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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada

The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.

soil freeze/thaw↗
NASA NTRS2016

Absolute Navigation Performance of the Orion Exploration Fight Test 1

Launched in December 2014 atop a Delta IV Heavy from the Kennedy Space Center, the Orion vehicle's Exploration Flight Test-1 (EFT-1) successfully completed the objective to stress the system by placing the un-crewed vehicle on a high-energy parabolic trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. Unique challenges associated with designing the navigation system for EFT-1 are presented with an emphasis on how redundancy and robustness influenced the architecture. Two Inertial Measurement Units (IMUs), one GPS receiver and three barometric altimeters (BALTs) comprise the navigation sensor suite. The sensor data is multiplexed using conventional integration techniques and the state estimate is refined by the GPS pseudorange and deltarange measurements in an Extended Kalman Filter (EKF) that employs UDU factorization. The performance of the navigation system during flight is presented to substantiate the design.

Zanetti, Renato↗
NASA NTRS2016

Earth Observation System Flight Dynamics System Covariance Realism

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.

A-Train↗
NASA NTRS2016

Warming of the Global Ocean: Spatial Structure and Water-Mass Trends

This study investigates the multidecadal warming and interannual-to-decadal heat content changes in the upper ocean (0-700 m), focusing on vertical and horizontal patterns of variability. These results support a nearly monotonic warming over much of the World Ocean, with a shift toward Southern Hemisphere warming during the well-observed past decade. This is based on objectively analyzed gridded observational datasets and on a modeled state estimate. Besides the surface warming, a warming climate also has a subsurface effect manifesting as a strong deepening of the midthermocline isopycnals, which can be diagnosed directly from hydrographic data. This deepening appears to be a result of heat entering via subduction and spreading laterally from the high-latitude ventilation regions of subtropical mode waters. The basin-average multidecadal warming mainly expands the subtropical mode water volume, with weak changes in the temperature-salinity (u-S) relationship (known as ''spice'' variability). However, the spice contribution to the heat content can be locally large, for example in Southern Hemisphere. Multidecadal isopycnal sinking has been strongest over the southern basins and weaker elsewhere with the exception of the Gulf Stream/North Atlantic Current/subtropical recirculation gyre. At interannual to decadal time scales, wind-driven sinking and shoaling of density surfaces still dominate ocean heat content changes, while the contribution from temperature changes along density surfaces tends to decrease as time scales shorten.

Global Ocean↗
NASA NTRS2016

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from milli-second pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar lightcurve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

PULSAR↗
NASA NTRS2016

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from millisecond pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar light-curve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

x-ray↗
NASA NTRS2017

A Modified Triples Algorithm for Flush Air Data Systems that Allows a Variety of Pressure Port Configurations

Air Data Systems (FADS) are becoming more prevalent on re-entry vehicles, as evi- denced by the Mars Science Laboratory and the Orion Multipurpose Crew Vehicle. A FADS consists of flush-mounted pressure transducers located at various locations on the fore-body of a flight vehicle or the heat shield of a re-entry capsule. A pressure model converts the pressure readings into useful air data quantities. Two algorithms for converting pressure readings to air data have become predominant- the iterative Least Squares State Estimator (LSSE) and the Triples Algorithm. What follows herein is a new algorithm that takes advantage of the best features of both the Triples Algorithm and the LSSE. This approach employs the potential flow model and strategic differencing of the Triples Algorithm to obtain the defective flight angles; however, the requirements on port placement are far less restrictive, allowing for configurations that are considered optimal for a FADS.

Millman, Daniel R.↗
NASA NTRS2017

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗
NASA NTRS2017

New High-Altitude GPS Navigation Results from the Magnetospheric Multiscale Spacecraft and Simulations at Lunar Distances

As reported in a companion work, in its first phase, NASA's 2015 highly elliptic Magnetospheric Multiscale (MMS) mission set a record for the highest altitude operational use of on-board GPS-based navigation, returning state estimates at 12 Earth radii. In early 2017 MMS transitioned to its second phase which doubled the apogee distance to 25 Earth radii, approaching halfway to the Moon. This paper will present results for GPS observability and navigation performance achieved in MMS Phase 2. Additionally, it will provide simulation results predicting the performance of the MMS navigation system applied to a pair of concept missions at Lunar distances. These studies will demonstrate how high-sensitivity GPS (or GNSS) receivers paired with onboard navigation software, as in MMS-Navigation system, can extend the envelope of autonomous onboard GPS navigation far from the Earth.

