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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A gimbaled low noise momentum wheel

The bus actuators are the heart and at the same time the Achilles' heel of accurate spacecraft stabilization systems, because both their performance and their perturbations can have a deciding influence on the achievable pointing accuracy of the mission. The main task of the attitude actuators, which are mostly wheels, is the generation of useful torques with sufficiently high bandwidth, resolution and accuracy. This is because the bandwidth of the whole attitude control loop and its disturbance rejection capability is dependent upon these factors. These useful torques shall be provided, without - as far as possible - parasitic noise like unbalance forces and torques and harmonics. This is because such variable frequency perturbations excite structural resonances which in turn disturb the operation of sensors and scientific instruments. High accuracy spacecraft will further require bus actuators for the three linear degrees of freedom (DOF) to damp structural oscillations excited by various sources. These actuators have to cover the dynamic range of these disturbances. Another interesting feature, which is not necessarily related to low noise performance, is a gimballing capability which enables, in a certain angular range, a three axis attitude control with only one wheel. The herein presented Teldix MWX, a five degree of freedom Magnetic Bearing Momentum Wheel, incorporates all the above required features. It is ideally suited to support, as a gyroscopic actuator in the attitude control system, all High Pointing Accuracy and Vibration Sensitive space missions.

Bichler, U.↗
DOE OSTI2025

An Overview of Emerging Nuclear Sensor Technologies: Challenges, Advancements and Applications

Nuclear sensors are essential for detecting and measuring nuclear radiation in various applications, including nuclear power plants, medical imaging, and environmental monitoring. Traditional nuclear sensors have served these fields for decades, but recent advancements in emerging sensor technologies offer novel improvements in accuracy, sensitivity, and reliability. This review presents an up-to-date overview of recent progress in the advancements of nuclear sensor technologies, their diverse applications, challenges in implementation, and opportunities for future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2000

New Developments in Quaternion Estimation from Vector Observations

This paper contains a critical comparison of estimators minimizing Wahba's loss function. Some new results are presented for the QUaternion ESTimator (QUEST) and EStimators of the Optimal Quaternion (ESOQ and ESOQ2) to avoid the computational burden of sequential rotations in these algorithms. None of these methods is as robust in principle as Davenport's q method or the Singular Value Decomposition (SVD) method, which are significantly slower. Robustness is only an issue for measurements with widely differing accuracies, so the fastest estimators, the modified ESOQ and ESOQ2, are well suited to sensors that track multiple stars with comparable accuracies. More robust forms of ESOQ and ESOQ2 are developed that are intermediate in speed.

Markley, F. Landis↗
DOE OSTI2020

Microbial potentiometric sensor: A new approach to longstanding challenges

The underlying hypothesis of this study is that simple potentiometric measurements between sensing electrodes and a shared reference electrode - Microbial Potentiometric Sesnor (MPS) system - can be employed in a long-term, continuous mode of operation to resolve the spatial and temporal changes in environmental systems. To address the hypothesis, (1) a conceptual description of the MPS system and its postulated principle of operation are provided; (2) the MPS system performance is documented under controlled laboratory conditions; and (3) the capabilities of the MPS system are documented under quiescent and dynamic field condition. In a laboratory setting, the variability among different MPS signals was insignificant confirming the postulated high accuracy and reproducibility of the sensor performance. It also demonstrated statistically significant correlations with dissolved oxygen (DO) and oxidation-reduction potential (ORP) sensors, while showing capabilities of operating under anoxic and anaerobic conditions. Regardless of their locations in the model wetland system, three MPS sensors functioned without interruption and cleaning for a period >2 years, and thus demonstrating long-term durability of the MPS technology. In real batch-wastewater treatment facility, the deployed MPS system signals were able to describe the organic carbon trends and correlate with each treatment phase in a cycle. Data reproducibility and reliability exceeded the expectations better describing the carbon treatment levels than the DO and ORP sensors (p < 4.4 × 10 –162 vs phase adjusted p < 3.0 × 10 –58 ). While MPS signals correlate with specific parameters that describe the local process or environments, it is more prudent to employ both the magnitude and pattern of a composite signal like the MPS signal describe the change to reflect any shift in the local environment. Finally, when compared to a baseline pattern, this change in signal magnitude and pattern reveals important information that can be employed to tailor and optimize any condition or process which involves microorganisms.

47 OTHER INSTRUMENTATION↗
NASA NTRS1990

Land use change detection based on multi-date imagery from different satellite sensor systems

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Stow, Douglas A.↗
NASA NTRS1979

Pioneer Venus Star Sensor

The design predictions and orbital performance verification of the solid state star scanner used in the Onboard Attitude Control of the Pioneer Venus Orbiter and Multiprobe are presented. The star sensor extended the scanner use to active despin control, and it differs from previous sensors in solid state detection, redundant electronics for reliability, larger field of view, and large dynamic spin range. The star scanner hardware and design performance based on the ability to predict all noise sources, signal magnitudes, and expected detection probability are discussed. In-flight data collected to verify sensor ground calibration are tabulated and plotted in predicted accuracy curves. It is concluded that the Pioneer Venus Star Sensor has demonstrated predictable star calibration in the range of .1 magnitude uncertainties and usable star catalogs of 100 stars with very high probabilities of detection, which were much better than expected and well within the mission requirements.

