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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 271 records · Page 15

Dielectric measurement using an open ended coaxial line with an extended center conductor

Permittivity may be determined by measuring the complex reflection coefficient of an open-ended coaxial line placed in contact with a test sample. This method works best for liquid samples. For the measurement of non-liquid materials problems can arise. A perfect preparation is needed to provide a good contact between the tip and the dielectric medium. At times, the dimension of the sensor cannot be freely chosen, as is the case for the measurement of the dielectric constant of the xylem layer of a living tree. The influence of the installation of the sensor on a tree's water status must be minimized by using a small sensor. In such cases the capacitance cannot be optimized. By extending the center conductor of the open-ended coaxial line, some of these problems can be avoided. This provides an additional tool to tune the capacitance of the sensor by adjusting the length of the extension. Therefore the measurement accuracy can be optimized. The sensor also becomes sensitive to a larger volume. A comparative study of a flush and extended tipped probes shows that the ability to measure the dielectric constant of trees has been notably increased due to the extension of the center conductor.

Wegmueller, Urs↗

Relative radiometric calibration of LANDSAT TM reflective bands

A common scientific methodology and terminology is outlined for characterizing the radiometry of both TM sensors. The magnitude of the most significant sources of radiometric variability are discussed and methods are recommended for achieving the exceptional potential inherent in the radiometric precision and accuracy of the TM sensors.

Barker, J. L.↗

Operational support for Upper Atmosphere Research Satellite (UARS) attitude sensors

The Upper Atmosphere Research Satellite (UARS) has several sensors that can provide observations for attitude determination: star trackers, Sun sensors (gimbaled as well as fixed), magnetometers, Earth sensors, and gyroscopes. The accuracy of these observations is important for mission success. Analysts on the Flight Dynamics Facility (FDF) UARS Attitude task monitor these data to evaluate the performance of the sensors taking corrective action when appropriate. Monitoring activities range from examining the data during real-time passes to constructing long-term trend plots. Increasing residuals (differences) between the observed and expected quantities is a prime indicator of sensor problems. Residual increases may be due to alignment shifts and/or degradation in sensor output. Residuals from star tracker data revealed and anomalous behavior that contributes to attitude errors. Compensating for this behavior has significantly reduced the attitude errors. This paper discusses the methods used by the FDF UARS attitude task for maintenance of the attitude sensors, including short- and long-term monitoring, trend analysis, and calibration methods, and presents the results obtained through corrective action.

Lee, M.↗

Guidance, Navigation, and Control for NASA Lunar Pallet Lander

The NASA Lander Technology project is leading the development and integration of the Lunar Pallet Lander (LPL) concept. The objective is to demonstrate precision landing by delivering a payload to the lunar surface within 100 meters of a landing target. Potential landing sites are selected near the lunar pole where water may be present in permanently shadowed regions that could enable future in-situ resource utilization. The LPL is part of a sequence of missions aimed at maturing the necessary technologies, such as lunar precision landing sensors, that will enable the next generation of multi-ton lunar payloads and human landers. This paper provides an overview of the Mission Design, Guidance Navigation and Control (GNC) algorithms, and sensor suite. The results show the LPL simulated trajectory and landing precision performance under nominal and dispersed conditions. The landing precision simulation confirms the need to rely on high-accuracy navigation techniques and sensors such as Terrain Relative Navigation (TRN) and the Navigation Doppler Lidar (NDL), currently being developed for space applications. The results also demonstrate the ability of the guidance and control system to perform a soft lunar touchdown by combining thrust vector control during the solid rocket motor deceleration phase, and pulse engine control, for the liquid powered descent phase.

