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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 NTRS2015

50-Year Window to Establish a Space Faring Civilization

Humankind may only have a short window of 50 years to become a space-faring civilization, after which time the opportunity to do so may become too difficult or impractical to pursue. Current policies for space exploration and infrastructure development implicitly assume a gradualistic approach to technology, budgets, and mission execution -- the common thought has been that there will be plenty of time in humankind's future to become a space-based species, and whatever we are unable to accomplish will be borne by the generations that follow. However, considering natural events, available energy, and human tendencies, the timing to make the most effective effort to achieve multi-planet status might be now, before momentum is lost and we become distracted by Peak Oil and changing energy economies -- restarting a space program after such turmoil may be more difficult than would be practical without cheap, storable, high-energy density petroleum. "Space-faring civilization" is defined as an economically profitable space-based economy that demands the presence of humans off-world in order to sustain a high level of prosperity. An initial foothold for a space-based economy that would fit within the 50-year window might include Earth dependence on rare-earth elements or other hard-to-obtain minerals mined from moons or asteroids, or a permanent settlement on another planet. Using published sources, notional mass and energy requirements for a minimal self-sustaining Mars settlement is calculated, and the number of launch vehicles discussed. Setting the launch schedule to match that of current NASA projections, it could take more than 26 years of semi-annual launches to build up such a self-sustaining human settlement -- a cost and commitment that has not been acknowledged nor planned for. Considering the time required to establish a multi-planet species, this paper frames the required window of decision that, if not taken, could condemn the species to Earth subject to whatever natural or human-made calamities that endanger single-planet civilizations.

human exploration↗
NASA NTRS2020

Overview and Initial Results of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Unmanned aerial systems (UAS) and automated terrain analysis for science and navigation are new technologies for planetary exploration. The Mars Helicopter will fly with the Mars2020 rover, the Dragonfly quadcopter will explore Titan, and Soil Properties and Object Classification (SPOC) software will be used for path planning and navigation on the Mars2020 rover. Using an Argo J5 rover instrumented with stereo cameras and Autonomous Soil Assessment System (ASAS) software, and an off the shelf quadcopter, SAND-E tested the use of automated terrain analysis and UAS data for science operations in a Mars-analog environment in Iceland during July of 2019. Scientifically, we sought to determine changes in the physical and chemical properties of sediments along a glacial-fluvial-aeolian transport pathway. Operationally, we tested rover mission-like scenarios that included UAS images and classified terrain images. Here, we present the initial results for both the operations and science elements of the study. Site Selection: A goal of SAND-E is examine sorting and alteration of sediments in fluvial and aeolian environments in both mineral-dominated and glass-dominated basaltic settings. During the first year of the project we focused on a mineral-dominated environment. Selection of the location was based on prior publications that indicated our selected region had a greater abundance of crystalline sediments than other areas fluvial-aeolian settings in Iceland. Other criteria included the presence of both fluvial and aeolian landforms along a transport pathway such that the sediments in transport could be linked to their source rocks. We chose the Skjaldbreidauhraun glacial outwash plain, which sits at the base of Thórisjökull glacier. The site is 30 km north of Thingvellir National Park and ~2 hours from Reykjavik. The outwash plain is fed by two small catchments that drain from the base of the glacier and cut through hyaloclastite and shield volcano bedrock. The drainage progresses from steep alluvial fans near the glacier into a low-sloping fluvial braidplain that becomes confined by the Skjaldbreidur shield volcano and creates a shallow canyon cut into lava bedrock. The fluvial system was a typical braided alluvial environment composed pebble- and cobble-bedded longitudinal bars and sandy channel beds. The river remained active and fluctuated in response to diurnal runoff cycles near the glacier before disappearing into the sandy substrate downstream. The high concentration of suspended sediment in the river was evident by the cloudy water and the silt and clay-sized sediments that draped the channel beds after abandonment and created playas in the lowest sloping areas of the catchment. The entire fluvial system was affected by the winds generated by frontal systems and katabatic flows descending the glacier. This resulted in the formation of aeolian lag deposits and a wind-deflation plain where the fluvial system was not active. Wind ripples and drifts formed in abandoned fluvial channels from aeolian reworking of the sand-sized fluvial sediments. The silt- and clay-sized sediments found in fluvial channels, bar tops, and playas generated dust plumes during high wind events. Our operation sought to capture the variability in this system by sampling from the range of fluvial and aeolian features 6.3 km (proximal), 11.3 km (medial), and 14.4 km (distal) along the river from its origin at the base of glacier.

