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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Experimental measurements of motion cue effects on STOL approach tasks

An experimental program to investigate the effects of motion cues on STOL approach is presented. The simulator used was the Six-Degrees-of-Freedom Motion Simulator (S.01) at Ames Research Center of NASA which has ?2.7 m travel longitudinally and laterally and ?2.5 m travel vertically. Three major experiments, characterized as tracking tasks, were conducted under fixed and moving base conditions: (1) A simulated IFR approach of the Augmentor Wing Jet STOL Research Aircraft (AWJSRA), (2) a simulated VFR task with the same aircraft, and (3) a single-axis task having only linear acceleration as the motion cue. Tracking performance was measured in terms of the variances of several motion variables, pilot vehicle describing functions, and pilot commentary.

Ringland, R. F.↗
NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗
NASA NTRSDate not supplied

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗
NASA NTRS1986

Adaptive filtering of biodynamic stick feedthrough in manipulation tasks on board moving platforms

A novel approach to suppress the effects of biodynamic interference is presented. An adaptive noise canceling technique is employed for substracting the platform motion correlated components from the control stick output. The effects of biodynamic interference and its suppression by adaptive noise cancellation has been evaluated in a series of tracking tasks performed in a moving base simulator. Simulator motions were in pitch, roll and combined pitch and roll. Human operator performance was assessed from the mean square values of the tracking error and the control activity. The tracking error and the total stick output signal were found to increase significantly with motion and to diminish substantially with adaptive noise cancellation, thus providing a considerable improvement in tracking performance under conditions in which platform motion were present. The adaptive filter was found to cause a significant increase in the cross-over frequency and decrease in the phase margin. Moreover, the adaptive filter was found to significantly improve the human operator visual motor response. This improvement is manifested as an increased human operator gain, a smaller time delay and lower pilot workload.

Velger, M.↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
NASA NTRS1982

An estimation of the condensation rates in three severe storm systems from satellite observations of the convective mass flux

A technique was developed for estimating the condensation rates of convective storms using satellite measurements of cirrus anvil expansion rates and radiosonde measurements of environmental water vapor. Three cases of severe convection in Oklahoma were studied and a diagnostic model was developed for integrating radiosonde data with satellite data. Two methods were used to measure the anvil expansion rates - the expansion of isotherm contours on infrared images, and the divergent motions of small brightness anomalies tracked on the visible images. The differences between the two methods were large as the storms developed, but these differences became small in the latter stage of all three storms. A comparison between the three storms indicated that the available moisture in the lowest levels greatly affected the rain rates of the storms. This was evident from both the measured rain rates of the storms and the condensation rates estimated by the model. The possibility of using this diagnostic model for estimating the intensities of convective storms also is discussed.

Mack, R. A.↗
NASA NTRS1985

Results on nucleon life-time from the Kolar gold field experiment

The KGF nucleon decay experiment has been in operation since October 1980 with a 140 ton calorimetric detector at a depth of 2.3 Km underground. The detector comprises 34 layers of proportional counters arranged in an orthogonal geometry with 12 mm thick iron plates in between successive layers. The proportional counters are made up of square (10 x 10 square centimeters) iron plates of wall thickness 2.3 mm. Each of the 1600 counters is instrumented to provide data on ionization, DE/dx and arrival time. The visible energy of a particle is determined to an accuracy of approximately 20% from the ionization and range of its track. The end point ionization of a stopping track provides the direction of motion as well as the nature of the particle (mu/pi,k,p). Decay of mu is recorded with an overall efficiency of only 20% in view of the thickness of 13 g/square centimeters between successive layers.

Krishnaswamy, M. R.↗
NASA NTRS1988

Computation of two-phase shear-layer flow using an Eulerian-Lagrangian analysis

A combined Eulerian-Lagrangian analysis which combines a linearized block implicit Navier-Stokes analysis for the continuous phase with a Lagrangian analysis for the discrete phase has been utilized to simulate a two-phase shear-layer flow in a two-dimensional channel flow configuration. The motion of the particles is tracked in computational coordinate space, resulting in improved computational efficiency, and interphase coupling terms for the Eulerian analysis are computed from the instantaneous distribution of the particles rather than the trajectory information. The use of the implicit Navier-Stokes analysis for the continuous phase has made it possible to efficiently use a highly stretched mesh. A low Reynolds number form of the k-epsilon turbulence model was used with near-wall resolution, thus eliminating the need to use the 'wall-function' approach. The streamwise velocity profiles for the continuous and the discrete phases have been compared with experimental data for two test cases.

