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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Novel RFID-Based Strain Sensor for Wireless Structural Health Monitoring

Conventional tools for deformation measurement are widely used for structural health monitoring—i.e. strain gauges and fiber optic sensors—due to their relative low cost and efficiency. However, these techniques still present some drawbacks particularly in limited access locations, since their usage requires some sort of cabling or battery-driven electronics. Thus, in a few situations there may be room for new technologies for deformation monitoring of structures. One of the options are passive radio frequency identification (RFID)-based sensors. In synthesis, like conventional methods, these sensors are attached to the surface a test-piece, but are then remotely interrogated and powered by a transmitter. The solidarity of the sensor to the underlying material means that the detected signal is modified in a way that can be correlated to sample strain in a given direction. This paper encompasses the project of a wireless deformation sensor based on an inverted-F antenna focusing on its miniaturization and performance optimization. For this purpose, such an antenna was designed with the help of finite element modelling tools for operation on a 2.0 mm-thick aluminium sheet, and then experimentally validated through static loading tests. Finally, even though sensors of this kind are still in early developments, results show that RFID sensors represents a promising method for remote deformation assessment in components.

42 ENGINEERING↗
DOE OSTI2024

Applications of fuzzy logic and best-worst method for tritium sensor selection

Accurate assessment of tritium as a fuel source is critical in fusion reactions, necessitating effective sensor evaluation methods. This study investigates a multi-criteria decision-making framework for selecting tritium sensors, integrating fuzzy logic to enhance decision quality. Initial attempts at applying fuzzy logic were found to be too elementary and failed to capture the complexity of multi-criteria selection; this prompted a refined approach that incorporated expert insights and advanced ranking techniques for sensor evaluation. The research used a two-stage methodology. In the first stage, important criteria and sub-criteria for sensor performance were identified and defined. These criteria were then weighted and scored using a fuzzy best-worst method, drawing upon expert opinions to ensure relevance and validity. The second stage involved interpreting information about varying sensors to rank them based on their overall criteria scores, encouraging the selection of the most suitable options. The result of the study is a proposed method for effective sensor selection in fusion reactors, which in turn will significantly improve the reliability of tritium monitoring in fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems

Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There are two key research gaps for missing sensor data imputation in buildings: the lack of customized and automated imputation methodology, and the difficulty of the validation of data imputation methods. In this paper, a framework is developed to address these two gaps. First, a validation data generation module is developed based on pattern recognition to create a validation dataset to quantify the performance of data imputation methods. Second, a pool of data imputation methods is tested under the validation dataset to find an optimal single imputation method for each sensor, which is termed as an ensemble method. The method can reflect the specific mechanism and randomness of missing data from each sensor. The effectiveness of the framework is demonstrated by 18 sensors from a real campus building. The overall accuracy of data imputation for those sensors improves by 18.2% on average compared with the best single data imputation method.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

Prospects of the ICESat-2 Laser Altimetry Mission for Savanna Ecosystem Structural Studies Based on Airborne Simulation Data

The next planned spaceborne lidar mission is the Ice, Cloud and land Elevation Satellite 2 (ICESat-2), which will use the Advanced Topographic Laser Altimeter System (ATLAS) sensor, a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in an oak savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA's Goddard Space Flight Center. ATLAS-like data was generated using the MATLAS simulator, which adjusts MABEL data's detected number of signal and noise photons to that expected from the ATLAS instrument. Transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we chose to use data from the near infrared channel that had the highest number of photons. We segmented each transect into 50 m, 25 m and 14 m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an automated algorithm to identify cut off points where the cumulative density of photons from the highest elevation indicates the presence of the canopy top and likewise where such cumulative density from the lowest elevation indicates the mean terrain elevation. MABEL derived height metrics were moderately correlated to discrete return lidar (DRL) derived height metrics r(sub 2) and RMSE values ranging from 0.60 to 0.73 and 2.9 m to 4.4 m respectively) but MATLAS simulation resulted in more modest correlations with DRL indices r(sub 2) ranging from 0.5 to 0.64 and RMSE from 3.6 m to 4.6 m). Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover. On the basis of the simulated data, there is reason to believe that the ability of ICESat-2 to estimate height in savannas will be comparable to the original ICESat mission although the respective sensors have different measurement principles.

