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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Sap Velocity Data for East River Watershed Sites (2023-2025)

This dataset includes sap velocity measurements for aspen (populus tremuloides), fir (abies lasiocarpa), spruce (Engelmann spruce) and lodgepole pine (pinus contorta) trees at nine sites in the East River Watershed near Gothic, CO. This dataset was generated following a similar method as a previous dataset (Dataset. doi:10.15485/1647654) but was conducted at different sites in the area and now includes lodgepole pine. Site selection was done to explicitly improve understanding of topographic controls of tree water use. The data collection began in June 2023 and we provide data until December 2025 - though data collection is ongoing. The sap flux data were collected using ICT SFM1 sensors and are presented in both units of cm h^-1 and as kg h^-1 by multiplying the sap flux by the sapwood area of the tree. All sap flow data has been been corrected using estimates of wounding diameter, water content of wood and sap wood depth. We also provide a normalized sap velocity estimate by subtracting each measurement from that trees' annual minimum and dividing by that trees' annual maximum. This provides data for each tree and year on a 0-1 scale. This data entry contains one CSV file that includes all available sap flow data. The timestamps are provided in local time as year, day of year and hour and each measurement contains an associated latitude, longitude and site number which can be used to identify trees in a given stand. Each species is given a numeric value as: 1= populus tremuloides, 2=Engelmann spruce, 3=abies lasiocarpa and 4=pinus contorta.

abies↗
DOE OSTI2016

Advanced Sensor Arrays and Packaging

Novel sensor packaging elements were designed, fabricated, and tested in order to facilitate the transition of electrochemical mixed-potential sensors toward commercialization. Of the two designs completed, the first is currently undergoing field trials, taking direct measurements within vehicle exhaust streams, while the second is undergoing preliminary laboratory testing. The sensors’ optimal operating conditions, sensitivity to hydrogen, and long-­term baseline stability were also investigated. The sensing capabilities of lanthanum chromite (La 0.8 Sr 0.2 CrO 3 ) and indium-­doped tin oxide (ITO) working electrodes were compared, and the ITO devices were selected for pre-­commercial field trials testing at a hydrogen fuel cell vehicle fueling station in California. Previous data from that fueling station were also analyzed, and the causes of anomalous baseline drift were identified.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Integrated System for Methane Emissions Monitoring, Mapping, and Quantification

This report presents the work completed under the DOE iM4 project for the development of a methane emission monitoring system for detection, location, and quantification of methane in oil and gas industries. The task was divided into four main areas including: 1) Sensors and Input, 2) Centralized Cloud Information Center, 3) Algorithms, and 4) Testing and Validation. Task 1 focused on researching and developing an understanding of the current, or soon to be, available methane sensing technologies. Task 2 consisted of developing the architecture, selecting hardware, software and elements for the methane monitoring system. Task 3 focused on the algorithms used for the complex inverse model of going from measured methane signatures to the detection, localization, and quantification of sources that are desired. Finally, Task 4 focused on the methods of testing and validating the operation of the system. Attention was also given to the development method and cost breakdown of the system.

03 NATURAL GAS↗
NASA NTRS1976

Monitoring stratospheric ozone and aerosols using orbiting photoelectric detectors

Application of slightly modified off-the-shelf automatic celestial navigation systems ('star trackers') is considered for the purposes of monitoring variations in the optical depth of the stratospheric aerosol and ozone layers. The basic principle of the technique is to observe stars from an orbiting station as they are occulted by the stratospheric aerosol layer. Since molecular and refraction extinction are directly calculable, total extinction measurements using a dual-sensor (S4 and S20) approach allows us to directly solve for ozone and aerosol extinction and look for correlations between these two parameters. The technique appears promising for remotely monitoring aerosol and ozone optical depth in the 15-25 km region over selected locations and is independently accurate if aerosol composition and relative size distribution are invariant.

