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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Measurements of short-term thermal responses of coniferous forest canopies using thermal scanner data

Thermal Infrared Multispectral Scanner (TIMS) data were collected over a coniferous forest in western Oregon. Concurrent radiosonde measurements of atmospheric profiles of air temperature and moisture provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Surface temperature differences measured by the TIMS over time between flight lines were combined with surface radiative energy balance estimates to develop thermal response numbers (TRN). These numbers characterized the thermal response of the diffent surface types. Barren surfaces had the lowest TRN, whereas the forested surfaces had the highest.

Luvall, J. C.↗
NASA NTRS1991

The use of aircraft-based Thermal Infrared Multispectral Scanner (TIMS) data to measure surface energy budgets on a landscape scale

A series of Thermal Infrared Multispectral Scanner Data (TIMS) was collected over the H. J. Andrews experimental forest in western Oregon and at the Coweeta Hydrologic Laboratory in North Carolina. Flight lines were overlapped with an 8 to 28 minute time difference between flight lines. Concurrent radiosonde measurements of atmospheric profiles of air and dew point temperatures provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Surface temperature differences over time between flight lines allowed the development of thermal response numbers (TRN) which characterized the thermal response of the different surface types. The polygons containing mostly soil and bare rock had the lowest TRN whereas the forested polygons were the highest. Results indicate that forest canopy temperatures measured by the TIMS are comparable to needle thermocouples temperatures. ET models developed from the TIMS data obtained similar ET rates as those using energy balance techniques.

Luvall, Jeffrey C.↗
NASA NTRS1998

Thermal Characteristics of Urban Landscapes

Although satellite data are very useful for analysis of the urban heat island effect at a coarse scale, they do not lend themselves to developing a better understanding of which surfaces across the city contribute or drive the development of the urban heat island effect. Analysis of thermal energy responses for specific or discrete surfaces typical of the urban landscape (e.g., asphalt, building rooftops, vegetation) requires measurements at a very fine spatial scale (i.e., less than 15 m) to adequately resolve these surfaces and their attendant thermal energy regimes. Additionally, very fine scale spatial resolution thermal infrared data, such as that obtained from aircraft, are very useful for demonstrating to planning officials, policy makers, and the general populace the benefits of the urban forest. These benefits include mitigating the urban heat island effect, making cities more aesthetically pleasing and more habitable environments, and aid in overall cooling of the community. High spatial resolution thermal data are required to quantify how artificial surfaces within the city contribute to an increase in urban heating and the benefit of cool surfaces (e.g., surface coatings that reflect much of the incoming solar radiation as opposed to absorbing it thereby lowering urban temperatures). The TRN (thermal response number) is a technique using aircraft remotely sensed surface temperatures to quantify the thermal response of urban surfaces. The TRN was used to quantify the thermal response of various urban surface types ranging from completely vegetated surfaces to asphalt and concrete parking lots for Huntsville, AL.

Luvall, Jeffrey C.↗
NASA NTRS2001

Intracranial distribution of the sympathetic system in mice: DiI tracing and immunocytochemical labeling

The intracranial distribution of the cephalic branches of the superior cervical ganglion (scg) was studied in mice using indocarbocyanine dye (DiI) anterograde tracing. Two main branches were traced from the scg. The first branch joined the nerve of the pterygoid canal (the vidian nerve), npc, from which several intracranial sympathetic branches passed to the branches of the trigeminal nerve (tgn), abducent nerve (abn), trochlear nerve (trn), and oculomotor nerve (ocn). Most of the second branch joined the abn, from which sympathetic fibers dispersed in the distal region of the trigeminal ganglion (tgg) to form a plexus close to the ganglion's branches. Branches from this plexus joined the branches of the tgn, trn, and ocn. Several minor branches arising from the second branch of the scg were also observed. One formed a sympathetic plexus around the internal carotid artery (ica); a second formed a sympathetic plexus in the proximal region of tgg, close to its root; and a third branch coursed laterally to reach the ear by passing along the greater petrosal nerve (gpn). All of the intracranial trajectories traced from scg were found to be catecholaminergic, and likely sympathetic, using tyrosine hydroxylase (TH) immunocytochemistry.