Orphee, Juan↗

Advances in satellite sea surface temperature measurement and oceanographic applications

Satellite techniques for measurement of sea surface temperature (SST) are reviewed briefly, and a discussion of satellite SST applications and recent research in oceanography is provided. These applications include the areas of climate, mesoscale oceanography, and fisheries. Examples given focus mainly on the Pacific and California Current regions. Satellite SST data are currently used operationally for fisheries applications and, in conjunction with in situ data, are providing new insights into mesoscale oceanographic phenomena. Requirements for sensor precision and calibration accuracy are more stringent in air-sea interaction studies and climate research, thus satellite data have gained only qualified acceptance for these applications. Improvements in future satellite instruments, more comprehensive in situ sensor deployments, and better data management procedures should eventually satisfy most oceanography and climate SST requirements.

Njoku, E. G.↗

Climate Quality Broadband and Narrowband Solar Reflected Radiance Calibration Between Sensors in Orbit

vAs the potential impacts of global climate change become more clear [1], the need to determine the accuracy of climate prediction over decade-to-century time scales has become an urgent and critical challenge. The most critical tests of climate model predictions will occur using observations of decadal changes in climate forcing, response, and feedback variables. Many of these key climate variables are observed by remotely sensing the global distribution of reflected solar spectral and broadband radiance. These "reflected solar" variables include aerosols, clouds, radiative fluxes, snow, ice, vegetation, ocean color, and land cover. Achieving sufficient satellite instrument accuracy, stability, and overlap to rigorously observe decadal change signals has proven very difficult in most cases and has not yet been achieved in others [2]. One of the earliest efforts to make climate quality observations was for Earth Radiation Budget: Nimbus 6/7 in the late 1970s, ERBE in the 1980s/90s, and CERES in 2000s are examples of the most complete global records. The recent CERES data products have carried out the most extensive intercomparisons because if the need to merge data from up to 11 instruments (CERES, MODIS, geostationary imagers) on 7 spacecraft (Terra, Aqua, and 5 geostationary) for any given month. In order to achieve climate calibration for cloud feedbacks, the radiative effect of clear-sky, all-sky, and cloud radiative effect must all be made with very high stability and accuracy. For shortwave solar reflected flux, even the 1% CERES broadband absolute accuracy (1-sigma confidence bound) is not sufficient to allow gaps in the radiation record for decadal climate change. Typical absolute accuracy for the best narrowband sensors like SeaWiFS, MISR, and MODIS range from 2 to 4% (1-sigma). IPCC greenhouse gas radiative forcing is approx. 0.6 W/sq m per decade or 0.6% of the global mean shortwave reflected flux, so that a 50% cloud feedback would change the global reflected flux by approx. 0.3 W/sq m or 0.3% per decade in broadband SW calibration change. Recent results comparing CERES reflected flux changes with MODIS, MISR, and SeaWiFS narrowband changes concluded that only SeaWiFS and CERES were approaching sufficient stability in calibration for decadal climate change [3]. Results using deep convective clouds in the optically thick limit as a stability target may prove very effective for improving past data sets like ISCCP. Results for intercalibration of geostationary imagers to CERES using an entire month of regional nearly coincident data demonstrates new approaches to constraining the calibration of current geostationary imagers. The new Decadal Survey Mission CLARREO is examining future approaches to a "NIST-in-Orbit" approach of very high absolute accuracy reference radiometers that cover the full solar and infrared spectrum at high spectral resolution but at low spatial resolution. Sampling studies have shown that a precessing CLARREO mission could calibrate other geo and leo reflected solar radiation and thermal infrared sensors.

Wielicki, Bruce A.↗

The attitude accuracy consequences of on-orbit calibration of the Extreme Ultraviolet Explorer attitude sensors by the Flight Dynamics Facility at Goddard Space Flight Center