Ewing, R. C.↗
NASA NTRSDate not supplied

In-Depth Analysis of Subject Functional Performance and Subjective Feedback Data for Evaluating Argos Simulation Quality

Mechanical offloading systems such as the Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) are used to simulate various partial gravity environments. ARGOS offloads pressurized suited subjects through a gimbaling pivot point system attached to a volumetric Portable Life Support System (PLSS). The pivot point can be configured to multiple locations with respect to the human-suit system center of gravity (CG). Previous work has tested and documented the interaction between different pivot point locations and measured CG. Observations indicated that small changes in pivot point location substantially affect the stability and functional performance (simulation quality) of a subject. This led to the development of a standardized gimbal assessment protocol to assess the functional performance of a pressurized suited subject as a function of the pivot point location, using the data obtained from a variety of planetary suit mobility tasks. As a result, an expansive repository of CG-related task metrics was generated from numerous ARGOS spacesuit test events, for different gimbal configurations and different test subjects. Based on the evaluation metrics and observed trends, several pivot point locations were iteratively identified to determine an “appropriate/optimal” configuration. This study thus describes the in-depth analysis of the CG evaluation metrics to better quantify trends and determine if specific factors are strongly associated with appropriate/optimal configurations. Quantitative and qualitative variables relating to subject task performance, subjective feedback, and anthropometry will be evaluated via probabilistic methods. The results from this study are expected to improve our understanding of optimal ARGOS gimbal settings, which will better inform the gimbal configuration identification process and improve simulation quality for extravehicular activity (EVA) training.

Joseph Yao↗
NASA NTRSDate not supplied

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗
NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗
NASA NTRS2004

The TechSat 21 Autonomous Sciencecraft Experiment

Software has been developed to perform a number of functions essential to autonomous operation in the Autonomous Sciencecraft Experiment (ASE), which is scheduled to be demonstrated aboard a constellation of three spacecraft, denoted TechSat 21, to be launched by the Air Force into orbit around the Earth in January 2006. A prior version of this software was reported in Software for an Autonomous Constellation of Satellites (NPO-30355), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 44. The software includes the following components: Algorithms to analyze image data, generate scientific data products, and detect conditions, features, and events of potential scientific interest; A program that uses component-based computational models of hardware to analyze anomalous situations and to generate novel command sequences, including (when possible) commands to repair components diagnosed as faulty; A robust-execution-management component that uses the Spacecraft Command Language (SCL) software to enable event-driven processing and low-level autonomy; and The Continuous Activity Scheduling, Planning, Execution, and Replanning (CASPER) program for replanning activities, including downlink sessions, on the basis of scientific observations performed during previous orbit cycles.

Sherwood, Robert↗
NASA NTRS1986

Heat flow and heat generation in greenstone belts

Heat flow has been measured in Precambrian shields in both greenstone belts and crystalline terrains. Values are generally low, reflecting the great age and tectonic stability of the shields; they range typically between 30 and 50 mW/sq m, although extreme values of 18 and 79 mW/sq m have been reported. For large areas of the Earth's surface that are assumed to have been subjected to a common thermotectonic event, plots of heat flow against heat generation appear to be linear, although there may be considerable scatter in the data. The relationship is expressed as: Q = Q sub o + D A sub o in which Q is the observed heat flow, A sub o is the measured heat generation at the surface, Q sub o is the reduced heat flow from the lower crust and mantle, and D, which has the dimension of length, represents a scale depth for the distribution of radiogenic elements. Most authors have not used data from greenstone belts in attempting to define the relationship within shields, considering them unrepresentative and preferring to use data from relatively homogeneous crystalline rocks. A discussion follows.

