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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

PASP Plus: An experiment to measure space-environment effects on photovoltaic power subsystems

The Photovoltaic Array Space Power Plus Diagnostic experiment (PASP Plus) was accepted as part of the APEX Mission payload aboard a Pegastar satellite to be orbited by a Pegasus launch vehicle in late 1992. The mission's elliptical orbit will allow us to investigate both space plasma and space radiation effects. PASP Plus will have eleven types of solar arrays and a full complement of environmental and interactions diagnostic sensors. Measurements of space-plasma interactions on the various solar arrays will be made at large negative voltages (to investigate arcing parameters) and at large positive voltages (to investigate leakage currents) by biasing the arrays to various levels up to -500 and +500 volts. The long-term deterioration in solar array performance caused by exposure to space radiation will also be investigated; radiation dosage will be measured by an electron/proton dosimeter included in the environmental sensor complement. Experimental results from PASP Plus will help establish cause-and-effect relationships and lead to improved design guidelines and test standards for new-technology solar arrays.

Guidice, Donald A.↗
NASA NTRS2005

Adaptive Control for Microgravity Vibration Isolation System

Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

Yang, Bong-Jun↗
NASA NTRS1992

A 6 degree-of-freedom Lorentz force vibration isolator with nonlinear controller

This program demonstrated the technical feasibility of constructing large-stroke magnetic suspensions that can meet the active vibration isolation requirements of Space Station. These requirements include: (1) strokes over 1 cm in all directions, (2) actuator bandwidths over 100 Hz, (3) isolator roll-off frequencies below 10(exp -2) Hertz, and (4) force capability over 1 Newton in all axes. The 100 Hz actuator bandwidth allows the suspension to reject any direct force disturbances that act on the microgravity experiment, for example forces created by cable connections. The low isolator roll-off frequency and large stroke allow the magnetic suspension to isolate the microgravity experiment from Space Station vibrations above the roll-off frequency. The capability to meet these requirements was demonstrated by designing, constructing and testing a six-degree-of-freedom, prototype magnetic suspension system that featured high-performance, Lorentz-force actuators and full multi-input, multi-output control. This prototype suspension is designed to isolate large orbiter locker experiments under typical spacecraft constraints of size, weight, and power. Suspension in the full six-degrees-of-freedom was successfully demonstrated in this program while using a gravity-force unload mechanism to simulate a space environment. The prototype isolator is capable of space-based isolation service with relatively minor modification. The use of advanced, nonlinear control algorithms were investigated on a specially designed single-degree-of-freedom testbed. This low acceleration test facility simulates the Space Station vibration isolation problem in a single horizontal axis with low-friction, air-slide support. This allowed testing at the desired microgravity levels, without the gravity bias effects that are seen in a full six-degrees-of-freedom suspension. Precision components were used to reduce residual accelerations to microgravity levels so that the effects of sensor, actuator, and electronic noise could be evaluated. During the Phase 2 program, this testbed was used to demonstrate the advantages of nonlinear control algorithms to provide increased vibration isolation performance.

Fenn, Ralph↗
NASA NTRS2018

Effects of Normal Metal Features on Superconducting Transition-Edge Sensors

In transition-edge sensors (TESs), the addition of normal metal stripes on top of the superconducting bilayer, perpendicular to the current direction, is known to globally alter the sensitivity of the resistance R to changes in temperature T and current I. Here, we describe measurements of the dependence of the TES current on magnetic field B, bath temperature and voltage bias in devices with various numbers of stripes. We show that the normal metal features have a profound effect on the appearance of localized regions of very large (T/R) dR/dT. We associate this with changes in the current distribution and corresponding changes in the oscillatory pattern of I (B). 140 μm TESs with no stripes are found to have a relatively smooth resistive transition and sufficiently low noise that the measured energy resolution is 1.6 eV for X-rays of 1.5 keV. The predicted energy resolution at 6 keV is better than 2 eV, once the heat capacity is optimized for these higher energies..