Non-NASA Center↗
NASA NTRS2007

The Use of the Airborne Thermal/Visible Land Application Sensor (ATLAS) to Determine the Thermal Response Numbers for Urban Areas

Although satellite data are very useful for analysis of the urban heat island effect at a coarse scale, they do not lend themselves to developing a better understanding of which surfaces across the city contribute or drive the development of the urban heat island effect. Analysis of thermal energy responses for specific or discrete surfaces typical of the urban landscape (e.g., asphalt, building rooftops, vegetation) requires measurements at a very fine spatial scale (i.e., < 15m) to adequately resolve these surfaces and their attendant thermal energy regimes. Additionally, very fine scale spatial resolution thermal infrared data, such as that obtained from aircraft, are very useful for demonstrating to planning officials, policy makers, and the general populace the benefits of the urban forest. These benefits include mitigating the urban heat island effect, making cities more aesthetically pleasing and more habitable environments, and aid in overall cooling of the community. High spatial resolution thermal data are required to quantify how artificial surfaces within the city contribute to an increase in urban heating and the benefit of cool surfaces (e.g., surface coatings that reflect much of the incoming solar radiation as opposed to absorbing it thereby lowering urban temperatures). The TRN (thermal response number)(Luvall and Holbo 1989) is a technique using aircraft remotely sensed surface temperatures to quantify the thermal response of urban surfaces. The TRN was used to quantify the thermal response of various urban surface types ranging from completely vegetated surfaces to asphalt and concrete parking lots for several cities in the United States.

Luvall, Jeffrey C.↗
NASA NTRS2010

Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids

A spacecraft guidance, navigation, and control (GN&C) system is needed to enable a spacecraft to descend to a surface, take a sample using a touch-and-go (TAG) sampling approach, and then safely ascend. At the time of this reporting, a flyable GN&C system that can accomplish these goals is beyond state of the art. This article describes AutoGNC, which is a GN&C system capable of addressing these goals, which has recently been developed and demonstrated to a maturity TRL-5-plus. The AutoGNC solution matures and integrates two previously existing JPL capabilities into a single unified GN&C system. The two capabilities are AutoNAV and GREX. AutoNAV is JPL s current flight navigation system, and is fairly mature with respect to flybys and rendezvous with small bodies, but is lacking capability for close surface proximity operations, sampling, and contact. G-REX is a suite of low-TRL algorithms and capabilities that enables spacecraft operations in close surface proximity and for performing sampling/contact. The development and integration of AutoNAV and G-REX components into AutoGNC provides a single, unified GN&C capability for addressing the autonomy, close-proximity, and sampling/contact aspects of small-body sample return missions. AutoGNC is an integrated capability comprising elements that were developed separately. The main algorithms and component capabilities that have been matured and integrated are autonomy for near-surface operations, terrain-relative navigation (TRN), real-time image-based feedback guidance and control, and six degrees of freedom (6DOF) control of the TAG sampling event. Autonomy is achieved based on an AutoGNC Executive written in Virtual Machine Language (VML) incorporating high-level control, data management, and fault protection. In descending to the surface, the AutoGNC system uses camera images to determine its position and velocity relative to the terrain. This capability for TRN leverages native capabilities of the original AutoNAV system, but required advancements that integrate the separate capabilities for shape modeling, state estimation, image rendering, defining a database of onboard maps, and performing real-time landmark recognition against the stored maps. The ability to use images to guide the spacecraft requires the capability for image-based feedback control. In Auto- GNC, navigation estimates are fed into an onboard guidance and control system that keeps the spacecraft guided along a desired path, as it descends towards its targeted landing or sampling site. Once near the site, AutoGNC achieves a prescribed guidance condition for TAG sampling (position/orientation, velocity), and a prescribed force profile on the sampling end-effector. A dedicated 6DOF TAG control then implements the ascent burn while recovering from sampling disturbances and induced attitude rates. The control also minimizes structural interactions with flexible solar panels and disallows any part of the spacecraft from making contact with the ground (other than the intended end-effector).