The science mission of the Extreme Ultraviolet Explorer (EUVE) requires attitude solutions with uncertainties of 27, 16.7, 16.7 arcseconds (3 sigma) around the roll, pitch, and yaw axes, respectively. The primary input to the attitude determination process is provided by two NASA standard fixed-head star trackers (FHSTs) and a Teledyne dry rotor inertial reference unit (DRIRU) 2. The attitude determination requirements approach the limits attainable with the FHSTs and DRIRU. The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) designed and executed calibration procedures that far exceeded the extent and the data volume of any other FDF-supported mission. The techniques and results of this attempt to obtain attitude accuracies at the limit of sensor capability and the results of analysis of the factors that limit the attitude accuracy are the primary subjects of this paper. The success of the calibration effort is judged by the resulting measurement residuals and comparisons between ground- and onboard-determined attitudes. The FHST star position residuals have been reduced to less tha 4 arcsec per axis -- a value that appears to be limited by the sensor capabilities. The FDF ground system uses a batch least-squares estimator to determine attitude. The EUVE onboard computer (OBC) uses an extended Kalman filter. Currently, there are systematic differences between the two attitude solutions that occasionally exceed the mission requirements for 3 sigma attitude uncertainty. Attempts to understand and reduce these differences are continuing.

Hashmall, J.↗

Time-Energy Uncertainty Relation for Noisy Quantum Metrology

Detection of very weak forces and precise measurement of time are two of the many applications of quantum metrology to science and technology. To sense an unknown physical parameter, one prepares an initial state of a probe system, allows the probe to evolve as governed by a Hamiltonian 𝐻 for some time 𝑡, and then measures the probe. If 𝐻 is known, we can estimate 𝑡 by this method; if 𝑡 is known, we can estimate classical parameters on which 𝐻 depends. The accuracy of a quantum sensor can be limited by either intrinsic quantum noise or by noise arising from the interactions of the probe with its environment. In this work, we introduce and study a fundamental trade-off, which relates the amount by which noise reduces the accuracy of a quantum clock to the amount of information about the energy of the clock that leaks to the environment. Specifically, we consider an idealized scenario in which a party Alice prepares an initial pure state of the clock, allows the clock to evolve for a time that is not precisely known, and then transmits the clock through a noisy channel to a party Bob. Meanwhile, the environment (Eve) receives any information about the clock that is lost during transmission. We prove that Bob’s loss of quantum Fisher information about the elapsed time is equal to Eve’s gain of quantum Fisher information about a complementary energy parameter. We also prove a similar, but more general, trade-off that applies when Bob and Eve wish to estimate the values of parameters associated with two noncommuting observables. We derive the necessary and sufficient conditions for the accuracy of the clock to be unaffected by the noise, which form a subset of the Knill-Laflamme error-correction conditions. A state and its local time-evolution direction, if they satisfy these conditions, are said to form a metrological code. We provide a scheme to construct metrological codes in the stabilizer formalism. We show that there are metrological codes that cannot be written as a quantum error-correcting code with similar distance in which the Hamiltonian acts as a logical operator, potentially offering new schemes for constructing states that do not lose any sensitivity upon application of a noisy channel. We discuss applications of the trade-off relation to sensing using a quantum many-body probe subject to erasure or amplitude-damping noise.

metrology↗

MODIS and VIIRS Calibration History and Future Outlook

The MODIS is a key instrument for NASA’s EOS program, currently operated onboard the Terra and Aqua spacecraft launched in 1999 and 2002, respectively. The VIIRS is a MODIS follow-on instrument for the JPSS program. Adding to the ones operated onboard the S-NPP and NOAA-20 satellites launched in 2011 and 2017, respectively, three nearly identical VIIRS instruments will also be launched. This will enable the data records from MODIS and VIIRS to be extended beyond 2040. In addition to various applications and scientific studies of the Earth’s system, long-term data records from MODIS and VIIRS observations will greatly benefit the space-based climate observing system. This is attributed to the high-quality measurements and extensive calibration efforts, from pre-launch to post-launch. This paper provides an overview of MODIS and VIIRS calibration history and approaches applied to establish and maintain sensor calibration traceability and accuracy. It illustrates calibration and performance issues through different phases of the mission using examples derived from ground testing equipment, on-board calibrators, and other calibration targets. Moreover, discussed in this paper are outstanding challenges and future efforts to maintain and improve sensor calibration stability and long-term data quality, and to better support the space-based climate observing system.