Drury, M. J.↗
NASA NTRS2018

Forming Perchlorates on Mars Through Plasma Chemistry During Dust Events

We report experimental evidences to support a new formation mechanism, multiphase redox plasma chemistry, for perchlorate on Mars observed during the Phoenix mission, whose high concentrations and high ClO4/Cl ratio cannot be fully interpreted by photochemistry. This chemical reaction occurs between Cl-bearing minerals on the Mars surface and free radicals generated by electrostatic discharge (ESD) during Mars dust events (dust storms, dust devils, and grain saltation). We conducted simulated ESD experiments in a Mars chamber with pure CO2, CO2+H2O(g), and Mars Simulate Gas Mixture at Martian atmospheric pressure. We directly observed (1) the instantaneous generation of atmospheric free radicals CO2+, CO+, OI, HIII, HII, OH, ArI, N2, and N2+in normal glow discharge (NGD), detected by in situ plasma emission spectroscopy, and O3by UV and Mid-IR spectroscopy; (2) the fast transformation of NaCl to NaClO3and NaClO4detected by laser Raman spectroscopy, with oxychlorine enrichment at the sample surfaces confirmed by ion chromatography. Through two sets of experimental comparison, we found that the oxidation power of ESD-electron is three orders of magnitude higher than that of UVC-photon. We scaled our experimental results to the modeled ESD in Mars dust events and Mars surface UV radiation level, and concluded that plasma chemistry occurred during Mars dust events can be an additional important formation mechanism for the large amounts of perchlorates observed during various missions to Mars.

Wu, Zhongchen↗
NASA NTRS2022

Electron Anisotropies in Magnetotail Dipolarization Events

Anisotropic electron distributions can be a major source of free energy for the generation of microinstabilities and waves. Here we investigate specifically anisotropies of the suprathermal electrons associated with dipolarization events in the geomagnetic tail. The investigation is based on an MHD simulation of magnetotail reconnection, flow bursts and dipolarization. This simulation is used to trace test particles in the electromagnetic fields of the MHD simulation and investigate their acceleration and contributions to flux increases. The simulated velocity distributions yield anisotropies which can be dominantly parallel (“cigar”-shaped), perpendicular (“pancake”-shaped) to the magnetic field, or a combination thereof (e.g., “rolling-pin”-shaped), depending on location, relative timing, and energy.

electron anisotropies↗
NASA NTRS2017

Preliminary Results from a Model-Driven Architecture Methodology for Development of an Event-Driven Space Communications Service Concept

NASA's next generation space communications network will involve dynamic and autonomous services analogous to services provided by current terrestrial wireless networks. This architecture concept, known as the Space Mobile Network (SMN), is enabled by several technologies now in development. A pillar of the SMN architecture is the establishment and utilization of a continuous bidirectional control plane space link channel and a new User Initiated Service (UIS) protocol to enable more dynamic and autonomous mission operations concepts, reduced user space communications planning burden, and more efficient and effective provider network resource utilization. This paper provides preliminary results from the application of model driven architecture methodology to develop UIS. Such an approach is necessary to ensure systematic investigation of several open questions concerning the efficiency, robustness, interoperability, scalability and security of the control plane space link and UIS protocol.