Carson, John M.↗
NASA NTRS2012

Fault Mitigation Schemes for Future Spaceflight Multicore Processors

Future planetary exploration missions demand significant advances in on-board computing capabilities over current avionics architectures based on a single-core processing element. The state-of-the-art multi-core processor provides much promise in meeting such challenges while introducing new fault tolerance problems when applied to space missions. Software-based schemes are being presented in this paper that can achieve system-level fault mitigation beyond that provided by radiation-hard-by-design (RHBD). For mission and time critical applications such as the Terrain Relative Navigation (TRN) for planetary or small body navigation, and landing, a range of fault tolerance methods can be adapted by the application. The software methods being investigated include Error Correction Code (ECC) for data packet routing between cores, virtual network routing, Triple Modular Redundancy (TMR), and Algorithm-Based Fault Tolerance (ABFT). A robust fault tolerance framework that provides fail-operational behavior under hard real-time constraints and graceful degradation will be demonstrated using TRN executing on a commercial Tilera(R) processor with simulated fault injections.

software based↗
NASA NTRS2011

Analysis and Testing of a LIDAR-Based Approach to Terrain Relative Navigation for Precise Lunar Landing

To increase safety and land near pre-deployed resources, future NASA missions to the moon will require precision landing. A LIDAR-based terrain relative navigation (TRN) approach can achieve precision landing under any lighting conditions. This paper presents results from processing flash lidar and laser altimeter field test data that show LIDAR TRN can obtain position estimates less than 90m while automatically detecting and eliminating incorrect measurements using internal metrics on terrain relief and data correlation. Sensitivity studies show that the algorithm has no degradation in matching performance with initial position uncertainties up to 1.6 km

ion propulsion↗
NASA NTRS2010

A New Strategy to Land Precisely on the Northern Plains of Mars

During the Phoenix mission landing site selection process, the Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experiment (HiRISE) images revealed widely spread and dense rock fields in the northern plains. Automatic rock mapping and subsequent statistical analyses showed 30-90% CFA (cumulative fractional area) covered by rocks larger than 1 meter in dense rock fields around craters. Less dense rock fields had 5-30% rock coverage in terrain away from craters. Detectable meter-scale boulders were found nearly everywhere. These rocks present a risk to spacecraft safety during landing. However, they are the most salient topographic features in this region, and can be good landmarks for spacecraft localization during landing. In this paper we present a novel strategy that uses abundance of rocks in northern plains for spacecraft localization. The paper discusses this approach in three sections: a rock-based landmark terrain relative navigation (TRN) algorithm; the TRN algorithm feasibility; and conclusions.

pin point landing↗
NASA NTRS2010

Analysis and Testing of a LIDAR-Based Approach to Terrain Relative Navigation for Precise Lunar Landing

Capability for precise lunar landing is the goal for future NASA missions. A LIDAR-based terrain relative navigation (TRN) approach lets us achieve this goal and also land under any illumination conditions. Results from field test data showed that the LIDAR TRN algorithm obtained position estimates with mean error of about 20 meters and standard deviations of about 10 meters. Moreover, the algorithm was capable of providing 99 percent correct estimates by assessing the local terrain relief in the data. Also, the algorithm was able to handle initial position uncertainty of up to 1.6 kilometers without performance degradation.

laser altimeter↗
NASA NTRS2017

Synopsis of Precision Landing and Hazard Avoidance (PL&HA) Capabilities for Space Exploration

