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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

An Evaluation of the Measurement Requirements for an In-Situ Wake Vortex Detection System

Results of a numerical simulation are presented to determine the feasibility of estimating the location and strength of a wake vortex from imperfect in-situ measurements. These estimates could be used to provide information to a pilot on how to avoid a hazardous wake vortex encounter. An iterative algorithm based on the method of secants was used to solve the four simultaneous equations describing the two-dimensional flow field around a pair of parallel counter-rotating vortices of equal and constant strength. The flow field information used by the algorithm could be derived from measurements from flow angle sensors mounted on the wing-tip of the detecting aircraft and an inertial navigation system. The study determined the propagated errors in the estimated location and strength of the vortex which resulted from random errors added to theoretically perfect measurements. The results are summarized in a series of charts and a table which make it possible to estimate these propagated errors for many practical situations. The situations include several generator-detector airplane combinations, different distances between the vortex and the detector airplane, as well as different levels of total measurement error.

Fuhrmann, Henri D.↗
NASA NTRS1998

X-Ray Emission from the Unidentified Gamma Ray Transient GRO J1838-0415 and X-Ray Localization of Gamma-Ray Transients near the Galactic Plane

The investigation was focused on studying the residual X-ray emission from possible counterparts of enigmatic gamma-ray transients near the Galactic plane. These sources (discovered by our group at Columbia) are highly variable gamma-ray sources with no radio-loud spectrally flat blazar in their approx 1 deg. diameter error box. BSAX Narrow Field Instruments pointed the gamma-ray error box of the prominent non-blazar Energetic Gamma Ray Experiment Telescope (EGRET) source GRO 1838-04 twice on April 17, 1997, and on April 20, 1997. Most of the EGRET error box was imaged and several faint X-ray sources were detected. BSAX Wide Field Camera data were also obtained for a variety of sources near the Galactic plane, including GRO J1838-04.

Tavani, Marco↗
NASA NTRS2003

The Burst and Transient Source Experiment(BATSE)Earth Occultation Catalog of Low-Energy Gamma-Ray Sources. Short title: BATSE Earth Occultation Catalog v2.0

The Burst and Transient Source Experiment (BATSE), aboard the Compton Gamma Ray Observatory (CGRO), provided a record of the low-energy gamma-ray sky (approx. 20-1000 keV) between 1991 April and 2000 May (9.1y). BATSE monitored the high energy sky using the Earth occultation technique (EOT) for point sources whose emission extended for times on the order of the CGRO orbital period (approx. 92m) or greater. Using the EOT to extract flux - 2 - information, a catalog of sources using data from the BATSE large area detectors has been prepared. The first part of the catalog consists of results from the all-sky monitoring of 58 sources, mostly Galactic, with intrinsic variability on timescales of hours to years. For these sources, we have included tables of flux and spectral data, and outburst times for transients. Light curves (or flux histories) covering the entire nine mission are being placed on the world wide web. We then performed a deep-sampling of these 58 objects, plus a selection of 121 more objects, combining data from the entire 9.ly BATSE dataset. Source types considered were primarily accreting binaries, but a small number of representative active galaxies, X-ray-emitting stars, and supernova remnants were also included. The sample represents a compilation of sources monitored and/or discovered with BATSE and other high energy instruments between 1991 and 2000, known sources taken from the HEAO 1 A-4 (Levine et al. 1984) and Macomb and Gehrels (1999) catalogs. The deep sample results include definite detections of 82 objects and possible detections of 36 additional objects. The definite detections spanned three classes of sources: accreting black hole and neutron star binaries, active galaxies and supernova remnants. The average fluxes measured for the fourth class, the X-ray emitting stars, were below the confidence limit for definite detection. Flux data for the deep sample are presented in four energy bands: 20-40, 40-70, 70-160, and 160-430 keV. The limiting average flux level (9.1 y) for the sample varies from 3.5 to 20 mCrab (5delta) between 20 and 430 keV, depending on systematic error, which in turn is primarily dependent on the sky location. To strengthen the credibility of detection of weaker sources (approx.5-25 mCrab), we generated Earth occultation images, searched for periodic behavior using FFT and epoch folding methods, and critically evaluated the energy-dependent emission in the four flux bands. The deep sample results are intended for guidance in performing future all-sky surveys or pointed observations in the hard X-ray and low-energy gamma-ray band, as well as more detailed studies with the BATSE EOT.