Gutshall, R. L.↗
NASA NTRS2011

Uncertainty Assessment of the SeaWiFS On-Orbit Calibration

Ocean color climate data records require water-leaving radiances with 5% absolute and 1% relative accuracies as input. Because of the amplification of any sensor calibration errors by the atmospheric correction, the 1% relative accuracy requirement translates into a 0.1% long-term radiometric stability requirement for top-of-the atmosphere radiances. The rigorous on-orbit calibration program developed and implemented for SeaWiFS by the NASA Ocean Biology Processing Group (OBPG) Calibration and Validation Team (CVT) has allowed the CVT to maintain the stability of the radiometric calibration of SeaWiFS at 0.13% or better over the mission. The uncertainties in the resulting calibrated top-of-the-atmosphere (TOA) radiances can be addressed in terms of accuracy (biases in the measurements), precision (scatter in the measurements), and stability (repeatability of the measurements). The calibration biases of lunar observations relative to the USGS RObotic Lunar Observatory (ROLO) photometric model of the Moon are 2-3%. The biases from the vicarious calibration against the Marine Optical Buoy (MOBY) are 1-2%. The precision of the calibration derived from the solar calibration signal-tonoise ratios are 0.16%, from the lunar residuals are 0.13%, and from the vicarious gains are 0.10%. The long-term stability of the TOA radiances, derived from the lunar time series, is 0.13%. The stability of the vicariouslycalibrated TOA radiances, incorporating the uncertainties in the MOBY measurements and the atmospheric correction, is 0.30%. These results allow the OBPG to produce climate data records from the SeaWiFS ocean color data.

Eplee, Robert E., Jr.↗
NASA NTRS2018

The Global Precipitation Measurement (GPM) Mission's Scientific Achievements and Societal Contributions: Reviewing Four Years of Advanced Rain and Snow Observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth’s atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° x 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Applications↗
NASA NTRS2002

Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time

Satellite data form the core of the information available for estimating precipitation on a global basis. While it is possible to create such estimates solely from one sensor, researchers have increasingly moved to using combinations of sensors in an attempt to improve accuracy, coverage, and resolution. This poster updates a long-term project in which the authors are working to provide routine combined-sensor estimates of precipitation over the entire globe at relatively fine time and space intervals. The goal is to produce these globally complete precipitation estimates on a 25-km grid every 3 hours. Since late January 2002 we have been estimating precipitation for the latitude band 50 degrees N-S within about 6 hours of observation time. This work is 1 of only 2 or 3 such efforts in the world. Now we are preparing to provide similar estimates for the last 5 years. All of this work is being carried out as part of the Tropical Rainfall Measuring Mission (TRMM). Initially, TRMM was focused on providing excellent long-term averages of precipitation in tropical regions, but since its launch in November 1997 continued research has allowed the same satellite and data system to be used for addressing weather-scale problems as well.

Huffman, George J.↗
NASA NTRS1980

Coal thickness guage using RRAS techniques, parts 2 and 3

Electron magnetic resonance was investigated as a sensing technique for use in measuring the thickness of the layer of coal overlying the rock substrate. The goal is development of a thickness gauge which will be usable for control of mining machinery to maintain the coal thickness within selected bounds. A sensor must be noncontracting, have a measurement range of 6 inches or more, and an accuracy of 1/2 inch or better. The sensor should be insensitive to variations in spacing between the sensor and the surface, the response speed should be adequate to permit use on continuous mining equipment, and the device should be rugged and otherwise suited for operation under conditions of high vibration, moisture, and dust. Finally, the sensor measurement must not be adversely affected by the natural effects occurring in coal such as impurities, voids, cracks, layering, high moisture level, and other conditions that are likely to be encountered.

King, J. D.↗
NASA NTRS2010

Direct Measurement Sensor of the Boundary Shear Stress in Fluid Flow

The flow fields and boundary erosion that are associated with scour at bridge piers are very complex. Direct measurement of the boundary shear stress and boundary pressure fluctuations in experimental scour research has always been a challenge and high spatial resolution and fidelity have been almost impossible. Most researchers have applied an indirect process to determine shear stress using precise measured velocity profiles. Laser Doppler Anemometry and Particle Image Velocimetry are common techniques used to accurately measure velocity profiles. These methods are based on theoretical assumptions to estimate boundary shear stress. In addition, available turbulence models cannot very well account for the effect of bed roughness which is fundamentally important for any CFD simulation. The authors have taken on the challenge to advance the magnitude level to which direct measurements of the shear stress in water flow can be performed. This paper covered the challenges and the efforts to develop a higher accuracy and small spatial resolution sensor. Also, preliminary sensor designs and test results are presented.

