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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Submm-Wave Radiometry for Cloud/Humidity/Precipitation Sciences

Although active sensors can provide cloud profiles at good vertical resolution, clouds are often coupled with dynamics to form fast and organized structures. Lack of understanding of these organized systems leads to great challenge for numerical models. The deficiency is partly reflected, for example, in poorly modeled intraseasonal variations (e.g., MJD). Remote sensing clouds in the middle and upper troposphere has been challenging from space. Vis/IR sensors are sensitive to the topmost cloud layers whereas low-frequency MW techniques are sensitivity to liquid and precipitation at the bottom of cloud layers. The middle-level clouds, mostly in the ice phase, require a sensor that has moderate penetration and sensitivity to cloud scattering, in order to measure cloud water content. Sensors at submm wavelengths provide promising sensitivity and coverage with the spatial resolution needed to measure cloud water content floating in the upper air. In addition, submm-wave sensors are able to provide better measurements of upper-tropospheric humidity than traditional microwave instruments.

Wu, Dong L.↗
DOE OSTI2026

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1990

Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.

Schenker, Paul S.↗
DOE OSTI2023

Performance Audit Report: Automated Meteorological Monitoring Stations, Lawrence Livermore National Laboratory

The Waste and Air Quality Offices Group at the Lawrence Livermore National Laboratory operates two main meteorological monitoring sites near Livermore, California. The primary met tower (Site 200) is located in the northwest corner of the lab and consists of a fifty-two (52) meter tower with vertical wind speed sensors, horizontal wind speed and direction sensors and air temperature sensors at fifty-two (52) meters, twenty-three (23) meters and ten (10) meters. In addition, there is a temperature and humidity probe at ten (10) meters. At two (2) meters there are upward and downward facing solar and infrared radiation sensors, an air temperature sensor, barometric pressure sensor and a temperature and relative humidity probe. At ground level there is a tipping bucket rain gauge located to the southwest of the tower. The datalogger, communication peripherals and the barometric pressure sensor are housed in a small building near the tower. The Site 300 met site is located approximately 10 miles east of Livermore within the boundary of the LLNL blast test site. This site also consists of a 52-meter tower which is configured the same as the 52-meter tower at Site 200. There is also a building at this site that houses the datalogger, communication peripherals and the barometric pressure sensor. At both Site 200 and Site 300, data are collected by Ethernet with telephone modem collection as a backup. The data collection interval for both sites is fifteen (15) minutes via workstations running Loggernet software located at the main lab facility. The audits of the Lawrence Livermore National Laboratory’s two automated meteorological stations located near Livermore, California were performed on October 24 & 25, 2023. These audits were performed under the guidelines of the Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV, Version 2 and the On-Site Meteorological Program Guidance for Regulatory Modeling Applications, U.S. EPA.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Applications of inertial-sensor high-inheritance instruments to DSN precision antenna pointing

Laboratory test results of the initialization and tracking performance of an existing inertial-sensor-based instrument are given. The instrument, although not primarily designed for precision antenna pointing applications, demonstrated an on-average 10-hour tracking error of several millidegrees. The system-level instrument performance is shown by analysis to be sensor limited. Simulated instrument improvements show a tracking error of less than 1 mdeg, which would provide acceptable performance, i.e., low pointing loss, for the Deep Space Network 70-m antenna subnetwork, operating at Ka-band (1-cm wavelength).

Goddard, R. E.↗
NASA NTRS2012

Conceptual Design Standards for eXternal Visibility System (XVS) Sensor and Display Resolution

NASA is investigating eXternal Visibility Systems (XVS) concepts which are a combination of sensor and display technologies designed to achieve an equivalent level of safety and performance to that provided by forward-facing windows in today s subsonic aircraft. This report provides the background for conceptual XVS design standards for display and sensor resolution. XVS resolution requirements were derived from the basis of equivalent performance. Three measures were investigated: a) human vision performance; b) see-and-avoid performance and safety; and c) see-to-follow performance. From these three factors, a minimum but perhaps not sufficient resolution requirement of 60 pixels per degree was shown for human vision equivalence. However, see-and-avoid and see-to-follow performance requirements are nearly double. This report also reviewed historical XVS testing.

