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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 NTRS1976

OAST Space Theme Workshop. Volume 3: Working group summary. 3: Sensors (E-3). A. Statement. B. Technology needs (form 1). C. Priority assessment (form 2). D. Additional assessment

Developments required to support the space power, SETI, solar system exploration and global services programs are identified. Instrumentation and calibration sensors (rather than scientific) are needed for the space power system. Highly sophisticated receivers for narrowband detection of microwave sensors and sensors for automated stellar cataloging to provide a mapping data base for SETI are needed. Various phases of solar system exploration require large area solid state imaging arrays from UV to IR; a long focal plane telescope; high energy particle detectors; advanced spectrometers; a gravitometer; and atmospheric distanalyzer; sensors for penetrometers; in-situ sensors for surface chemical analysis, life detection, spectroscopic and microscopic analyses of surface soils, and for meteorological measurements. Active and passive multiapplication sensors, advanced multispectral scanners with improved resolution in the UV and IR ranges, and laser techniques for advanced probing and oceanographic characterization will enhance for global services.

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NASA NTRS1981

Spacecraft attitude calibration/verification baseline study

A baseline study for a generalized spacecraft attitude calibration/verification system is presented. It can be used to define software specifications for three major functions required by a mission: the pre-launch parameter observability and data collection strategy study; the in-flight sensor calibration; and the post-calibration attitude accuracy verification. Analytical considerations are given for both single-axis and three-axis spacecrafts. The three-axis attitudes considered include the inertial-pointing attitudes, the reference-pointing attitudes, and attitudes undergoing specific maneuvers. The attitude sensors and hardware considered include the Earth horizon sensors, the plane-field Sun sensors, the coarse and fine two-axis digital Sun sensors, the three-axis magnetometers, the fixed-head star trackers, and the inertial reference gyros.

Chen, L. C.↗
DOE OSTI2025

Machine Learning-Based Technique for Automated Sensor Characterization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert s time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Zepeda, Cuevas [Chicago U., KICP]↗
DOE OSTI2025

Automating Sensor Characterization with Bayesian Optimization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Cuevas-Zepeda, Julian [Chicago U., KICP; Chicago U↗
NASA NTRS1978

Rotorcraft system identification techniques for handling qualities and stability and control evaluation

An integrated approach to rotorcraft system identification is described. This approach consists of sequential application of (1) data filtering to estimate states of the system and sensor errors, (2) model structure estimation to isolate significant model effects, and (3) parameter identification to quantify the coefficient of the model. An input design algorithm is described which can be used to design control inputs which maximize parameter estimation accuracy. Details of each aspect of the rotorcraft identification approach are given. Examples of both simulated and actual flight data processing are given to illustrate each phase of processing. The procedure is shown to provide means of calibrating sensor errors in flight data, quantifying high order state variable models from the flight data, and consequently computing related stability and control design models.

Hall, W. E., Jr.↗
DOE OSTI2025

Testing, Calibration, and UxS Integration of the Kromek GR1 Plus CZT Gamma Spectrometer

Collecting radiation measurements can be a hazardous task, especially in the presence of highly active sources. Various scenarios necessitate source search, classification, and quantification, often with limited or no a priori information. Activities such as disaster mitigation, emergency response, environmental monitoring, and site remediation may involve dangerous radioactive sources. In these situations, there is a pressing need for remote monitoring capabilities that protect human operators from potential harm and enhance adherence to the principle of “As Low as Reasonably Achievable” (ALARA) for radiation doses. The first step toward achieving remote radiation measurement capabilities is the remote operation of a radiation sensor. Once this milestone is reached, the next challenge is to integrate this remote sensing capability into suitable actuation agents, collectively referred to as uncrewed systems (UxS). These systems include familiar platforms such as robotic quadrupeds, aerial multirotor vehicles, and ground vehicles, any of which may be teleoperated, act autonomously, or utilize a combination of both. A critical factor in achieving remote radiation sensing is the availability of data from the appropriate sensor. Many commercially available radiation sensors have closed-source documentation for their communication protocols. Typical end-user products are often self-contained, handheld devices designed for manual measurement scenarios. While there are commercial off-the-shelf (COTS) integrations of radiation sensors with UxS available for purchase, these solutions are typically tailored for specific use cases and may not meet the requirements of different applications. This paper discusses efforts to remotely acquire radiation measurements from a small form-factor CZT gamma spectrometer. Sandia National Laboratories has successfully demonstrated the initial capability to integrate low size, weight, and power (SWaP) gamma spectroscopy into various UxS, alongside co-located GPS data logging and sensor calibration and qualification. With remote gamma spectroscopy achieved, the stage is set for UxS integration of this capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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↗
DOE OSTI2025