Wakeham, N. A.↗
NASA NTRS2016

Experimental Comparison of Piezoelectric and Magnetostrictive Shunt Dampers

A novel mechanism called the vibration ring is being developed to enable energy conversion elements to be incorporated into the driveline of a helicopter or other rotating machines. Unwanted vibration is transduced into electrical energy, which provides a damping effect on the driveline. The generated electrical energy may also be used to power other devices (e.g., health monitoring sensors). PZT (piezoceramic) and PMN-30PT (single crystal) stacks, as well as a Tb_0.3 Dy_0.7 Fe_1.92 (Terfenol-D) rod with a bias magnet array and a pickup coil, were tested as alternative energy conversion elements to use within the vibration ring. They were tuned for broadband damping using shunt resistors, and dynamic compression testing was conducted in a high-speed load frame. Energy conversion was experimentally optimized at 750Hz by tuning the applied bias stress and resistance values. Dynamic testing was conducted up to 1000Hz to determine the effective compressive modulus, shunt loss factor, internal loss factor, and total loss factor. Some of the trends of modulus and internal loss factor versus frequency were unexplained. The single crystal device exhibited the greatest shunt loss factor whereas the Terfenol-D device had the highest internal and total loss factors. Simulations revealed that internal losses in the Terfenol-D device were elevated by eddy current effects, and an improved magnetic circuit could enhance its shunt damping capabilities. Alternatively, the Terfenol-D device may be simplified to utilize only the eddy current dissipation mechanism (no pickup coil or shunt) to create broadband damping.

energy conversion↗
NASA NTRS2016

Experimental Comparison of Piezoelectric and Magnetostrictive Shunt Dampers

A novel mechanism called the vibration ring is being developed to enable energy conversion elements to be incorporated into the driveline of a helicopter or other rotating machines. Unwanted vibration is transduced into electrical energy, which provides a damping effect on the driveline. The generated electrical energy may also be used to power other devices (e.g., health monitoring sensors). PZT (piezoceramic) and PMN-30%PT (single crystal) stacks, as well as a Tb_0.3 Dy_0.7 Fe_1.92 (Terfenol-D) rod with a bias magnet array and a pickup coil, were tested as alternative energy conversion elements to use within the vibration ring. They were tuned for broadband damping using shunt resistors, and dynamic compression testing was conducted in a high-speed load frame. Energy conversion was experimentally optimized at 750Hz by tuning the applied bias stress and resistance values. Dynamic testing was conducted up to 1000Hz to determine the effective compressive modulus, shunt loss factor, internal loss factor, and total loss factor. Some of the trends of modulus and internal loss factor versus frequency were unexplained. The single crystal device exhibited the greatest shunt loss factor whereas the Terfenol-D device had the highest internal and total loss factors. Simulations revealed that internal losses in the Terfenol-D device were elevated by eddy current effects, and an improved magnetic circuit could enhance its shunt damping capabilities. Alternatively, the Terfenol-D device may be simplified to utilize only the eddy current dissipation mechanism (no pickup coil or shunt) to create broadband damping.

piezoelectric↗
NASA NTRS1994

Overview of the MSTI 2 on-orbit alignment

The Miniature Sensor Technology Integration (MSTI) 2 Spacecraft is a small 3-axis stabilized spacecraft designed to track mid-range missiles and estimate their state vectors. In order to accurately estimate the target state vector, the MSTI 2 spacecraft must have highly accurate knowledge of its own attitude. Errors in its attitude knowledge arise primarily from the errors in its Attitude Control System (ACS) sensors. The ACS sensors on the spacecraft include a scanning Earth Sensor (ES), a Sun Sensor (SS), and two 2-axis gyros. The On-Orbit Alignment (OOA) generated an error map of the ES and estimated the biases of the SS and the misalignment of the gyros. This paper discusses some of the error sources, and the techniques used to reduce the effects of these errors. The payload carried by the MSTI2 spacecraft is a high fidelity camera, which was aimed at the target using gimballed mirrors. By aiming it at a celestial target, the payload was used as a high-accuracy single-axis attitude reference. This attitude reference was compared to the attitude reference of the ACS sensors, and the errors were attributed to the ACS sensors.