Bailey, Randall E.↗
NASA NTRSDate not supplied

Qualification of A Transition Edge Sensor Based Anti-Coincidence Detector for A Probe Class Mission

The Line Emission Mapper (or LEM) is an X-ray probe class mission aimed to study the physics of galaxy formation, with a large field-of-view, high-resolution transition-edge sensor (TES) microcalorimeter. Because of the diffuse and faint nature of LEM’s targets, a high-fidelity anticoincidence detector (anti-co) is essential to reduce instrument background below the level of sky background. Lying directly behind the LEM sensor, the anti-co will detect ~3 counts per second per square centimeter from background galactic cosmic rays and the secondary particles they induce to detect and flag any events that could be confused with a science photon in the 0.3-2 keV signal band of LEM. Our design spans an active region 4-cm in diameter. It consists of 12 quasiparticle-trap-assisted electrothermal-feedback (QET) channels, each with 100 parallel TESes with common bias lines. The TES is a narrow strip of Mo/Au bilayer. We present fabrication processes that maintain the transition temperature (T c ) in Mo/Au bilayer structures across the active region. We further present a new design based on a a-Si/W TES layer that has previously achieved reasonable uniformity in lab testing.

x-ray↗
DOE OSTI2020

Apparatus and method for measuring level

A vessel with a cavity for measuring level is disclosed. The vessel includes a differential pressure sensor having a first port and a second port, a reference tube that connects the first port of the differential pressure sensor to a bottom portion of the cavity, and an impulse tube that connects the second port of the differential pressure sensor to an impulse tube ending. At least a portion of the impulse tube extends through the cavity and ends at a fluid inlet. The fluid inlet is located at a level above the reference tube.

42 ENGINEERING↗
NASA NTRS2011

High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence

A new concept has been developed for a high-temperature luminescence-based optical thermometer that both shows the desired temperature sensitivity in the upper temperature range of present state-of-the-art luminescence thermometers (above 1,300 C), while maintaining substantial stronger luminescence signal intensity that will allow these optical thermometers to operate in the presence of the high thermal background radiation typical of industrial applications. This objective is attained by using a Cr-doped GdAlO3 (Cr:GdAlO3) sensor with an orthorhombic perovskite structure, resulting in broadband luminescence that remains strong at high temperature due to the favorable electron energy level spacing of Cr:GdAlO3. The Cr:GdAlO3 temperature (and pressure) sensor can be incorporated into, or applied onto, a component s surface when a non-contact surface temperature measurement is desired, or alternatively, the temperature sensor can be attached to the end of a fiber-optic probe that can then be positioned at the location where the temperature measurement is desired. In the case of the fiber-optic probe, both the pulsed excitation and the luminescence emission travel through the fiber-optic light guide. In either case, a pulsed light source provides excitation of the luminescence, and the broadband luminescence emission is collected. Real-time temperature measurements are obtain ed using a least-squares fitting algorithm that determines the luminescence decay time, which has a known temperature dependence established by calibration. Due to the broad absorption and emission bands for Cr:GdAlO3, there is considerable flexibility in the choice of excitation wavelength and emission wavelength detection bands. The strategic choice of the GdAlO3 host is based on its high crystal field, phase stability, and distorted symmetry at the Cr3+ occupation sites. The use of the broadband emission for temperature sensing at high temperatures is a key feature of the invention and is novel since broadband luminescence emission normally shows severe thermal quenching. The tightly bound AlO6 octahedra in GdAlO3 results in a larger energy barrier to nonradiative decays than in other materials and therefore makes using broadband emission for temperature sensing possible at high temperatures. This approach results in a substantial increase in temperature capability. For example, the most commonly used Cr-doped crystal used for luminescence-based temperature measurements, ruby, has only been demonstrated up to 600 C, whereas the Cr:GdAlO3 optical thermometer under development has already been shown to exhibit useful luminescence up to 1,300 C. Because GdAlO3 is non-reactive and is stable in harsh, high-temperature environments, sensors composed of Cr:GdAlO3 will be very well suited for remote high-temperature measurements in engine or industrial environments where its intense high-temperature luminescence will stand out above significant thermal radiation background levels.