Measuring the thermal conductivity of hydrogels with a bidirectional 3w method

Hydrogels are soft, water-absorbing polymer materials with diverse applications in biomedicine and agriculture. Recently, hydrogels have been proposed to encapsulate water-soluble phase change materials which store energy in their latent heat of solidification. In these applications, the thermal conductivity of these materials affects their performance. Few methods exist for measuring the thermal conductivity of small quantities of hydrogels. Here, we describe an implementation of the bidirectional 3w technique to measure the thermal conductivity of hydrogels with particular attention to their moisture content. Our implementation of the technique can probe sample volumes as little as ~20 mL and yields the thermal conductivity without requiring fitting of additional thermal parameters. We numerically simulate 3w sensor designs with frequency-domain 3-D models to quantify and reduce errors introduced by the choice of substrate and insulation layer thickness. Frequencies in the ~1−20 Hz range yield less error for the materials considered here. We verify our setup with measurements on water and report values for polyacrylamide and poly(2-acrylamido-2-methylpropane sulfonic acid) (PAMPS) hydrogels. Our swollen hydrogels exhibited thermal conductivities nearly equivalent to water, 0.6 W m-1 K-1, and we estimate thermal conductivities of 0.43 and 0.42 W m-1 K-1 for neat polyacrylamide and PAMPS, respectively. Finally, we estimate an error of ±7%, consistent with other 3ω methods, with the largest error coming from the sensor calibration. We find our implementation of the bidirectional 3w method gives reasonable results and can be employed for prototyping soft materials relevant for thermal storage.

3-omega, thermal conductivity, hydrogel, moisture ↗
NASA NTRS1972

The image-processing system for the Earth Resources Technology Satellite.

Description of the image-processing system for the Earth Resources Technology Satellite (ERTS), which will process video-tape recordings received from the satellite into imagery and digitized video data suitable for earth-resource study and analysis. The system is made up of three subsystems. The bulk processor produces 70-mm images and digitized records, corrected for systematic geometric and radiometric errors as well as for sensor-calibration and other errors. The precision processor modifies the bulk images to significantly increase geometric precision. The special processor transfers either bulk or precision data to computer-compatible tape.

Johnson, R. H.↗
NASA NTRS1973

Digital rectification of ERTS multispectral imagery

Rectified ERTS multispectral imagery have been produced utilizing all digital techniques, as the first step toward producing precision corrected imagery. Errors arising from attitude and ephemeris sources have been corrected, and the resultant image is represented in a meter/meter mapping utilizing an intensity resampling technique. Early results from available data indicate negligible degradation of the photometric and resolution properties of the source data as a consequence of the geometric correction process. Work utilizing ground control points to produce precision rectified imagery, and including photometric corrections resulting from available sensor calibration data, is currently in progress.

Rifman, S. S.↗
NASA NTRS1979

Studies of radiative transfer in the earth's atmosphere with emphasis on the influence of the radiation budget in the joint institute for advancement of flight sciences at the NASA-Langley Research Center

Earth and solar radiation budget measurements were examined. Sensor calibration and measurement accuracy were emphasized. Past works on the earth's radiation field that must be used in reducing observations of the radiation field were reviewed. Using a finite difference radiative transfer algorithm, models of the angular and spectral dependence of the earth's radiation field were developed.

