctic regions, the rapid warming rate has reached 0.2-0.3 K/yr. which is about 10 times higher than the global average. Geophysical distribution of the surface temperature trend in the arctic region is emphasized and reported.

Global warming↗
NASA NTRS1988

Supersonic combustion performance of hydrogen/hydrocarbon mixtures as determined by a nonintrusive temperature monitor

A simple and reliable OH absorption technique was developed and applied to measure path integrated temperature and OH number density in scramjet combustor hardware. The first series of measurements was made in premixed combustion products at the exit of a Mach 2 nozzle mounted on a hydrogen fueled vitiated heater. The second series of tests was conducted during supersonic combustion evaluation of hydrogen/hydrocarbon fuel mixtures. These measurements were made near the exit of a 48-inch long diverging supersonic combustor. The OH number density measurements indicated that both the nozzle and the combustor flow were not in equilibrium.

Northam, G. Burton↗
NASA NTRS2011

High Temperature Monitoring the Height of Condensed Water in Steam Pipes

An in-service health monitoring system is needed for steam pipes to track through their wall the condensation of water. The system is required to measure the height of the condensed water inside the pipe while operating at temperatures that are as high as 250 deg. C. The system needs to be able to make real time measurements while accounting for the effects of cavitation and wavy water surface. For this purpose, ultrasonic wave in pulse-echo configuration was used and reflected signals were acquired and auto-correlated to remove noise from the data and determine the water height. Transmitting and receiving the waves is done by piezoelectric transducers having Curie temperature that is significantly higher than 250 deg. C. Measurements were made at temperatures as high as 250 deg. C and have shown the feasibility of the test method. This manuscript reports the results of this feasibility study.

fluid height monitoring↗
DOE OSTI2024

Distributed Magnetic Field and Temperature Monitoring for Superconducting Radio Frequency Cavities

The overall objective of the proposed Phase I program was to design, construct and demonstrate a fiber optic sensing system capable of providing temperature and magnetic field measurements with an enhanced spatial resolution that can be implemented over a large surface area (cryomodules) to survey superconducting radio frequency cavities and magnets. A magnetic field sensor capable of detecting fluxes on the order of 1 μT is required to detect the distribution of trapped flux on the cavity surface. A unique distributed magnetic field sensor was successfully designed and constructed to demonstrate the detection of magnetic fluxes less than 500 nT. The sensor leveraged the ultra-high sensitivity of Sentek’s picoDAS to measure the magnetostriction induced vibrations in a commercially available Metglas 2605 SC ribbon that was in physical contact with sensing fiber. Static magnetic fields were detected by applying an alternating current a copper wire proximate to the Metglas 2605SC ribbon to create an AC bias magnetic field. In an alternative approach, an AC bias magnetic field was applied to a special magnetic field sensing fiber with Metglas 2605SC cladding successfully detect a magnetic field flux of a 3 μT. Exhaustive testing was performed to characterize the dependency of sensor response on the direction of the applied magnetic field. Although the special sensing fiber based magnetic field sensor did not exhibit an observable dependence on the direction of the magnetic field, the Metglas 2605SC ribbon sensor exhibited a clear directional dependence. A wide variety of polymer materials were evaluated to enhance the temperature response of an FBG based sensor at cryogenic temperatures. The processing and performance challenges provided the motivation to develop a new simple cryogenic temperature sensor that uses a commercially available fiber optic splice protector. The EVA hot melt tube that becomes adhered to the optical fiber and the polyolefin outer tube that shrinks upon heating in the fusion splicer heater provide the high thermal expansion coefficient necessary to impart a significant strain on the FBG when exposed to cryogenic temperatures. The temperature sensitivity (Δ𝜆𝐵𝑟𝑎𝑔𝑔~ 62 𝑝𝑝𝑚/℃) of the FBG-based sensor was on par with the best reported to date. The simple design, use of readily available cost-effective materials, and well-established processing techniques lends this approach to the creation of hundreds to thousands of temperature sensors on one single optical fiber length. The inherently small form factor also allows for co-location with the distributed magnetic field sensor. In preparation for field testing of the prototype sensing system at the Jefferson Labs in potential Phase II program, several different cable designs were evaluated to package the sensors. The preliminary successful demonstration of fully functional sensing cables provides the foundation for subsequent development efforts to advance the Technology Readiness Level of the technology. The technical feasibility of the proposed approach was successfully demonstrated in this Phase I effort.