MODIS↗

Synthetic Scene Generation of the Stennis V and V Target Range for the Calibration of Remote Sensing Systems

The verification and validation (V&V) target range developed at Stennis Space Center is a useful test site for the calibration of remote sensing systems. In this paper, we present a simple algorithm for generating synthetic radiance scenes or digital models of this target range. The radiation propagation for the target in the solar reflective and thermal infrared spectral regions is modeled using the atmospheric radiative transfer code MODTRAN 4. The at-sensor, in-band radiance and spectral radiance for a given sensor at a given altitude is predicted. Software is developed to generate scenes with different spatial and spectral resolutions using the simulated at-sensor radiance values. The radiometric accuracy of the simulation is evaluated by comparing simulated with AVIRIS acquired radiance values. The results show that in general there is a good match between AVIRIS sensor measured and MODTRAN predicted radiance values for the target despite the fact that some anomalies exist. Synthetic scenes provide a cost-effective way for in-flight validation of the spatial and radiometric accuracy of the data. Other applications include mission planning, sensor simulation, and trade-off analysis in sensor design.

Cao, Chang-Yong↗

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.

Engineering↗

Testing and Improving a UAV-Based System Designed for Wetland Methane Source Measurements

Wetlands are the single highest emitting methane source category, but the magnitude of wetland fluxes remains difficult to fully characterize due to their large spatial extent and heterogeneity. Fluxes can vary with land surface conditions, vegetation type, and seasonal changes in environmental conditions. Unmanned aerial vehicles (UAVs) are an emerging platform to better characterize spatial variability in these natural ecosystems. While presenting some advantages over traditional techniques like towers and flux chambers, in that they are mobile vertically and horizontally, their use is still challenging, requiring continued improvement in sensor technology and field measurement approaches. In this work, we employ a small, fast response laser spectrometer on a Matrice 600 hexacopter. The system was previously deployed successfully for 40 flights conducted in a four-day period in 2018 near Fairbanks, Alaska. These flights revealed several potential areas for improvement, including: vertical positioning accuracy, the need for sensor health indicators, and approaches to deal with low wind speeds. An additional set of flights was conducted this year near Antioch in California. Flights were conducted several meters above ground up to 15-25 m in a curtain pattern. These curtains were flown both upwind and downwind of a tower site, allowing us to calculate a mass balance methane flux estimate that can be compared to eddy covariance fluxes from the tower. Testing will better characterize the extent to which altitude drifts in-flight and how GPS values compare with measurements from the onboard LIDAR, as well as the agreement between two-dimensional wind speed and direction on the ground versus measured onboard the UAV. Hardware improvements to the sensor and GPS are being considered to help reduce these sources of uncertainty. Results of this testing and how system performance relates to needs for quantifying wetland fluxes, will be presented.

Golston, Levi↗

Shuttle propellant loading instrumenation development

A continuous capacitance sensor was developed and an analog signal conditioner was evaluated to demonstrate the acceptability of these items for use in the space shuttle propellant loading system. An existing basic sensor concept was redesigned to provide capability for cryogenic operation, to improve performance, and to minimize production costs. Sensor development verification consisted of evaluation of sensor linearity, cryogenic performance, and stability during vibration. The signal conditioner evaluation consisted mainly of establishing the effects of the variations in temperature and cable parameters and evaluating the stability. A sensor linearity of 0.04 in. was achieved over most of the sensor length. The sensor instability caused by vibration was 0.04 percent. The cryogenic performance data show a maximum instability of 0.19 percent at liquid hydrogen temperature; a theoretical calibration can be computed a within 1 percent. The signal conditioner evaluation showed that, with temperature compensation, all error sources typically contribute much less than 1 percent. An estimate of the accuracy achievable with the sensor and signal conditioner shows an rss estimate of 0.75 in. for liquid oxygen and 1.02 in. for liquid hydrogen. These are approximately four times better than the shuttle requirements. Comparison of continuous sensor and discrete sensor performance show the continuous sensor to be significantly better when there is surface activity due to sloshing, boiling, or other disturbances.