Matloff, G. L.↗
NASA NTRS1985

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture/remote Sensing

Analysis of the early thematic mapper (TM) data indicate the TM sensor and associated ground processing are performing equal to the high expectations and within advertised specifications. The overall TM system with improved resolution, together with additional and more optimumly placed spectral bands shows much promise for benefits in future analysis activities. By selecting man-made features of known dimensions (e.g., highways, airfields, buildings, and isolated water bodies), an assessment was made of the TM performance relative to the specified 30-meter (98-foot) resolution. The increase of spatial resolution of TM (30 m) over MSS (80 M) appears to be significant not only in resolving spectrally distinct classes that were previously undefinable but also in distinguishing within-field variability. An Important result of the early TM evaluation and pre-TM analyses was the development of an integrated system to receive LANDSAT-4 TM (as well as MSS) data and analyze the data via various approaches.

Bizzell, R. M.↗
NASA NTRS1990

Advanced Transport Operating Systems Program

NASA-Langley's Advanced Transport Operating Systems Program employs a heavily instrumented, B 737-100 as its Transport Systems Research Vehicle (TRSV). The TRSV has been used during the demonstration trials of the Time Reference Scanning Beam Microwave Landing System (TRSB MLS), the '4D flight-management' concept, ATC data links, and airborne windshear sensors. The credibility obtainable from successful flight test experiments is often a critical factor in the granting of substantial commitments for commercial implementation by the FAA and industry. In the case of the TRSB MLS, flight test demonstrations were decisive to its selection as the standard landing system by the ICAO.

White, John J.↗
NASA NTRS1992

Chemical sensors for space applications

The payload of the Space Station Freedom will include sensors for frequent monitoring of the water recycling process and for measuring the many biochemical parameters related to onboard experiments. This paper describes the sensor technologies and the types of transducers and selectors considered for these sensors. Particular attention is given to such aspects of monitoring of the water recycling process as the types of water use, the sources of water and their hazards, the sensor systems for monitoring, microbial monitoring, and monitoring toxic metals and organics. An approach for monitoring water recycling is suggested, which includes microbial testing with a potentiometric device (which should be in first line of tests), the use of an ion-selective electrode for inorganic ion determinations, and the use of optic fiber techniques for the determination of total organic carbon.

Bonting, Sjoerd L.↗
NASA NTRS1993

Comparison of remote sensing measurements with a two-scale polarimetric emission and scattering model for sea surfaces

Recently, it has been observed that the brightness temperatures of sea surfaces correlate with the azimuth angle of the ocean wind vector, indicating that ocean wind direction can not only be retrieved from the microwave backscatter, but also from the brightness temperature measurements. In this paper, comparison of the theoretical result calculated from a two-scale emission and scattering model with the Seasat and SSM/I model functions and aircraft measurements is presented and potential applications of microwave polarimetry are discussed. In our two-scale model, the modified reflectivities of large scale surfaces are calculated by extending the small perturbation method to the second order for small scale perturbation with anisotropic directional spectrum. It was found that the modified reflectivities derived from the second-order scattered field agree excellently well with the results obtained from a Monte Carlo simulation technique which numerically calculates the polarimetric reflectivities of one-dimensional random rough surfaces with a power-law spectrum. Without the second-order correction, the modified reflectivities of the rough surfaces are significantly over-estimated and sign errors are observed in the third and fourth Stokes parameters for thermal emissions. The surface spectrum parameters and two-scale cutoff are selected so that the calculated scattering and emission signatures agree with the reported model functions for Seasat and SSM/I. Subsequently, the polarimetric signatures of sea surfaces are illustrated to indicate the possibility of reducing the number of azimuthal looks required for spaceborne sensors in the remote sensing of ocean wind by using the polarimetric information. Furthermore, it is found that contrary to the dependence of backscattering coefficients on incidence angles, polarimetric brightness temperatures display a stronger wind direction dependence in the near nadir-looking direction than away from nadir. Finally, we discuss the potential of a single-look polarimetric radiometer for wind retrieval.

Yueh, S. H.↗
NASA NTRS1994

Semiconductor-metal graded-index composite thin films for infrared applications

Theoretical/experimental studies have been carried out on germanium:silver (Ge:Ag) graded-index composite thin films which demonstrate that graded coatings, consisting of varied concentrations of Ag with respect to the Ge film thickness, exhibit different optical properties ranging from selective infrared (IR) reflectance to broadband IR absorptance. The graded coatings have been produced by dc magnetron cosputtering of Ge and Ag and the spectral properties are found to be stable against temperature. The coatings have been applied to an infrared tunnel sensor (micro-Golay cell) to improve the device performance.