43 PARTICLE ACCELERATORS↗
NASA NTRS1980

Satellite temperature monitoring and prediction system

The paper describes the Florida Satellite Freeze Forecast System (SFFS) in its current state. All data collection options have been demonstrated, and data collected over a three year period have been stored for future analysis. Presently, specific minimum temperature forecasts are issued routinely from November through March. The procedures for issuing these forecast are discussed. The automated data acquisition and processing system is described, and the physical and statistical models employed are examined.

Barnett, U. R.↗
NASA NTRS2024

Kankakee River Water Resources: Monitoring Temperature and Vegetation to Detect River Flow Impediments at Energy Intake Structures

The goal of this tutorial is to provide a comprehensive and accessible guide for detecting aquatic vegetation within the Kankakee River using Earth Observation data as well as pairing these observations with environmental trends monitoring. By offering step-by-step instructions and insights into the latest remote sensing technologies, this tutorial aims to equip readers with the knowledge and tools necessary to identify and track aquatic vegetation within a river extent of their choice.

Marisa Smedsrud↗
NASA NTRS1996

Precision Lower Stratospheric Temperature Monitoring with the MSU: Technique, Validation, and Results, 1979-1991

Microwave Sounding Unit channel 4 data from the TIROS-N (Television and Infrared Operational Satellite)-N series of NOAA (National Oceanic and Atmospheric Administration) satellites are intercalibrated to provide a continuous global record of deep-layer averaged lower stratospheric temperatures during 1979-1991. A 13-year record of temperature anomalies is time averaged into pentads and months on a 2.5 deg. grid. The monthly gridpoint anomalies are validated with ten years of radiosonde data during 1979-88. The calibration stability of each satellite's measurements is evaluated during satellite overlap periods, the longest of which reveal no measurable instrumental drift at the level of 0.01 C yr (exp -1). Intercomparisons between NOAA-6 and NOAA- 7 anomalies indicate monthly gridpoint precision of 0.05 C in the tropics to around 0.10 C in the extratropics, and signal-to-noise ratios precision and stability statistics are much better than have been previously reported by other investigators for MSU channel 4. Pentad precision is about 0.10 C in the tropics to around 0.25 C at high latitudes and signal-to- noise ratios generally over 250 in the tropics and high latitudes, but 100-200 in the middle latitudes. Radiosonde comparisons to the monthly gridpoint anomalies have correlations ranging from 0.90 in the tropics (where the interannual variability is smallest) to as high as 0.99 at high-latitude stations. The corresponding standard error of estimate is generally around 0.3 C. A significant difference in decadal trends is found between the satellite and radiosonde systems, with a step change of 0.21 C (sondes cooler) compared to the satellite measurements. Investigations of the possible sources of the discrepancy lead us to suspect that the gradual transition from on-site calibration of sondes with thermometers to factory calibration of sondes around 1982 might have caused a change in the calibration, although this conclusion must be viewed as tentative. The largest globally averaged temperature variations during 1979-91 occur after the El Chichon (1982) and Pinatubo (1991) volcanic eruptions. These warm events are superimposed upon a net downward trend in temperatures during the period. This cooling trend has more of a step function than linear character, with the step occurring during the El Chichon warm event. It is strongest in polar regions and the Northern Hemisphere middle latitudes. These characteristics are qualitatively consistent with radiative adjustments expected to occur with observed ozone depletions.