Sabnis, Jayant S.↗
NASA NTRS1991

Operation of the University of Hawaii 2.2M telescope on Mauna Kea

NASA's planetary astronomy program provides part of the funding for the 2.2 meter telescope. The parameters for time on the telescope are laid out. A major instrumental highlight has been the commissioning of a 256 x 256 near infrared camera which uses a Rockwell NICMOS-3 array. At the f/10 focus, image scales of 0.37 and 0.75 arcsec/pixel are available. A new, high quantum efficiency Tektronix 1024 x 1024 CCD saw first light on the telescope in 1991, and was available regularly from April 1991. Data from both of these detectors are transmitted directly to the Sun workstation for immediate analysis by the observers. The autoguider software was enhanced to permit guided tracking on objects have nonsideral motions (i.e., solar system objects).

Hall, Donald N. B.↗
NASA NTRS1991

Direct adaptive impedance control of manipulators

An adaptive scheme for controlling the end-effector impedance of robot manipulators is presented. The proposed control system consists of three subsystems: a simple filter which characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller which produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics, and it is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a very general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter.

Colbaugh, R.↗
NASA NTRS2010

Active Debris Removal - A Grand Engineering Challenge for the Twenty-First Century

The collision between Iridium 33 and Cosmos 2251 in 2009 underlined the potential of an ongoing collision cascade effect (the Kessler Syndrome ) in the near-Earth orbital debris environment. A 2006 NASA analysis of the instability of the debris population in the low Earth orbit (LEO, the region below 2000 km altitude) shows that the environment has reached a point where the debris population will continue to increase in the next 200 years, even without any future launches. The increase is driven by fragments generated via collisions among existing objects in LEO. In reality, the situation will be worse than this prediction because satellite launches will continue and unexpected major breakups may continue to occur. Mitigation measures commonly adopted by the international space community (such as the 25-year rule) will help, but will be insufficient to stop the population growth. To better preserve the near-Earth space environment for future generations, active debris removal (ADR) should be considered. The idea of active debris removal is not new. However, due to the monumental technical, resource, operational, legal, and political challenges associated with removing objects from orbit, it has not yet been widely considered feasible. The recent major breakup events and the environment modeling efforts have certainly reignited the interest in using active debris removal to remediate the environment. This trend is further highlighted by the National Space Policy of the United States of America, released by the White House in June 2010, where the President explicitly directs NASA and the Department of Defense to pursue research and development of technology and techniques, to mitigate and remove on-orbit debris, reduce hazards, and increase understanding of the current and future debris environment. A 2009 modeling study by the NASA Orbital Debris Program Office has shown that, in order to maintain the LEO debris population at a constant level for the next 200 years, an active debris removal of about five objects per year is needed. The targets identified for removal are those with the highest mass and collision probability products. Analyses from the study indicate that the majority of those objects are spent upper stages with masses ranging from 1 to more than 8 metric tons, residing in several altitude regions and concentrated in about 10 inclination bands. To remove five of those objects per year in a cost-effective manner truly represents a grand challenge in engineering and technology development. An end-to-end debris removal operation includes, in general terms, launches orbit rendezvous, precision tracking, stabilization (of the tumbling motion), capture, and deorbit of the targets. An ADR system deigned to remove a single object is not very cost-effective. Therefore, the repeatability of the removal system is almost a requirement. Some of the technologies involved in the ADR process do exist, but the difficulty is to make them more cost effective. Other technologies, such as ways to stabilize a massive tumbling upper stage and the capture mechanisms, are new and will require major innovative research and development efforts. This paper summarizes an updated assessment of the environment, including what needs to be done to control the population growth, and outlines the major engineering and technology challenges to carry out active debris removal to preserve the environment.

Liou, Jer-Chyi↗
NASA NTRS2015

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Orbit Determination↗
NASA NTRS2019

Joint 3D-Wind Retrievals with Stereoscopic Views from MODIS and GOES

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectroradiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, o e ring a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Carr, James L.↗
NASA NTRSDate not supplied

Space Launch System Launch Window and Day of Launch Processes

Lunar missions benefit from varying the launch azimuth as a function of launch time to allow longer launch windows with minimum performance impacts. This variable azimuth approach allows the vehicle to track the Moon’s apparent motion due to Earth’s rotation . The Space Launch System (SLS) Block 1 vehicle design requires the mission to launch into an elliptical parking orbit to provide sufficient energy to insert Orion into a trans-lunar trajectory. The primary benefit of varying the launch azimuth, and as a result the parking orbit inclination, allows the SLS Interim Cryogenic Propulsion Stage (ICPS) to perform its Trans-Lunar Injection (TLI) burn closer to perigee and take advantage of performing a burn in a location where the burn will primarily raise apogee.