Hamlet, J.↗

Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain

Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from differences in the methods of measurement, the vertical and temporal resolution of the measurements, and the spatial variability of these differences. Here we quantify instrument measurement variability in 80-m wind speed during WFIP2 and its impact on the calculated errors and the change in error from one model version to another. Here the model versions tested involved updates in model physics from HRRRv1 to HRRRv4, and reductions in grid interval from 3 km to 750 m. Model errors were found to be 2–3 m s –1 . Differences in errors as determined by various instruments at each site amounted to about 10% of this value, or 0.2–0.3 m s –1 . Changes in model skill due to physics or grid-resolution updates also differed depending on the instrument used to determine the errors; most of the instrument-to-instrument differences were ~0.1 m s –1 , but some reached 0.3 m s –1 . All instruments at a given site mostly showed consistency in the sign of the change in error. In two examples, though, the sign changed, illustrating a consequence of differences in measurements: errors determined using one instrument may show improvement in model skill, whereas errors determined using another instrument may indicate degradation. This possibility underscores the importance of having accurate measurements to determine the model error.

54 ENVIRONMENTAL SCIENCES↗

High Resolution and Large Dynamic Range Resonant Pressure Sensor Based on Q-Factor Measurement

A pressure sensor has a high degree of accuracy over a wide range of pressures. Using a pressure sensor relying upon resonant oscillations to determine pressure, a driving circuit drives such a pressure sensor at resonance and tracks resonant frequency and amplitude shifts with changes in pressure. Pressure changes affect the Q-factor of the resonating portion of the pressure sensor. Such Q-factor changes are detected by the driving/sensing circuit which in turn tracks the changes in resonant frequency to maintain the pressure sensor at resonance. Changes in the Q-factor are reflected in changes of amplitude of the resonating pressure sensor. In response, upon sensing the changes in the amplitude, the driving circuit changes the force or strength of the electrostatic driving signal to maintain the resonator at constant amplitude. The amplitude of the driving signals become a direct measure of the changes in pressure as the operating characteristics of the resonator give rise to a linear response curve for the amplitude of the driving signal. Pressure change resolution is on the order of 10(exp -6) torr over a range spanning from 7,600 torr to 10(exp -6) torr. No temperature compensation for the pressure sensor of the present invention is foreseen. Power requirements for the pressure sensor are generally minimal due to the low-loss mechanical design of the resonating pressure sensor and the simple control electronics.

Gutierrez, Roman C.↗

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗

Chemical detection system with at least one electronic nose

A system for predicting one or more analytes based on outputs from thin film gas sensors is provided. The system may comprise an electronic nose (e-nose). The e-nose may comprise the gas sensors and a first processor. The system may further comprise a second processor. The second processor may be configured to receive the output from each of the gas sensors, evaluate a prediction accuracy using an evaluation parameter of each of a plurality of models which are trained and tested and select a model from among the plurality of models to deploy based on a comparison of the evaluation parameter for each of the plurality of models and use the same. The second processor may also receive, an output of each of the gas sensors caused by unknown one or more analytes; and predict, using the deployed model, the one or more analytes that causes the output.

Ivanov, Ilia N.↗

Thermal Stability of the AVIRIS On-Board Calibrator

The AVIRIS On-Board Calibrator (OBC) provides essential data for refining the calibration of each AVIRIS data run. Annual improvement to the AVIRIS sensor and laboratory calibration accuracy has resulted in increasingly high demands on the stability of the OBC. Since the 1995 flight season, the OBC could track the stability of the spectrometer alignment to the 2% level, a significant improvement over previous years. The major contributor to this 2% stability was the conversion from a constant-current bulb power supply to an intensity-based active feedback power supply. Given the high sensor signal-to-noise ratio, improving the OBC to track 1% or 0.5% changes was highly desirable. Achieving stability better than 2% required an examination of the mechanisms affecting stability.

Faust, Jessica↗