Lamb, James L.↗
NASA NTRS2001

International Space Station Increment-2 Quick Look Report

The objective of this quick look report is to disseminate the International Space Station (ISS) Increment-2 reduced gravity environment preliminary analysis in a timely manner to the microgravity scientific community. This report is a quick look at the processed acceleration data collected by the Microgravity Acceleration Measurement System (MAMS) during the period of May 3 to June 8, 2001. The report is by no means an exhaustive examination of all the relevant activities, which occurred during the time span mentioned above for two reasons. First, the time span being considered in this report is rather short since the MAMS was not active throughout the time span being considered to allow a detailed characterization. Second, as the name of the report implied, it is a quick look at the acceleration data. Consequently, a more comprehensive report, the ISS Increment-2 report, will be published following the conclusion of the Increment-2 tour of duty. NASA sponsors the MAMS and the Space Acceleration Microgravity System (SAMS) to support microgravity science experiments, which require microgravity acceleration measurements. On April 19, 2001, both the MAMS and the SAMS units were launched on STS-100 from the Kennedy Space Center for installation on the ISS. The MAMS unit was flown to the station in support of science experiments requiring quasisteady acceleration data measurements, while the SAMS unit was flown to support experiments requiring vibratory acceleration data measurement. Both acceleration systems are also used in support of the vehicle microgravity requirements verification. The ISS reduced gravity environment analysis presented in this report uses mostly the MAMS acceleration data measurements (the Increment-2 report will cover both systems). The MAMS has two sensors. The MAMS Orbital Acceleration Research Experiment Sensor Subsystem, which is a low frequency range sensor (up to 1 Hz), is used to characterize the quasi-steady environment for payloads and vehicle. The MAMS High Resolution Acceleration Package is used to characterize the ISS vibratory environment up to 100 Hz. This quick look report presents some selected quasi-steady and vibratory activities recorded by the MAMS during the ongoing ISS Increment-2 tour of duty.

Jules, Kenol↗
NASA NTRS2009

Nanotunneling Junction-based Hyperspectal Polarimetric Photodetector and Detection Method

A photodetector, detector array, and method of operation thereof in which nanojunctions are formed by crossing layers of nanowires. The crossing nanowires are separated by a few nm thick electrical barrier layer which allows tunneling. Each nanojunction is coupled to a slot antenna for efficient and frequency-selective coupling to photo signals. The nanojunctions formed at the intersection of the crossing wires defines a vertical tunneling diode that rectifies the AC signal from a coupled antenna and generates a DC signal suitable for reforming a video image. The nanojunction sensor allows multi/hyper spectral imaging of radiation within a spectral band ranging from terahertz to visible light, and including infrared (IR) radiation. This new detection approach also offers unprecedented speed, sensitivity and fidelity at room temperature.

Son, Kyung-ah↗
NASA NTRS2020

Change of Exposure Time Mid-test in High Temperature DIC Measurement

Performing digital image correlation (DIC) at extreme temperatures has been greatly challenging due to the radiation which saturates the camera sensor. At such high temperatures, the light intensity emitted from an object is occasionally so powerful that the acquired images are overwhelmingly saturated. This induces data loss, potentially ruining the test, thus requiring the user to restart the test. For this reason, selection of an appropriate camera sensitivity plays a crucial role prior to beginning the test. Exposure time is a factor contributing to camera sensitivity and it is the easiest setting to manipulate during the test since it introduces minimal errors when comparing to other factors, especially in quasi-static tests. This paper examines the influence of changing exposure time mid-test on DIC measurement uncertainty. The investigation was conducted by rigid body motion experiments at room temperature and 1600 ◦C, respectively. Thereby, some recommendations are given to help DIC users assess their images at room temperature to extrapolate the exposure at extreme temperatures along with accompanying solutions to salvage data at high temperature.