Eldridge, Jeffrey↗
NASA NTRS2017

Precise starshade stationkeeping and pointing with a Zernike wavefront sensor

Starshades, large occulters positioned tens of thousands of kilometers in front of space telescopes, o er one of the few paths to imaging and characterizing Earth-like extrasolar planets. However, for the starshade to generate a su ciently dark shadow on the telescope, the two must be coaligned to just 1 meter laterally, even at these large separations. The principal challenge to achieving this level of control is in determining the position of the starshade with respect to the space telescope. In this paper, we present numerical simulations and laboratory results demonstrating that a Zernike wavefront sensor coupled to a WFIRST-type telescope is able to deliver the stationkeeping precision required, by measuring light outside of the science wavelengths. The sensor can determine the starshade lateral position to centimeter level in seconds of open shutter time for stars brighter than eighth magnitude, with a capture range of 10 meters. We discuss the potential for fast (ms) tip/tilt pointing control at the milli-arcsecond level by illuminating the sensor with a laser mounted on the starshade. Finally, we present early laboratory results.

Shaklan, Stuart↗
DOE OSTI2021

All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost, low-power gas detection

In this work, we report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using additive manufacturing techniques. The silver interdigitated electrode (IDE) arrays and conducting polymer films are printed onto PI using a direct-write technology of aerosol-jet printing. Morphological characteristics are examined by scanning electron microscopy and energy-dispersive X-ray analysis which reveal homogeneously printed PANI film on the IDE platform. The gas sensing performance is evaluated in the analytical early leak detection range of 5–1000 ppm NH3 in air as a function of both thermal (23 °C, 50 °C, 80 °C) and relative humidity (RH = 0%, 30%, 50%) exposures. The sensor exhibits sensitivity down to 5 ppm NH3 with a sub-ppm detection limit and good repeatability. We observe rapid NH3 detection at 0% RH with very extended times for equilibration and recovery. However, at both 30 and 50% RH, the room temperature response and recovery times are reduced to only about 1 min and 5 min, respectively. Experiments also reveal good sensitivity toward the analyte even at higher operating temperatures. Present results merit the practical application of aerosol-jet-printed, low-power sensors for industrial applications where low-level hazardous gas detection is essential.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Integrating Carbon Nanomaterials with Metals for Bio-sensing Applications