Spencer, Roy W.↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗
NASA NTRS2023

Kankakee Water Resources: Monitoring Temperature and Vegetation to Detect River Flow Impediments at Energy Intake Structures

In recent years, unpredictable grassing events have occurred at the Dresden Generating Station, located on the Kankakee River in northern Illinois. Grassing events are characterized by large mats of aquatic vegetation that accumulate downstream, resulting in the clogging of water intake structures and leading to major disruptions in power generation. Currently, employees at the Dresden Generating Station are responsible for reactively responding to each grassing event individually. This project, in partnership with Constellation Nuclear and the United States Geological Survey (USGS), assessed the feasibility of using Earth observations (Landsat 9 OLI-2, Landsat 8 OLI, Sentinel-2 MSI, DOVE PlanetScope, WorldView-3, and GPM IMERG) to detect floating aquatic vegetation within the Kankakee River and identify predictive factors that trigger grassing events, as doing so will provide the Dresden Generating Station the ability to anticipate future grassing events and enhance general hydrologic modeling efforts held by the USGS. The results of this study illustrated that, while aquatic vegetation can be detected by satellites with up to moderate spatial resolution (30 m), temporal resolution is a major limiting factor for tracking movements in floating aquatic vegetation and identifying predictive measures for these events. In addition, correlation results suggest a possible negative relationship between grassing events and river discharge (-0.875 correlation coefficient). In the future, pairing these results with ground control surveys and sensors with higher temporal capabilities would allow our project partners to predict and proactively address future grassing events, ensuring the reliable operation of the Dresden Generating Station.

Marisa Smedsrud↗
DOE OSTI2024

Highly cascaded first-order fiber Bragg gratings in highly multimode optical fibers for distributed temperature sensing under harsh environment conditions

This study presents a pioneering technique for fabricating highly cascaded first-order fiber Bragg gratings (FBGs) using a femtosecond laser-assisted point-by-point inscription method in highly multimode optical fibers, specifically Sapphire crystalline fiber, and pure silica coreless fiber. Notably, it marks the first successful demonstration of a distributed array comprising 10 FBGs within highly multimode fibers. This achievement is facilitated by a high-power laser technique that yields larger reflectors characterized by a Gaussian intensity profile. These first-order FBGs offer various advantages, including enhanced reflectivity, reduced fabrication time, and simplified spectral characteristics, enhancing their accessibility for interpretation when contrasted with higher-order FBGs. In addition to that it encompasses a comprehensive analysis of the robustness and efficacy of these FBGs, with particular emphasis on their ability to endure extreme temperatures. These FBGs demonstrate an advantageous capability for localized multi-point temperature monitoring, reaching temperatures up to 1500°C with sapphire crystalline fiber and 1100°C with pure silica coreless fiber. This resilience makes them suitable for deployment in harsh environmental conditions. This innovative approach substantially broadens the potential applications of highly multimode optical fibers, particularly in the arena of sensing and communication, where challenges related to thermal gradients and harsh environments prevail. Furthermore, these groundbreaking first-order FBGs signify a substantial advancement in the realm of distributed temperature sensing, offering supreme capabilities for temperature monitoring and signal stability. As such, our work holds the promise of a substantial impact on industries and applications that demand unwavering reliability under extreme conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Development of copper thiolate organometallic compound as thermal sensitive coating for energy storage system safety

Safety and reliability are primary concerns for the deployment of lithium-ion batteries, especially in electric vehicles (EV) and larger-scale energy storage systems (ESS). Current technology in battery management systems (BMS) includes cell voltage monitoring and positioning temperature sensors in selected locations. For a system with hundreds to thousands of individual batteries, single-point temperature monitoring is inadequate to detect hot spots and cell overheating, which could lead to thermal runaway. Here, we have developed a temperature-sensitive copper-thiol compound that can be directly coated onto battery pouch foils to enable early detection of thermal runaway. Upon reaching specific temperatures, this compound releases a sulfur-containing detectable gas, which can be identified using chemically specific gas sensors to trigger an early warning signal. Such a signal propagate through air offers broad signal coverage and enables a more comprehensive approach to large-area temperature monitoring. The Cu-ethanethiol coating is designed to release volatile gases when the substrate surface temperature exceeds 70 °C, with continuous outgassing as the temperature increases. The compound is composed of Cu, S, Cl, hydrocarbons and trace amounts of oxygen. Upon heating, the oxidation state of Cu(I) transitions to Cu (II), accompanied by gas release. Thermogravimetric analysis coupled with mass spectrometry correlated well with the onset of gas release temperature and emission of sulfur-containing volatile gases. Additionally, an acrylic overcoat is applied to enhance the adhesion of the thermally sensitive compound film to the battery pouch foil. This coating is expected to offer an additional safety layer for ESS, alerting possible thermal runaway events before a failure occurs, thereby allowing sufficient time to implement a mitigation plan.