Rygaard, Christopher A.↗
NASA NTRS2000

SeaWiFS Postlaunch Calibration and Validation Analyses

The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the SeaWiFS Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of the reprocessing. Three volumes of the SeaWiFS Postlaunch Technical Report Series (Volumes 9, 10, and 11) are needed to document the improvements implemented since launch. Volume 10 continues the sequential presentation of postlaunch data analysis and algorithm descriptions begun in Volume 9. Chapter 1 of Volume 10 describes an absorbing aerosol index, similar to that produced by the Total Ozone Mapping Spectrometer (TOMS) Project, which is used to flag pixels contaminated by absorbing aerosols, such as, dust and smoke. Chapter 2 discusses the algorithm being used to remove SeaWiFS out-of-band radiance from the water-leaving radiances. Chapter 3 provides an itemization of all significant changes in the processing algorithms for each of the first three reprocessings. Chapter 4 shows the time series of global clear water and deep-water (depths greater than 1,000m) bio-optical and atmospheric properties (normalized water-leaving radiances, chlorophyll, atmospheric optical depth, etc.) based on the eight-day composites as a check on the sensor calibration stability. Chapter 5 examines the variation in the derived products with scan angle using high resolution data around Hawaii to test for residual scan modulation effects and atmospheric correction biases. Chapter 6 provides a methodology for evaluating the atmospheric correction algorithm and atmospheric derived products using ground-based observations. Similarly, Chapter 7 presents match-up comparisons of coincident satellite and in situ data to determine the accuracy of the water-leaving radiances, chlorophyll a, and K(490) products.

Hooker, Stanford B.↗
NASA NTRS2004

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

Amer, Tahani↗
NASA NTRS2010

Shack-Hartmann Phasing of Segmented Telescopes: Systematic Effects from Lenslet Arrays

The segments in the Keck telescopes are routinely phased using a Shack-Hartmann wavefront sensor with sub-apertures that span adjacent segments. However, one potential limitation to the absolute accuracy of this technique is that it relies on a lenslet array (or a single lens plus a prism array) to form the subimages. These optics have the potential to introduce wavefront errors and stray reflections at the subaperture level that will bias the phasing measurement. We present laboratory data to quantify this effect, using measured errors from Keck and two other lenslet arrays. In addition, as part of the design of the Thirty Meter Telescope Alignment and Phasing System we present a preliminary investigation of a lenslet-free approach that relies on Fresnel diffraction to form the subimages at the CCD. Such a technique has several advantages, including the elimination of lenslet aberrations.

segmented mirrors↗
NASA NTRS1998

Polar Hydra Data Analysis

The science activities are: 1) Hydra is still operating successfully on orbit. 2) A large amount of analysis and discovery has occurred with the Hydra ground data processing this past year. 3) Full interdetector calibration has been implemented and documented. This intercalibration was necessitated by the incorrect installation of bias resistors in the pre-acceleration stage to the electron channeltrons. This had the effect of making the counting efficiency for electrons energy dependent as well as channeltron specific. The nature of the error had no impact on the ion detection efficiency since they have a different bias arrangement. This intercalibration is so effective, that the electron and ion moment densities are routinely produced with a level of agreement better than 20%. 4) The data processing routinely removes glint in the sensors and produces public energy time spectrograms on the web overnight. 6) Routine, but more intensive computer processing codes are operational that determine for electrons and ions, the density, the flow vector, the pressure tensor and the heat flux by numerical integration. These codes use the magnetic field to sustain the quality of their output. To gain access to this high quality magnetic field within our data stream we have monitored Russell's web page for zero levels and timing files (since his data acquisition is not telemetry synchronous) and have a local reconstruction of B for our use. We have also detected a routine anomaly in the magnetometer data stream that we have documented to Chris Russell and developed an editing algorithm to intercept these "hits" and remove them from the geophysical analysis.