Until recently, robotic exploration missions to the Moon, Mars, and other solar system bodies relied upon controlled blind landings. Because terrestrial techniques for terrain relative navigation (TRN) had not yet been evolved to support space exploration, landing dispersions were driven by the capabilities of inertial navigation systems combined with surface relative altimetry and velocimetry. Lacking tight control over the actual landing location, mission success depended on the statistical vetting of candidate landing areas within the predicted landing dispersion ellipse based on orbital reconnaissance data, combined with the ability of the spacecraft to execute a controlled landing in terms of touchdown attitude, attitude rates, and velocity. In addition, the sensors, algorithms, and processing technologies required to perform autonomous hazard detection and avoidance in real time during the landing sequence were not yet available. Over the past decade, NASA has invested substantial resources on the development, integration, and testing of autonomous precision landing and hazard avoidance (PL&HA) capabilities. In addition to substantially improving landing accuracy and safety, these autonomous PL&HA functions also offer access to targets of interest located within more rugged and hazardous terrain. Optical TRN systems are baselined on upcoming robotic landing missions to the Moon and Mars, and NASA JPL is investigating the development of a comprehensive PL&HA system for a Europa lander. These robotic missions will demonstrate and mature PL&HA technologies that are considered essential for future human exploration missions. PL&HA technologies also have applications to rendezvous and docking/berthing with other spacecraft, as well as proximity navigation, contact, and retrieval missions to smaller bodies with microgravity environments, such as asteroids.

Robertson, Edward A.↗
NASA NTRS2016

COBALT: A GN&C Payload for Testing ALHAT Capabilities in Closed-Loop Terrestrial Rocket Flights

The COBALT (CoOperative Blending of Autonomous Landing Technology) payload is being developed within NASA as a risk reduction activity to mature, integrate and test ALHAT (Autonomous precision Landing and Hazard Avoidance Technology) systems targeted for infusion into near-term robotic and future human space flight missions. The initial COBALT payload instantiation is integrating the third-generation ALHAT Navigation Doppler Lidar (NDL) sensor, for ultra high-precision velocity plus range measurements, with the passive-optical Lander Vision System (LVS) that provides Terrain Relative Navigation (TRN) global-position estimates. The COBALT payload will be integrated onboard a rocket-propulsive terrestrial testbed and will provide precise navigation estimates and guidance planning during two flight test campaigns in 2017 (one open-loop and closed- loop). The NDL is targeting performance capabilities desired for future Mars and Moon Entry, Descent and Landing (EDL). The LVS is already baselined for TRN on the Mars 2020 robotic lander mission. The COBALT platform will provide NASA with a new risk-reduction capability to test integrated EDL Guidance, Navigation and Control (GN&C) components in closed-loop flight demonstrations prior to the actual mission EDL.

Carson, John M., III↗
NASA NTRS2020

EDL Simulation Results for the Mars 2020 Landing Site Safety Assessment

The Mars 2020 rover is NASA’s next flagship mission, set to explore Mars in search of scientific evidence of past microbial life. Importantly, the rover will also, for the first time, have the ability to collect and cache rock and soil samples for retrieval and return to laboratories here on Earth. A key step in the development of the Mars 2020 mission is the selection of a suitable landing site with the largest likelihood of meeting scientific goals. This decision is a complex and critical one that requires close interaction between the scientific and engineering communities. The chosen landing site must be both scientifically interesting — providing the project with the greatest possible chance of gathering credible and defendable scientific evidence — and also safe enough to attempt a landing in the first place. Thus, arguably one of the most important undertakings of the Entry, Descent, and Landing (EDL) team, is to effectively enumerate, quantify, and communicate the landing risks to all of the stakeholders. The culmination of this effort is the Landing Site Safety Assessment, which is a review commissioned by the project, presided over by the EDL Standing Review Board, and attended by management and science stakeholders, in which the EDL team communicates their assessment of the associated landing risks and the statistical probability of a successful landing at each of the final candidate landing sites. This paper summarizes the results of high-fidelity computer simulations of the Mars 2020 EDL sequence used in this assessment. From an EDL performance perspective, all four candidates offer similar level of robustness, which is in-family with Mars Science Laboratory (MSL). However, two new features of the Mars 2020 EDL sequence – range trigger and Terrain-Relative Navigation (TRN) – dramatically enhance the capability of the EDL system to safely land at landing sites with much more rugged terrain than ever before considered. This has allowed the landing site selection for Mars 2020 to proceed in a manner that has been unprecedentedly weighted more heavily toward scientific interest and less heavily on engineering constraints. With TRN, the overall probability of success is predicted to be approximately 99% for all of the candidates.