Early warning systems↗
NASA NTRS2011

Analyzing the Effects of Climate Change on Sea Surface Temperature in Monitoring Coral Reef Health in the Florida Keys Using Sea Surface Temperature Data

This presentation discusses use of 4 kilometer satellite-based sea surface temperature (SST) data to monitor and assess coral reef areas of the Florida Keys. There are growing concerns about the impacts of climate change on coral reef systems throughout the world. Satellite remote sensing technology is being used for monitoring coral reef areas with the goal of understanding the climatic and oceanic changes that can lead to coral bleaching events. Elevated SST is a well-documented cause of coral bleaching events. Some coral monitoring studies have used 50 km data from the Advanced Very High Resolution Radiometer (AVHRR) to study the relationships of sea surface temperature anomalies to bleaching events. In partnership with NOAA's Office of National Marine Sanctuaries and the University of South Florida's Institute for Marine Remote Sensing, this project utilized higher resolution SST data from the Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR. SST data for 2000-2010 was employed to compute sea surface temperature anomalies within the study area. The 4 km SST anomaly products enabled visualization of SST levels for known coral bleaching events from 2000-2010.

Jones, Jason↗
NASA NTRS2005

Modeling contamination migration on the Chandra X-Ray Observatory

During its first 5 years of operation, the cold (-60 C) optical blocking filter of the Advanced CCD Imaging Spectrometer (ACIS), on board the Chandra X-ray Observatory, has accumulated a contaminating layer that attenuates the low-energy x rays. To assist in assessing the likelihood of successfully baking off the contaminant, members of the Chandra Team developed contamination-migration simulation software. The simulation follows deposition onto and (temperature-dependent) vaporization from surfaces comprising a geometrical model of the Observatory. A separate thermal analysis, augmented by on-board temperature monitoring, provides temperatures for each surface of the same geometrical model. This paper describes the physical basis for the simulations, the methodologies, and the predicted migration of the contaminant for various bake-out scenarios and assumptions.

O'Dell, Stephen L.↗
NASA NTRS2013

High Temperatures Health Monitoring of the Condensed Water Height in Steam Pipe Systems

Ultrasonic probes were designed, fabricated and tested for high temperature health monitoring system. The goal of this work was to develop the health monitoring system that can determine the height level of the condensed water through the pipe wall at high temperature up to 250 deg while accounting for the effects of surface perturbation. Among different ultrasonic probe designs, 2.25 MHz probes with air backed configuration provide satisfactory results in terms of sensitivity, receiving reflections from the target through the pipe wall. A series of tests were performed using the air-backed probes under irregular conditions, such as surface perturbation and surface disturbance at elevated temperature, to qualify the developed ultrasonic system. The results demonstrate that the fabricated air-backed probes combined with advanced signal processing techniques offer the capability of health monitoring of steam pipe under various operating conditions.

High Temperatures (HT)↗
DOE OSTI2025

Wireless Patch Antenna Characterization for Live Health Monitoring Using Machine Learning

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 $\frac{𝑀𝐻𝑧}{°C}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRSDate not supplied

A generalizable machine learning approach to predict land surface temperature

Monitoring of land surface and atmospheric states is highly reliant on satellite data. Traditionally, data products are generated using carefully tuned and validated algorithms for low-earth orbit (LEO) sensors. However, the emerging constellation of geostationary (GEO) sensors contributes global, high temporal resolution observations which can better capture the diurnal variability of key observables like land surface temperature (LST). Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from LEO and GEO satellites to develop a deep learning-based method for sensor-to-sensor algorithm emulation. Our model is trained on GOES-16 thermal bands to predict MODIS Terra LST and achieves a validation error <2K. Further, application of the model to unseen times of day and a second GEO sensor observing an unseen spatial domain demonstrate the generalization of the deep learning model across space, time and spectra. We anticipate that the synergies between a variety of active orbit configurations can be used to accelerate application of existing algorithms to new datasets.

Kate Marie Duffy↗