Winternitz, Luke B.↗
NASA NTRS2019

Predictability of Ocean Heat Content From Electrical Conductance

Ocean heat content (OHC) is a key climate variable that needs to be monitored to know how Earth's energy imbalance is changing, yet observing OHC remains a challenge. The present study examines whether a depth integral of the ocean's electrical conductivity (“conductance”), which may be inferred from both in situ methods and satellite magnetometers over the global ocean, could help monitor OHC. The ocean's electrical conductivity locally depends on temperature, salinity, and pressure, but it is not as well known how the conductance depends on OHC and ocean salt content. By examining the output of an ocean state estimate shown to agree well with observations that have not been assimilated, this study evaluates the fundamental limitations of using perfectly known ocean conductance to predict OHC, rather than the challenges associated with accounting for observational error. It is found that the ocean's conductance and OHC fields are nonlinearly related but nevertheless highly correlated. A statistical framework tends to predict OHC more accurately than ocean salt content from ocean conductance in regions where conductivity is more sensitive to salinity than temperature. The annually (bidecadally) averaged OHC can be predicted from a combination of conductance and depth‐averaged conductivity ocean fields to within nearly 0.1% (1%) error globally and even more accurately in many poorly observed (e.g., ice‐covered) regions. Practical application of this statistical framework to monitor OHC requires examination of the effect of uncertainties in the observed bathymetry and ocean conductance, which vary with application.

Trossman, D. S.↗
NASA NTRS2019

Three CA-Related Covariance Issues and Their Solutions

This presentation addresses three issues that arise in the use of DoD-produced satellite state estimate covariances in the conjunction assessment process: the realism of the provided covariances, how to address correlated error between two satellites' covariance matrices, and how to proceed when a furnished covariance is non-positive-definite. To address the first, DoD has implemented a set of two "consider parameters" with which to alter/expand the covariance to account for atmospheric density forecast error and satellite frontal area uncertainty, the two largest sources of unmodeled position prediction error for LEO orbits; these values are governed by a satellite's orbital parameters and ballistic coefficient histories, as well as the current and predicted space weather situation. This approach substantially improves the realism of the covariance by accounting for expected prediction errors that are not part of the fit process that generates the covariance. The second issue of covariance correlation is a complicated one, but the main shared error source—global atmospheric density error that is common to both satellites can be characterized and, through sensitivity vectors, quantified at the conjunction's time of closest approach and removed from the joint covariance, which is used in the CA probability of collision (Pc) calculation. Finally, while according to the orbit determination theory a non-positive-definite (NPD) covariance is not possible, numerical truncation and covariance interpolation can conspire to produce NPD results, which render the covariance unusable for certain CA risk assessment calculations, such as Monte Carlo Pc determination. Three similar techniques are profiled and the simplest of them recommended as a reasonable remediation technique when NPD covariances are encountered by CA practitioners.

Dynamic Consider Parameter↗
NASA NTRS2020

Toward Coupled Data Assimilation in NASA’s GEOS: Developments in the Ocean Context

The Global Modeling & Assimilation Office (GMAO) at NASA GSFC produces analyses and predictions of the Earth system using various configurations of the Goddard Earth Observing System (GEOS) model and assimilation system. The current sub-seasonal-to-seasonal prediction system (GEOS-S2S) is based on a coupled atmosphere-ocean-land-ice configuration of GEOS which includes the Modular Ocean Model version 5 (MOM5) run at approximately 50-km resolution and a de-coupled OI-based ocean analysis that uses an initialization of MOM5 forced by the MERRA-2 reanalysis. GMAO will soon implement an updated GEOS-S2S system that will run at 25-km resolution and adopt aspects of the hybrid four-dimensional ensemble-variational (H4DEnVar) system already running in the production-version atmospheric analysis system, including a Local Ensemble Transform Kalman Filter (LETKF) to provide initial conditions for the oceanic state. This presentation will focus on developments to sustain the GMAO's systems on longer time horizons, where more radical transformations will be required to adapt to advanced computing environments, higher resolution and more diverse model components, and new observations for the Earth system. Results will describe progress toward a version of the GEOS coupled system that will be based around the Joint Effort for Data assimilation Integration (JEDI) framework being developed within Joint Center for Satellite Data Assimilation (JCSDA) and include an updated ocean model, MOM6. Discussion will focus specifically on the use of a Unified Forward Operator (UFO) for simulating observations and the Object Oriented Prediction System (OOPS) for providing the state estimate. These features are being developed as a multi-agency effort under the auspices of the JCSDA and are being adopted in the GMAO for all its applications of coupled data assimilation including S2S, numerical weather prediction, and reanalysis.