Badescu, Mircea↗
NASA NTRS1966

The ring laser inertial sensor.

Ring laser inertial sensor for aerospace systems obtaining high accuracy angular resolution and mechanical simplicity

ANGULAR VELOCITY↗
NASA NTRS1988

Feasibility of using GPS measurements for OMV attitude update

This paper presents the results of a feasibility study to determine whether the measurements from GPS satellites can be used to estimate the OMV attitude to an accuracy comparable to the onboard sun sensors, i.e., better than 0.5 degree in each axis. The results documented in this paper demonstrate that OMV attitude can be estimated to an accuracy of 0.1 - 0.5 degree in each axis by processing GPS measurements in an onboard integrated, 17-state GPS/inertial navigation filter. The result is particularly significant for missions of short duration burns where accurate attitude information is needed to minimize guidance and control errors. It is shown that the GPS attitude technique described in this paper can be easily implemented in the current OMV navigation system design. Results reported in this paper are expected to support the goal of developing a fault-tolerant guidance, navigation, and control system offering an improved total navigation performance for the OMV.

Upadhyay, Triveni N.↗
DOE OSTI2023

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗
DOE OSTI2021

Using non-invasive MEMS pressure sensors for measuring building envelope air leakage

Micro-electromechanical systems (MEMS)-based sensors have seen significant improvements in accuracy and cost over the past several years, and due to the need for altitude sensing in unmanned aerial vehicles and wearable technologies, absolute pressure sensors have shown the most dramatic improvements. This paper investigates applications of MEMS sensors in commercial buildings, including pairing two absolute pressure sensors to determine differential pressures between different locations in and around buildings. Differential pressure measurements are commonly made in commercial buildings for a number of applications, including static pressure measurements for variable-speed supply fan control, air balancing in hospitals, and for envelope and duct air leakage testing. This paper focuses specifically on envelope air-leakage testing applications of these sensors. The use of continuous pressure measurements in addition to one-time non-intrusive outdoor airflow measurements of rooftop packaged units is investigated. A comparison with standardized leakage testing indicated that continuous measurements with MEMS pressure-sensors were able to estimate envelope leakage to within 3–16% of the standardized test result. In addition, the magnitude and stability of differential pressure differences that can be resolved with absolute pressure sensors are also investigated in the laboratory and the field. Results show that the sensors can be effectively used for pressures seen in low rise buildings with rooftop units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1987

Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination.

Dozier, Jeff↗
NASA NTRS1996

Evaluation of transit-time and electromagnetic flow measurement in a chronically instrumented nonhuman primate model

The Physiology Research Branch at Brooks AFB conducts both human and nonhuman primate experiments to determine the effects of microgravity and hypergravity on the cardiovascular system and to identify the particular mechanisms that invoke these responses. Primary investigative efforts in our nonhuman primate model require the determination of total peripheral resistance, systemic arterial compliance, and pressure-volume loop characteristics. These calculations require beat-to-beat measurement of aortic flow. This study evaluated accuracy, linearity, biocompatability, and anatomical features of commercially available electromagnetic (EMF) and transit-time flow measurement techniques. Five rhesus monkeys were instrumented with either EMF (3 subjects) or transit-time (2 subjects) flow sensors encircling the proximal ascending aorta. Cardiac outputs computed from these transducers taken over ranges of 0.5 to 2.0 L/min were compared to values obtained using thermodilution. In vivo experiments demonstrated that the EMF probe produced an average error of 15% (r = .896) and 8.6% average linearity per reading, and the transit-time flow probe produced an average error of 6% (r = .955) and 5.3% average linearity per reading. Postoperative performance and biocompatability of the probes were maintained throughout the study. The transit-time sensors provided the advantages of greater accuracy, smaller size, and lighter weight than the EMF probes. In conclusion, the characteristic features and performance of the transit-time sensors were superior to those of the EMF sensors in this study.

Non-NASA Center↗
DOE OSTI2024

Object Detection and Recognition with PointPillars in LiDAR Point Clouds – Comparisions

In the field of autonomous systems, neural networks have been leveraged for object detection and recognition in 2-dimensional images captured by cameras. Other types of sensors are available for sensing surroundings, including LiDAR sensors, and corresponding networks have been developed to perform detection and recognition in the point clouds generated by these sensors. The approaches are similar, both perform convolutions, but have distinct characteristics and challenges. In designing and configuring autonomous systems, a variety of LiDAR sensors are available, along with configurable deep neural networks to leverage their data. This work presents a review of the PointPillars network, an evolution of the seminal PointNet, comparing accuracy and training time relative to different LiDAR sensors, network and training parameters, CPU and GPU hardware, and the criticality of the use of reflective intensity as a feature. The value of using reflectivity as a predictive feature is explored and quantified to determine if it makes a significant difference in accuracy of the PointPillars network. Two separate LiDAR sensors are utilized, a 16-plane and a 32-plane, and corresponding accuracies and training times with the PointPillars network are evaluated.

LiDAR, machine learning, neural network, object re↗