Gwenzi, David↗
DOE OSTI2020

Selective Sampling for Sensor Type Classification in Buildings

A key barrier to applying any smart technology to a building is the requirement of locating and connecting to the necessary resources among the thousands of sensing and control points, i.e., the metadata mapping problem. Existing solutions depend on exhaustive manual annotation of sensor metadata --- a laborious, costly, and hardly scalable process. To reduce the amount of manual effort required, this paper presents a multi-oracle selective sampling framework to leverage noisy labels from information sources with unknown reliability such as existing buildings, which we refer to as weak oracles, for metadata mapping. This framework involves an interactive process, where a small set of sensor instances are progressively selected and labeled for it to learn how to aggregate the noisy labels as well as to predict sensor types. Two key challenges arise in designing the framework, namely, weak oracle reliability estimation and instance selection for querying. To address the first challenge, we develop a clustering-based approach for weak oracle reliability estimation to capitalize on the observation that weak oracles perform differently in different groups of instances. For the second challenge, we propose a disagreement-based query selection strategy to combine the potential effect of a labeled instance on both reducing classifier uncertainty and improving the quality of label aggregation. We evaluate our solution on a large collection of real-world building sensor data from 5 buildings with more than 11,000 sensors of 18 different types. The experiment results validate the effectiveness of our solution, which outperforms a set of state-of-the-art baselines.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRSDate not supplied

Predicting SLS Launch Environment using a Novel Multiphase Formulation

Powerful acoustic waves generated during ignition of launch vehicles may be dangerous to the vehicle, its payload, or the surrounding structures. The water-based Ignition Overpressure and Sound Suppression (IOP/SS) system at Kennedy Space Center’s (KSC) Launch Complex 39B (LC-39B) will be used to protect the Space Launch System (SLS) from the acoustic vibrations generated during launch. The IOP/SS system uses enormous amounts of water to dampen and attenuate these sound waves. To better understand the launch environment risks and to study the effectiveness of the IOP/SS system it is desirable to have time-accurate unsteady simulations of the vehicle ignition with water-based sound suppression. This paper presents results obtained with a novel, high-order accurate, and robust numerical method designed for simulating compressible multiphase flows. A positivity-preserving finite difference scheme is utilized which is formally high-order accurate and also provably robust. Robustness is critical due to the extreme nature of the flow which exhibits highly nonlinear shock and rarefaction waves interacting with liquid-gas interfaces with density ratios of the order of 1000:1. Furthermore, the high-order accuracy (and the high resolution property) is desirable for predicting wave phenomena like IOP waves since the signal can be resolved accurately and propagated long distances with fewer grid points. This finite-difference method was developed using NASA’s Launch, Ascent, and Vehicle Aerodynamics (LAVA) Cartesian immersed boundary framework. We present a validation case by applying our solver to the SLS Scale Model Acoustic Test (SMAT). The SLS SMAT is a well-instrumented 5% scale model test meant to represent the SLS at NASA KSC’s LC-39B pad. Scale IOP tests were performed with and without the sound suppression water and included many sensors which recorded the pressure waves produced during ignition. For this validation case we conduct two simulations, likewise with and without sound suppression water, and compare the SLS SMAT pressure sensor signals with our numerical signals at identical locations. Following this validation case we present a study of the SLS launch environment to examine engineering safety concerns about the mobile launch pad. Engineers at KSC redesigned the main flame deflector at LC-39B anticipating the increased loads from the SLS and to repair damage from prior Shuttle missions. This deflector redesign made use of surface pressure and temperature data from LAVA full-scale SLS simulations without the sound suppression system. The engineers were questioning the possibility of increased pressure loads on the underside of the mobile launcher due to the water in the flame trench. Based on the results established in our simulations of the SLS SMAT, we performed updated calculations for SLS at LC-39B with and without water systems active to assess the readiness of the launch pad for Artemis I launch. Our results show that the IOP/SS system is effective at reducing the overpressure signal and overall sound pressure levels felt by the vehicle and additionally that the pressure loads experienced by the mobile launcher (ML) during engine startup is not increased by the presence of water.

EGS↗
NASA NTRS2009

Sensor System Performance Evaluation and Benefits from the NPOESS Airborne Sounder Testbed-Interferometer (NAST-I)

Advanced satellite sensors are tasked with improving global-scale measurements of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring, and environmental change detection. Validation of the entire measurement system is crucial to achieving this goal and thus maximizing research and operational utility of resultant data. Field campaigns employing satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft are an essential part of this validation task. The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I) has been a fundamental contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This paper focuses on some of the challenges associated with validating advanced atmospheric sounders and the benefits obtained from employing airborne interferometers such as the NAST-I. Select results from underflights of the Aqua Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) obtained during recent field campaigns will be presented.

Larar, A.↗
NASA NTRS2018

Reflectance-Based Imaging Spectrometer Error Budget Field Practicum at the Railroad Valley Test Site, Nevada

Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.