Source record↗
NASA NTRS1980

Airborne lightning characterization

A WC-130 aircraft was instrumented with wideband electromagnetic field sensors and flown near active thunderstorms to obtain data on the characteristics of nearby and direct strike lightning. An electric field ground station and time-of-arrival network provided time correlated data to identify the three dimensional locations of the discharge and the different events in the lightning flash. A description of the sensors, calibration procedures, and recording equipment is presented. Data are presented on return stroke characteristics in the 5 to 50 km range.

Baum, R. K.↗
NASA NTRS1980

Middle infrared multispectral aircraft scanner data - Analysis for geological applications

Multispectral middle IR (8-13 microns) data were acquired with an aircraft scanner over Utah. Because these digital image data were dominated by temperature, all six channels were highly correlated. Extensive processing was required to allow geologic photointerpretation based on subtle variations in spectral emittance between rock types. After preliminary processing, ratio images were produced and color ratio composites created from these. Sensor calibration and an atmospheric model allowed determination of surface brightness, temperature, emittance, and color composite emittance images. The best separation of major rock types was achieved with a principal component transformation, followed by a Gaussian stretch, followed by an inverse transformation to the original axes.

Kahle, A. B.↗
NASA NTRS1981

An industrial perspective of the LANDSAT opportunity

The feasibility of enhancing LANDSAT products to provide the greatest usability low cost data possible can be determined through government sponsorship and finance of one or more task forces composed of a critical number of experts in multiple disciplines from many industries and academia. The synergism of multiple minds addressing singular problems without the creation of permanent or perpetual structures must yield output in the form of implementable specifications, even if presented as alternatives. Changes are needed within the spacecraft in order to account for Sun angle changes. The use of pointing accuracy to make geometric corrections (and possible radiometric corrections, is needed more than onboard data reduction and information extraction, which assume a proper knowledge of application and reduce potential utilization. Multilinear arrays need to be investigated and methods for sensor calibration and for determining the effects of atmospheric inversion, as well as the best way to back out the modulation transfer function must be determined.

Williams, B. F.↗
NASA NTRS1981

An examination of spectral band ratioing to reduce the topographic effect on remotely sensed data

Spectral-band ratioing of radiance data is examined as a means of reducing the topographic effect in multispectral data. A ground-based nadir-pointing two-channel radiometer filtered for the red and photographic IR portions of the spectrum was used to measure the topographic effect associated with a uniform surface inclined from horizontal to 60 deg at 16 compass points and for several solar elevations. It is found that ratioing reduced the topographic effect in the field-measured radiance data by an average of 83%, that the remaining topographic effect could be further reduced by subtracting the scattered-light component of the global irradiance before ratioing, and that ratioing was not effective in reducing the topographic effect on shaded surfaces illuminated solely by scattered light. It is concluded that additional variations in ratios can be expected for Landsat data owing to sensor calibration and quantization.

Holben, B.↗
NASA NTRS1982

Hot foil transducer skin friction sensor

The device utilizes foil transducers with only one edge exposed to the fluid flow. The surfaces are polished producing a foil transducer that does not generate turbulence while sufficiently thick to carry the required electrical current for high temperature fluid flow. The assembly utilizes a precut layered metal sandwich with attached electrodes eliminating a need for welding and individual sensor calibration.

Vranas, T.↗
NASA NTRS1982

LANDSAT 4 to ground station interface description, revision 5

The radiometric requirements, internal calibration, sensor output format, geometric characteristics, and data processing constants for the LANDSAT 4 multispectral scanner and thematic mapper are described. In addition, telemetry format, onboard computer reports, and LANDSAT 4 communications are discussed.

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