Digital Image Correlation↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities withinthe same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2001

Ground-Based Icing Condition Remote Sensing System Definition

This report documents the NASA Glenn Research Center activities to assess and down select remote sensing technologies for the purpose of developing a system capable of measuring icing condition hazards aloft. The information generated by such a remote sensing system is intended for use by the entire aviation community, including flight crews. air traffic controllers. airline dispatchers, and aviation weather forecasters. The remote sensing system must be capable of remotely measuring temperature and liquid water content (LWC), and indicating the presence of super-cooled large droplets (SLD). Technologies examined include Profiling Microwave Radiometer, Dual-Band Radar, Multi-Band Radar, Ka-Band Radar. Polarized Ka-Band Radar, and Multiple Field of View (MFOV) Lidar. The assessment of these systems took place primarily during the Mt. Washington Icing Sensors Project (MWISP) in April 1999 and the Alliance Icing Research Study (AIRS) from November 1999 to February 2000. A discussion of the various sensing technologies is included. The result of the assessment is that no one sensing technology can satisfy all of the stated project goals. Therefore a proposed system includes radiometry and Ka-band radar. A multilevel approach is proposed to allow the future selection of the fielded system based upon required capability and available funding. The most basic level system would be the least capable and least expensive. The next level would increase capability and cost, and the highest level would be the most capable and most expensive to field. The Level 1 system would consist of a Profiling Microwave Radiometer. The Level 2 system would add a Ka-Band Radar. The Level 3 system would add polarization to the Ka-Band Radar. All levels of the system would utilize hardware that is already under development by the U.S. Government. However, to meet the needs of the aviation community, all levels of the system will require further development. In addition to the proposed system, it is also recommended that NASA continue to foster the development of Multi-Band Radar and airborne microwave radiometer technologies.

Reehorst, Andrew L.↗
DOE OSTI2017

Detection and Quantification of Biologically Active Botulinum Neurotoxin Serotypes A and B Using a Förster Resonance Energy Transfer-Based Quantum Dot Nanobiosensor

Botulinum neurotoxin (BoNT) is the most potent toxin known. The ingestion of food contaminated with biologically active BoNT causes foodborne botulism, which can lead to respiratory paralysis, coma, and death after ingestion of as little as 70 mu g for a 70 kg human. Because of its lethality and challenges associated with current detection methods, there is an urgent need for highly sensitive rapid screening techniques capable of detecting biologically active BoNT. Here, we describe a Forster resonance energy transfer-based nanobiosensor that uses quantum dots (QDs) and two specific quencher-labeled peptide probes to detect and differentiate two biologically active forms of BoNT, serotypes A and B, which were responsible for 80% of human foodborne botulism cases in the U.S. from 2012 to 2015. Each peptide probe contains an enzymatic cleavage site specific to only one serotype. QDs were selected based on the spectral overlap with the quenchers. In the presence of the target BoNT serotype, the peptide probe is cleaved and the quenching of QD photoluminescence (PL) is reduced, giving a signal that is easily detected by a PL spectrophotometer. This sensor performance was evaluated with light chains of BoNT/A and BoNT/B (LcA and LcB), catalytic domains of the respective serotypes. LcA and LcB were detected in 3 h with limits of detection of 0.2 and 2 ng/mL, respectively. The specificity of the sensor was evaluated, and no cross-reactivity from nontarget serotypes was observed with 2 h of incubation. Because each serotype-specific peptide is conjugated to a QD with a unique emission wavelength, multiple biologically active BoNT serotypes could be detected in one PL spectrum. The sensor was also shown to be responsive to BoNT/A and BoNT/B holotoxins. Good performance of this sensor implies its potential application as a rapid screening method for biologically active BoNT/A and BoNT/B in the laboratory and in the field.

botulinum neurotoxin↗
DOE OSTI2022

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗
DOE OSTI2019

Sequential Learning with Active Partial Labeling for Building Metadata

Modern buildings are instrumented with thousands of sensing and control points. The ability to automatically extract the physical context of each point, e.g., the type, location, and relationship with other points, is the key to enabling building analytics at scale. However, this process is costly as it usually requires domain expertise with a deep understanding of the building system and its point naming scheme. In this study, we aim to reduce the human effort required for mapping sensors to their context, i.e., metadata mapping. We formulate the problem as a sequential labeling process and use the conditional random field to exploit the regular and dependent structures observed in the metadata. We develop a suite of active learning strategies to adaptively select the most informative subsequences in point names for human labeling, which significantly reduces the inputs from domain experts.We evaluated our approach on three different buildings and observed encouraging performance in metadata mapping from the proposed solution.

99 GENERAL AND MISCELLANEOUS↗