Ong, Cindy↗
DOE OSTI2024

Accurate Ultrasonic Thickness Measurement for Arbitrary Time-Variant Thermal Profile

Ultrasonic thickness measurement of mechanical structures is one of the most popular and commonly used nondestructive methods for various kinds of process control and corrosion monitoring. With ultrasonic propagation speed being temperature-dependent, the thickness measurement can be performed reliably only when the thermal profile is completely known. Most conventional techniques assume the temperature of the test structure is uniform and at room temperature across its thickness. Such assumptions may lead to large errors in the thickness measurement, especially when there are significant temperature variations across the thickness. State-of-the-art techniques use external temperature measurements or implement iterative methods to compensate for the unknown thermal profiles. However, such techniques produce unsatisfactory results when the heat distribution is complex or varies rapidly with time. In this work, we propose a two-sensors technique, using both compressive and shear excitations, with a non-iterative rapid data processing method for accurate thickness measurement under arbitrary time-variant thermal profile. The independent behavior of shear and compressive waves is used to formulate a real-time thickness estimation technique. The developed technique is experimentally validated on a steel plate with fixed acoustic sensors. Test results show that the error in thickness estimation can be reduced by up to 98% compared to conventional thickness gauging methods.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Experimenting with Sensor Webs Using Earth Observing 1

The New Millennium Program (NMP) Earth Observing 1 ( EO-1) satellite was launched November 21, 2000 as a one year technology validation mission. After an almost flawless first year of operations, EO-1 continued to operate in a test bed d e to validate additional technologies and concepts that will be applicable to future sensor webs. A sensor web is a group of sensors, whether space-based, ground-based or air plane-based which act in a collaborative autonomous manner to produce more value than would otherwise result from the individual observations.

Mandl, Dan↗
NASA NTRS2006

AIRS Retrieval Validation During the EAQUATE

Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.

Zhou, Daniel K.↗
NASA NTRS2019

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

ocean colour↗
DOE OSTI2023

Noninvasive liquid level sensing with laser generated ultrasonic waves

This article proposes a noninvasive liquid level sensing technique using laser-generated ultrasound waves for nuclear power plant applications. Liquid level sensors play an important role of managing the coolant system safely and stably in the plant structure. Current sensing techniques are mostly intrusive, performing inside the fluidic structure, which is disadvantageous in terms of the regular maintenance of the plant system. Furthermore, typical intrusive sensors do not perform stably under varying environmental conditions such as temperature and radiation. In this study, sensing units are attached to the outer surface of a liquid vessel to capture guided ultrasound waves in a nonintrusive manner. The signal intensity of the guided wave dissipates when the signal interacts with the internal liquid media. The sensing mechanism is mathematically expressed as an index value to correlate the liquid level with the sensor signal. For the acoustic wave generation, laser-generated ultrasound was adopted instead of using typical contact type transducers. Following the simulation validation of the proposed concept, the performance of the developed sensor was confirmed through experimental results under elevated liquid temperature conditions. Finally, the nonlinear multivariable regression exhibited the best-fit to the datasets measured under the variable liquid level and temperature conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Extracted Radar Columns and In Situ Sensors (RadCLss) Value-Added Product Report

In order to validate precipitation, in 2010 the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility procured 3- and 5-cm wavelength radars for documenting the macrophysical, microphysical, and dynamical structure of precipitating systems. To maximize the scientific impact, ARM supported the development of an application chain to correct for various phenomena in order to retrieve the “point” values of moments of the radar spectrum and polarimetric measurements. In estimation from ARM radars, a workflow was created to directly compare radar “point” values with various in situ observations at the surface.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Agricultural scene understanding

The author has identified the following significant results. The LACIE field measurement data were radiometrically calibrated. Calibration enabled valid comparisons of measurements from different dates, sensors, and/or locations. Thermal band canopy results included: (1) Wind velocity had a significant influence on the overhead radiance temperature and the effect was quantized. Biomass and soil temperatures, temperature gradient, and canopy geometry were altered. (2) Temperature gradient was a function of wind velocity. (3) Temperature gradient of the wheat canopy was relatively constant during the day. (4) The laser technique provided good quality geometric characterization.

Landgrebe, D. A.↗
NASA NTRS1993

An assessment of the Nimbus-7/CZCS calibration for May 1986 using satellite and in situ data from the Arabian Sea

A hydrographic survey of the central Arabian Sea was conducted in May 1986 and stations were correlated with Nimbus-7/Coastal Zone Color Scanner (CZCS) overpasses. As calibration of the CZCS degraded severely during its lifetime, pigment concentrations from samples at four sites in the Arabian Sea were used to refine the calibration of the CZCS. This vicarious calibration technique provided a final estimate of the sensor's sensitivity loss for sensor Gain 2. Calibration using normalized water-leaving radiance for the 520 nm and 550 nm bands showed considerable final sensor degradation. Future missions must incorporate calibration validation programs in order to maintain derived product accuracy requirements. Profiles of pigment concentration, salinity, temperature, and light attenuation are used to describe the bio-optical characteristics of the Arabian Sea during the intermonsoon period.

Hay, Bernward J.↗