Harmon, B. A.↗
NASA NTRS2006

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Sun-Mack, Sunny↗
NASA NTRS2007

Density and Cavitating Flow Results from a Full-Scale Optical Multiphase Cryogenic Flowmeter

Liquid propulsion systems are hampered by poor flow measurements. The measurement of flow directly impacts safe motor operations, performance parameters as well as providing feedback from ground testing and developmental work. NASA Marshall Space Flight Center, in an effort to improve propulsion sensor technology, has developed an all optical flow meter that directly measures the density of the fluid. The full-scale sensor was tested in a transient, multiphase liquid nitrogen fluid environment. Comparison with traditional density models shows excellent agreement with fluid density with an error of approximately 0.8%. Further evaluation shows the sensor is able to detect cavitation or bubbles in the flow stream and separate out their resulting effects in fluid density.

Korman, Valentin↗
NASA NTRS2011

Terminal - Tactical Separation Assured Flight Environment (T-TSafe)

The Tactical Separation Assured Flight Environment (TSAFE) has been previously tested as a conflict detection and resolution tool in the en-route phase of flight. Fast time simulations of a terminal version of this tool called Terminal TSAFE (T-TSAFE) have shown promise over the current conflict detection tools. It has shown to have fewer false alerts (as low as 2 per hour) and better prediction to conflict time than Conflict Alert. The tool will be tested in the simulated terminal area of Los Angeles International Airport, in a Human-in-the-loop experiment to identify controller procedures and information requirements. The simulation will include comparisons of T-TSAFE with NASA's version of Conflict Alert. Also, some other variables such as altitude entry by the controller, which improve T-TSAFE's predictions for conflict detection, will be tested. T-TSAFE integrates features of current conflict detection tools such as Automated Terminal Proximity Alert used to alleviate compression errors in the final approach phase. Based on fast-time simulation analysis, the anticipated benefits of T-TSAFE over Conflict Alert include reduced false/missed alerts and increased time to predicted loss of separation. Other metrics that will be used to evaluate the tool's impact on the controller include controller intervention, workload, and situation awareness.

Verma, Savita Arora↗
NASA NTRS2011

Wide-Field Infrared Survey Telescope (WFIRST) Interim Report

The New Worlds, New Horizons (NWNH) in Astronomy and Astrophysics 2010 Decadal Survey prioritized the community consensus for ground-based and space-based observatories. Recognizing that many of the community s key questions could be answered with a wide-field infrared survey telescope in space, and that the decade would be one of budget austerity, WFIRST was top ranked in the large space mission category. In addition to the powerful new science that could be accomplished with a wide-field infrared telescope, the WFIRST mission was determined to be both technologically ready and only a small fraction of the cost of previous flagship missions, such as HST or JWST. In response to the top ranking by the community, NASA formed the WFIRST Science Definition Team (SDT) and Project Office. The SDT was charged with fleshing out the NWNH scientific requirements to a greater level of detail. NWNH evaluated the risk and cost of the JDEM-Omega mission design, as submitted by NASA, and stated that it should serve as the basis for the WFIRST mission. The SDT and Project Office were charged with developing a mission optimized for achieving the science goals laid out by the NWNH re-port. The SDT and Project Office opted to use the JDEM-Omega hardware configuration as an initial start-ing point for the hardware implementation. JDEM-Omega and WFIRST both have an infrared imager with a filter wheel, as well as counter-dispersed moderate resolution spectrometers. The primary advantage of space observations is being above the Earth's atmosphere, which absorbs, scatters, warps and emits light. Observing from above the atmosphere enables WFIRST to obtain precision infrared measurements of the shapes of galaxies for weak lensing, infrared light-curves of supernovae and exoplanet microlensing events with low systematic errors, and infrared measurements of the H hydrogen line to be cleanly detected in the 1<z<2 redshift range important for baryon acoustic oscillation (BAO) dark energy measurements. The Infrared Astronomical Satellite (IRAS), the Cosmic Background Explorer (COBE), Herschel, Spitzer, and Wide-field Infrared Sur-vey Explorer (WISE) are all space missions that have produced stunning new scientific advances by going to space to observe in the infrared. This interim report describes progress as of June 2011 on developing a requirements flowdown and an evaluation of scientific performance. An Interim Design Reference Mission (IDRM) configuration is presented that is based on the specifications of NWNH with some refinements to optimize the design in accordance with the new scientific requirements. Analysis of this WFIRST IDRM concept is in progress to ensure the capability of the observatory is compatible with the science requirements. The SDT and Project will continue to refine the mission concept over the coming year as design, analysis and simulation work are completed, resulting in the SDT s WFIRST Design Reference Mission (DRM) by the end of 2012.