Scudder, J. D.↗
NASA NTRS2019

Improvements in the Uncertainty Model in the Goddard Institute for Space Studies Surface Temperature (GISTEMP) Analysis

We outline a new and improved uncertainty analysis for the Goddard Institute of Space Studies (GISS) Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses and incorporate independently derived estimates for ocean data processing, station homogenization and other structural biases. The resulting 95% uncertainties are near 0.05° C in the global annual mean for the last 50 years, and increase going back further in time reaching 0.15° C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date), and conclude with 86% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).

Nathan J L Lenssen↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
NASA NTRS2012

Determining Correlation and Coherence Lengths in Turbulent Boundary Layer Flight Data

Wall pressure data acquired during flight tests at several flight conditions are analysed and the correlation and coherence lengths of the data reported. It is found that the correlation and coherence lengths are influenced by the origin of the structure producing the pressure and the frequency bandwidth over which the analyses are performed. It is shown how the frequency bandwidth biases the correlation length and how the convection of the pressure field might reduce the coherence measured between sensors. A convected form of the cross correlation and cross spectrum is introduced to compensate for the effects of convection. Coherence lengths measured in the streamwise direction appear much longer than expected. Coherent structures detected using the convected cross correlation do not exhibit an exponential coherent power decay.

Palumbo, Dan↗
NASA NTRS2012

Can the Lateral Proximity Effect Be Used to Create the Superconducting Transition of a Micron-Sized TES?

Recent measurements of micron-sized Mo/Au bilayer Transition Edge Sensors (TESs) have demonstrated that the TES can behave like an S-S'-S weak link due to the lateral proximity effect from superconducting leads. In this regime the Tc is a function of bias current, and the effective Tc shifts from the bilayer Tc towards the lead Tc. We explore the idea that a micron-sized S-N-S weak link could provide a new method to engineer the TES Tc. This method would be particularly useful when small size requirements for a bilayer TES (such as for a hot-electron microbolometer) lead to undesirable shifts in the bilayer Te. We present measurements of a variety of micron-sized normal Au 'TES' devices with Nb leads. We find no evidence of a superconducting transition in the Au film of these devices, in dramatic contrast to the strong lateral proximity effect seen in micron-sized Mo/Au bilayer devices. The absence of a transition in these devices is also in disagreement with theoretical predictions for S-N-S weak links. We hypothesize that a finite contact resistance between the Nb and Au may be weakening the effect. We conclude that the use of the lateral proximity effect to create a superconducting transition will be difficult given current fabrication procedures.

Barrentine, E. M.↗
NASA NTRS1975

ATS-6 spacecraft - An EMC challenge

A series of analytical, measurement, and experimental EMI tests were performed on ATS-6. The EMC problems encountered included: (1) wiring pickup and reradiation, (2) input rectification and bias offset, (3) harmonics, (4) component degradation, (5) unbalanced shield ground, (6) inadvertent pickup, and (7) electro-explosive devices. The test program consisted of materials evaluation (with regard to shielding effectiveness, cost, weight, etc.), sun sensor RF susceptibility, cable shielding material evaluation, RF integrity of solar panels and power harnesses, anechoic chamber tests, bonding and grounding, and shielding and thermal control.

Kampinsky, A.↗
NASA NTRSDate not supplied

Detecting Hail from Space: Algorithms, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global climatologies of severe hail using several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the late 1980’s using the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We developed a passive-microwave algorithm that corresponds tightly to radar reflectivity and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗
DOE OSTI2024

Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.

25 ENERGY STORAGE↗