David Way↗
NASA NTRSDate not supplied

OASSIS: Onboard Adaptive Safe-site Identification System Y3

The OASSIS Year 3 project continues to innovate with three goals: 1) transition to a generic configuration compatible with GNC flight software, 2) implement a new, computationally-efficient TRN algorithm for lunar landing, and 3) integrate with the a HWIL testbed to validate lunar landing GNC systems. This project enables lunar lander GNC flight software to be tested dynamically without the need of a costly flight campaign and without the risk of catastrophic hardware loss. Additionally, the TRN algorithm development and testing enhances the state-of-the-art in pinpoint landing navigation, ultimately improving the overall landing accuracy, safety, and reliability of a crewed lunar landing mission.

James S Mccabe↗
NASA NTRSDate not supplied

Building Maps for Terrain Relative Navigation Using Blender: An Open-Source Approach

A persistent challenge for vision-based navigation systems that compare imagery to a reference map is generating high quality maps with similar lighting conditions. Image rendering software can be used to apply variable lighting to reference maps or to generate synthetic imagery for test trajectories. While many image rendering software packages are available, with several developed specifically for spaceflight applications, there are often limitations due to cost, image fidelity, or flexibility. In this paper, we demonstrate the use of an open-source image rendering software, Blender, for use in Terrain Relative Navigation (TRN) applications. A scene in Blender was generated based on elevation data and satellite imagery of the region of West Texas used by Blue Origin for the operation of their New Shepard suborbital rocket. The Blender scene was validated by reproducing imagery collected during a flight of New Shepard in October 2020 and was further used to generate reference maps for use by a TRN algorithm on a subsequent New Shepard flight in August 2021. The work was performed under the NASA Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which is focused on technology advancement for precision landing and hazard avoidance. This work aims to lower the cost of entry and generally promote the adoption and advancement of vision-based navigation technologies.

Kyle W Smith↗
NASA NTRSDate not supplied

Digital Elevation Map Parametric Error Analysis Using Corresponding NAC Images

Future lunar landing systems, particularly those used to land humans on the lunar surface aspart of the ARTEMIS program, will require precision navigation relative to the lunar surface. The most common way to meet these stringent navigation require-ments is through terrain relative navigation (TRN), which localizes a spacecraft by comparing descent im-agery with a predefined map of the surface. The accu-racy achievable using TRN is limited by the accuracy of the reference Digital Elevation Map (DEM). It is therefore critical for future lunar missions that potential errors in DEMs be quantified. This paper describes one of NASA’s current efforts to develop a process for evaluating lunar DEM quality.

Chris R Gnam↗
NASA NTRSDate not supplied

Digital Elevation Map Parametric Error Analysis Pipeline using Corresponding NAC Images

Future lunar landing systems, particularly those used to land humans on the lunar surface as part of the ARTEMIS program, will require precision navigation relative to the lunar surface. The most common way to meet these stringent navigation requirements is through terrain relative navigation (TRN), which localizes a spacecraft by comparing descent imagery with a predefined map of the surface. The accuracy achievable using TRN is limited by the accuracy of the reference Digital Elevation Map (DEM). It is therefore critical for future lunar missions that potential errors in DEMs be quantified. This paper describes one of NASA’s current efforts to develop a process for evaluating lunar DEM quality.

Chris Gnam↗
NASA NTRS2021

Mars 2020 Perseverance Edl Gnc Safe Target Selection Reconstruction

On February 18th, 2021, NASA landed Perseverance on the Jezero crater (on Mars) using a new Terrain Relative Navigation (TRN) capability. TRN is com-prised of a new sensor, the Lander Vision System (LVS), and a new GNC algo-rithm, the Safe Target Selection (STS). LVS localized the descent vehicle with respect to a map. STS selected the safe landing target within a reachable region from the on-board Safe Targets Map (STM). The landing target was then handed to the Mars Science Laboratory (MSL) heritage powered descent GNC system to execute the landing. This paper describes the design and the as-flown performance of the STS algorithm.

Dutta, Soumyo↗