Green, J.↗
NASA NTRS2011

Deformed Shape Calculation of a Full-Scale Wing Using Fiber Optic Strain Data from a Ground Loads Test

A ground loads test of a full-scale wing (175-ft span) was conducted using a fiber optic strain-sensing system to obtain distributed surface strain data. These data were input into previously developed deformed shape equations to calculate the wing s bending and twist deformation. A photogrammetry system measured actual shape deformation. The wing deflections reached 100 percent of the positive design limit load (equivalent to 3 g) and 97 percent of the negative design limit load (equivalent to -1 g). The calculated wing bending results were in excellent agreement with the actual bending; tip deflections were within +/- 2.7 in. (out of 155-in. max deflection) for 91 percent of the load steps. Experimental testing revealed valuable opportunities for improving the deformed shape equations robustness to real world (not perfect) strain data, which previous analytical testing did not detect. These improvements, which include filtering methods developed in this work, minimize errors due to numerical anomalies discovered in the remaining 9 percent of the load steps. As a result, all load steps attained +/- 2.7 in. accuracy. Wing twist results were very sensitive to errors in bending and require further development. A sensitivity analysis and recommendations for fiber implementation practices, along with, effective filtering methods are included

Jutte, Christine V.↗
NASA NTRS2011

A Proposal to Localize Fermi GBM GRBs Through Coordinated Scanning of the GBM Error Circle via Optical Telescopes

We investigate the feasibility of implementing a system that will coordinate ground-based optical telescopes to cover the Fermi GBM Error Circle (EC). The aim of the system is to localize GBM detected GRBs and facilitate multi-wavelength follow-up from space and ground. This system will optimize the observing locations in the GBM EC based on individual telescope location, Field of View (FoV) and sensitivity. The proposed system will coordinate GBM EC scanning by professional as well as amateur astronomers around the world. The results of a Monte Carlo simulation to investigate the feasibility of the project are presented.

Ukwatta, T. N.↗
NASA NTRS2012

Adaptive Trajectory Prediction Algorithm for Climbing Flights

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Seperation Assurance↗
NASA NTRS2013

Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

hydrologic prediction↗
NASA NTRS2019

Robust Positioning in the Presence of Multipath and NLOS GNSS Signals

GNSS signals can be blocked and reflected by nearby objects, such as buildings, walls, and vehicles. They can also be reflected by the ground and by water. These effects are the dominant source of GNSS positioning errors in dense urban environments, though they can have an impact almost anywhere. Non- line-of-sight (NLOS) reception occurs when the direct path from the transmitter to the receiver is blocked and signals are received only via a reflected path. Multipath interference occurs, as the name suggests, when a signal is received via multiple paths. This can be via the direct path and one or more reflected paths, or it can be via multiple reflected paths. As their error characteristics are different, NLOS and multipath interference typically require different mitigation techniques, though some techniques are applicable to both. Antenna design and advanced receiver signal processing techniques can substantially reduce multipath errors. Unless an antenna array is used, NLOS reception has to be detected using the receiver's ranging and carrier-power-to-noise-density ratio (C/N0) measurements and mitigated within the positioning algorithm. Some NLOS mitigation techniques can also be used to combat severe multipath interference. Multipath interference, but not NLOS reception, can also be mitigated by comparing or combining code and carrier measurements, comparing ranging and C/N0 measurements from signals on different frequencies, and analyzing the time evolution of the ranging and C/N0 measurements.

McGraw, Gary A.↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗
NASA NTRS1989

Slot clock recovery in optical PPM communication systems with avalanche photodiode photodetectors

Slot timing recovery in a direct-detection optical PPM communication system can be achieved by processing the photodetector output waveform with a nonlinear device whose output forms the input to a phase-locked loop. The choice of a simple transition detector as the nonlinearity is shown to give satisfactory synchronization performance. The rms phase error of the recovered slot clock and the effect of slot timing jitter on the bit error probability were directly measured. The experimental system consisted of an AlGaAs laser diode (wavelength = 834 nm) and a silicon avalanche photodiode photodetector. The system used Q = 4 PPM signaling and operated at a source data rate of 25 Mbits/s. The mathematical model developed to compute the rms phase error of the recovered clock is shown to be in good agreement with results of actual measurements of phase errors. The use of the recovered slot clock in the receiver resulted in no significant degradation in receiver sensitivity compared to a system with perfect slot timing. The system achieved a bit error probability of 10 to the -6th at a received optical signal energy of 55 detected photons per information bit.

Davidson, Frederic M.↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗
NASA NTRS2020

Alaska Transportation & Infrastructure - Identifying Permafrost Subsidence Using NASA Earth Observations to Pinpoint Road & Infrastructure Vulnerability in Fairbanks, Alaska

A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. UAVSAR and Sentinel-1 seasonal deformation returns produced consistent spatial deformation patterns with residual root mean squared errors of 13 and 21 millimeters, respectively. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution.In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.

Patrick Saylor↗
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↗