Mahajan, Rahul↗
NASA NTRS2020

Mode-Based Sensing and Actuation Techniques for Multi-Objective Flexible Aircraft Control

Intelligent sensing and actuation designs are explored as a means to improve performance of a gust load alleviation control design for a flexible wing aircraft equipped with wing-shaping control surfaces. The proposed techniques rely on identification of the dominant structural modes during specified flight conditions and uses them as a basis for sensor placement and actuator utilization. Specifically, a strategy for sensor placement is discussed that uses target mode shape capture as a mean to improve state estimation quality. A second strategy that reduces the number of wing-shaping control inputs using mode and objective-based shape functions as virtual input channels is also presented. Both techniques are demonstrated in simulation of a flexible wing transport aircraft utilizing a multi-objective control system designed to suppress flexible motion, minimize gust and maneuver load, and reduce drag.

Hashemi, Kelley E.↗
NASA NTRS2019

Technical Challenges Associated with In-Air Wingtip Docking of Aircraft in Forward Flight

Autonomous in-air wingtip docking of aircraft offers significant opportunity for system level performance gains for numerous aircraft applications. Several of the technical challenges facing wingtip docking of fixed-wing aircraft are addressed in this paper, including: close proximity aerodynamic coupling; mechanisms and operations for robust docking; and relative state estimation methods. A simulation framework considering the aerodynamics, rigid-body dynamics, and vehicle controls is developed and used to perform docking sensitivity studies for a system of two 5.5% scale NASA Generic Transport Model aircraft. Additionally, proof of- concept testing of a candidate docking mechanism designed to move the primary wingtip vortex inboard suggests the viability of such an approach for achieving robust docking.

Quinlan, Jesse R.↗
NASA NTRS2020

Search and Rescue under the Forest Canopy using Multiple UAS

We consider the problem of multi-robot search and rescue under the forest canopy. Forest is a particularly challenging environment for collaborative mapping and exploration, mainly due to the existence of severe perceptual aliasing, which hinders reliable mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) with onboard sensing and autonomy. Each UAV runs a lightweight filtering algorithm for local state estimation, and a dynamic-aware frontier selection algorithm for fast exploration. The essential and computationally intensive task of collaborative simultaneous localization and mapping (CSLAM) is performed at a central ground station. To handle perceptual aliasing, we make use of stable landmarks extracted from trees, which significantly improve precision and recall during place recognition. Furthermore, to recover from incorrect pairwise data associations during loop closure, we propose a novel procedure for global data association based on recently developed techniques on cycle consistent multiway matching. Our algorithm returns a global data association that is guaranteed to be cycle consistent, and is shown to significantly improve precision compared to the input pairwise associations. The overall multi-UAV system is extensively validated during real-world collaborative exploration missions in a forest at NASA Langley Research Center.

Multi-robot systems↗
NASA NTRSDate not supplied

Implementation of Machine Learning Methods for Crater-Based Navigation

Terrain Relative Navigation methods require surface feature detectors to gain information from images used to improve on-board state estimates. This paper presents the development of a crater detection method based on Machine Learning that can extract data from optical images with different crater shapes and sizes, under varying lighting conditions. This work includes an automated capability for generating labeled training data and iterative testing of the neural network-based crater detector. Preliminary results are included to quantify the detector’s accuracy compared to a known crater catalog, given a set of real lunar images from the Lunar Reconnaissance Orbiter.

Sofia G Catalan↗
NASA NTRSDate not supplied

Trajectory Optimization for dynamic tool Systems Swapping

Develop capability to reliably execute a handoff of the grapple tool between two robot arms in difficult environments. Goals for the end of summer include evaluating different approaches to state estimation and determine optimal handoff poses based on a given scene.

Dominic Bisio↗