A. S. Craig↗
NASA NTRSDate not supplied

Space Launch System Launch Windows and Day of Launch Processes

Lunar missions benefit from varying the launch azimuth as a function of launch time to allow longer launch windows with minimum performance impacts. This variable azimuth approach allows the vehicle to track the Moon’s apparent motion due to Earth’s rotation. The Space Launch System (SLS) Block 1 vehicle design requires the mission to launch into an elliptical parking orbit to provide sufficient energy to insert Orion into a Trans-Lunar Injection (TLI) orbit. The primary benefit of varying the launch azimuth, and as a result the achieved orbit inclination, allows the SLS Interim Cryogenic Propulsion Stage (ICPS) to perform its TLI burn closer to perigee and take advantage of performing a burn in a location where the burn will optimally raise apogee.

launch window↗
NASA NTRS2019

Low-Dose Caffeine Administration During Acute Sleep Deprivation Eliminates Visual Motion Processing Impairment, but Does Not Improve Saccadic Rate

Oculomotor tracking performance changes according to time awake. A constant routine (CR) study demonstrated that increasing time awake 1) reduces the precision of visual motion processing, 2) decreases steady-state closed-loop pursuit performance and 3) decreases peak saccadic velocity. We aimed to determine the contribution of homeostatic sleep pressure on these oculometric changes by administering low-dose caffeine over one night of sleep deprivation. Participants completed two weeks of at-home 8.5 hours sleep per day, followed by an approximately 24-hour laboratory CR in semi-recumbent posture under less than 4 lux of light. The visual tracking task was performed every two hours after waking and hourly overnight. Low-dose caffeine of 0.3 milligrams per kilogram was administered hourly during the biological night. Nine participants (5F) completed the study. Caffeine dosing: 1) prevented the impairment of visual motion processing, 2) reduced by approximately half the impairment of closed-loop pursuit performance (gain, minus 0.47 percent per hour, significance of slope change: p (probability) less than 0.006; proportion smooth, minus 0.35 percent per hour, p less than 0.005), and 3) had an insignificant (p less than 0.39) effect on the impairment of saccadic peak velocity (slope, minus 1.13 percent per hour; intercept, minus 0.62 percent per hour). These results suggest that visual motion processing and some proportion of closed-loop pursuit performance are impaired due to homeostatic mechanisms during sleep deprivation.

Sleep↗
NASA NTRSDate not supplied

Oculometric Analysis of Saccadic Compensation for Visual Motion Processing Impairment due to Alcohol and Sleep Disruption

The Visuomotor Control Laboratory at Ames Research Center has developed a 5-minute ocular tracking test that computes 21 largely independent metrics of visuomotor performance, reflecting neural signal processing along a number of distinct pathways through cortex, brainstem, and cerebellum. Human sensorimotor performance is resilient to the challenges and stressors of many operational environments, in part, because overall performance is achieved through multiple parallel systems. Our multidimensional oculometrics allow us to examine impacts on these sub-components separately. To illustrate this, we contrasted the effects of two mild neural stressors, acute sleep-deprivation and low-dose alcohol. We have previously shown that, in both cases, oculometric analysis is a highly sensitive indicator of impairment. Here we quantified not only the observed impact on the performance of one sub-system, smooth pursuit, which uses high-level cortical processing of visual motion to track a moving object, but also the observed (partial) compensation by an evolutionarily older mid-brain and brainstem subsystem, saccades, which generates jumps in eye position to catch up with the target when smooth pursuit is inadequate. Specifically, we examined the dose-response (effect size vs. dose size) of the ground lost (pursuit deficit) and the ground recouped (saccadic compensation) across three separate studies – acute low-dose alcohol administration (16 subjects), acute sleep loss (12 subjects), and acute sleep loss with caffeine intervention (9 subjects). We computed the dose-response slopes using linear regression. The figure below shows that, in the case of acute sleep deprivation, the resulting slopes for ground lost and ground recouped (mean ± SE across subjects) were significantly different (paired t-test, t(11) = 5.17, p < 0.001), indicating poor saccadic compensation. However, when sleep loss was coupled with caffeine ingestion, ground lost was decreased and ground recouped increased such that the slopes were no longer different (t(8) = -0.05, p = 0.965). With alcohol, the two slopes were large albeit not significantly different (t(15) = 0.96, p = 0.351), indicating significant pursuit impairment but effective saccadic compensation. Our findings show that sleep deprivation and alcohol affect oculomotor performance differently. Low-dose alcohol effects appear predominantly cortical, with effective brainstem compensation. Sleep loss and circadian disruption however appears to affect both cortical and brainstem pathways with caffeine providing an effective countermeasure to both effects. Beyond the mere detection of impairment, our oculometric assessment allows us to characterize the nature of the deficit, to provide insight into the neural substrate, and to assess the effectiveness of countermeasures.

pursuit↗