Age structure in most developed countries is changing fast as the average lifespan is increasing significantly, calling for solutions to provide improved treatments for age-related neurological diseases and disorders. In order to address these problems, a reliable way of recording information about neurotransmitters from in vitro and in vivo applications is needed to better understand neurological diseases and disorders as well as currently used treatments. Likewise, recent developments in medicine, especially with the opioid crisis, are demanding a swift move to personalized medicine to administer patient needs rather than population-wide averages. In order to enable the so-called personalized medicine, it is necessary to be able to do measurements in vivo and in real time. These actions require sensitive and selective detection of different analytes from very demanding environments. Current state-of-the-art materials are unable to provide sensitive and selective detection of neurotransmitters as well as the required time resolution needed for drug molecules at a reasonable cost. To meet these challenges, we have utilized different metals to grow carbon nanomaterials and applied them for sensing applications showing that there are clear differences in their electrochemical properties based on the selected catalyst metal. Additionally, we have combined atomistic simulations to support optimizing materials for experiments and to gain further understanding of the atomistic level reactions between different analytes and the sensor surface. With carbon nanostructures grown from Ni and Al + Co + Fe hybrid, we can detect dopamine, ascorbic acid, and uric acid simultaneously. On the other hand, nanostructures grown from platinum provide a feasible platform for detection of H 2 O 2 making them suitable candidates for enzymatic biosensors for detection of glutamate, for example. Tetrahedral amorphous carbon electrodes have an ability to detect morphine, paracetamol, tramadol, and O-desmethyltramadol. With carbon nanomaterial-based sensors, it is possible to reach metal-like properties in sensing applications using only a fraction of the metal as seed for the material growth. We have also seen that by using nanodiamonds as growth catalyst for carbon nanofibers, it is not possible to detect dopamine and ascorbic acid simultaneously, although the morphology of the resulting nanofibers is similar to the ones grown using Ni. This further indicates the importance of the metal selection for specific applications. However, Ni as a continuous layer or as separate islands does not provide adequate performance. Thus, it appears that metal nanoparticles combined with fiber-like morphology are needed for optimized sensor performance for neurotransmitter detection. This opens up a new research approach of application-specific nanomaterials, where carefully selected metals are integrated with carbon nanomaterials to match the needs of the sensing application in question.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Advances in solar forecasting: Computer vision with deep learning

Renewable energy forecasting is crucial for integrating variable energy sources into the grid. It allows power systems to address the intermittency of the energy supply at different spatiotemporal scales. To anticipate the future impact of cloud displacements on the energy generated by solar facilities, conventional modeling methods rely on numerical weather prediction or physical models, which have difficulties in assimilating cloud information and learning systematic biases. Augmenting computer vision with machine learning overcomes some of these limitations by fusing real-time cloud cover observations with surface measurements acquired from multiple sources. This Review summarizes recent progress in solar forecasting from multisensor Earth observations with a focus on deep learning, which provides the necessary theoretical framework to develop architectures capable of extracting relevant information from data generated by ground-level sky cameras, satellites, weather stations, and sensor networks. Overall, machine learning has the potential to significantly improve the accuracy and robustness of solar energy meteorology; however, more research is necessary to realize this potential and address its limitations.

14 SOLAR ENERGY↗
DOE OSTI2019

Leaf surface temperature and sapflow raw data, 11 March 2016 - 13 June 2016, Santarem Brazil, Km67 tower

This data package contains raw, unprocessed leaf surface temperature data for five trees and sap velocity data for four trees near the Km67 flux tower in Santarem, Brazil. Data was collected over the course of three months. Datalogger output from sapflow ICT sensors was translated using ICT software and is included in the attached zip file. Raw data is in .csv and .xls formats. Leaf surface temperature sensor photos, sensor manual PDFs, and three file-level metadata excel files are also included in the attached file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification

This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Machine processing of remotely sensed data; Proceedings of the Conference, Purdue University, West Lafayette, Ind., October 16-18, 1973

Topics discussed include the management and processing of earth resources information, special-purpose processors for the machine processing of remotely sensed data, digital image registration by a mathematical programming technique, the use of remote-sensor data in land classification (in particular, the use of ERTS-1 multispectral scanning data), the use of remote-sensor data in geometrical transformations and mapping, earth resource measurement with the aid of ERTS-1 multispectral scanning data, the use of remote-sensor data in the classification of turbidity levels in coastal zones and in the identification of ecological anomalies, the problem of feature selection and the classification of objects in multispectral images, the estimation of proportions of certain categories of objects, and a number of special systems and techniques. Individual items are announced in this issue.

Source record↗
NASA NTRS1974

Meteorological data collection via ERTS-A data retransmission facilities

The author has identified the following significant results. Two meteorological data acquisition systems were built to support hydrometeorological programs related to flow forecasting. Data errors were detected in the stream level formation; these errors were caused by sensor difficulties.

Vockeroth, R. E.↗