Roberts, Christopher J.↗
NASA NTRS2011

Modeling of Coronal Mass Ejections that Caused Particularly Large Geomagnetic Storms Using ENLIL Heliosphere Cone Model

In our previous paper we reported the results of modeling of 14 selected well -observed strong halo coronal mass ejection (CME) events using the WSA -ENLIL cone model combination. Cone model input parameters were obtained from white light coronagraph images of the CME events using the analytical method developed by Xie et al. This work verified that coronagraph input gives reasonably good results for the CME arrival time prediction. In contrast to Taktakishvili et al., where we started the analysis by looking for clear CME signatures in the data and then proceeded to model the interplanetary consequences at 1 AU, in the present paper we start by generating a list of observed geomagnetic storm events and then work our way back to remote solar observations and carry out the corresponding CME modeling. The approach used in this study is addressing space weather forecasting and operational needs. We analyzed 36 particularly strong geomagnetic storms, then tried to associate them with particular CMEs using SOHO/LASCO catalogue, and finally modeled these CMEs using WSA-ENLIL cone model. Recently, Pulkkinen et al. developed a novel method for automatic determination of cone model parameters. We employed both analytical and automatic methods to determine cone model input parameters. We examined the CME arrival times and magnitude of impact at 1 AU for both techniques. The results of the simulations are compared with the ACE satellite observations. This comparison demonstrated that WSA -ENLIL model combination with coronagraph input gives reasonably good results for the CME arrival times for this set of 'geoeffective" CME events as well.

Taktakishvili, A.↗
NASA NTRS2007

Next Generation Wiring

Wiring is a major operational component on aerospace hardware that accounts for substantial weight and volumetric space. Over time wire insulation can age and fail, often leading to catastrophic events such as system failure or fire. The next generation of wiring must be reliable and sustainable over long periods of time. These features will be achieved by the development of a wire insulation capable of autonomous self-healing that mitigates failure before it reaches a catastrophic level. In order to develop a self-healing insulation material, three steps must occur. First, methods of bonding similar materials must be developed that are capable of being initiated autonomously. This process will lead to the development of a manual repair system for polyimide wire insulation. Second, ways to initiate these bonding methods that lead to materials that are similar to the primary insulation must be developed. Finally, steps one and two must be integrated to produce a material that has no residues from the process that degrades the insulating properties of the final repaired insulation. The self-healing technology, teamed with the ability to identify and locate damage, will greatly improve reliability and safety of electrical wiring of critical systems. This paper will address these topics, discuss the results of preliminary testing, and remaining development issues related to self-healing wire insulation.

Medelius, Petro↗
NASA NTRS2020

Leveraging Partnerships, Science Content, Special Events, and NASA Assets to Help Girl Scouts Earn Space Science Badges

Throughout 2019, NASA celebrated historic anniversaries and announced bold new programs generating excitement about earth and space exploration. One of the most notable events was the celebration of the 50th anniversary of Apollo 11 historic first steps on the Moon. Complementing this anniversary event were the additional activities and events conducted across the agency that highlighted the many science achievements that were attained across all of NASA’s Science Mission Directorate (SMD) Divisions (earth, planetary, heliophysics, and astrophysics). Further excitement was generated through NASA’s Artemis program which plans to send the first woman and next man to the surface of the Moon. NASA continues to inspire the public including learners of all ages around the world. Building on this momentum, in October 2019, the Astromaterials Research and Exploration Science (ARES) Science Engagement team partnered with the Lunar and Planetary Institute (LPI) and the Girl Scouts of San Jacinto to host an event that enabled Girl Scouts to earn recently released space science badges developed by the Reach for the Stars: NASA Science for Girls Scouts Program. The event celebrated SMD science and highlighted Earth’s Moon and International Observe the Moon Night (InOMN) while facilitating the earning of the NASA inspired space science badges. This event was coordinated and led by the ARES Science Engagement team as part of their collaborative work and involvement in NASA’s SMD Science Activation Program.

Graff, P. V.↗
NASA NTRS2018

The Zwicky Transient Facility: Data Processing, Products, and Archive

The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky at rates of ∼3760 square degrees/hour to median depths of g ~ 20.8 and r ~ 20.6 mag (AB, 5σ in 30 sec). We describe the Science Data System that is housed at IPAC, Caltech. This comprises the data-processing pipelines, alert production system, data archive, and user interfaces for accessing and analyzing the products. The real-time pipeline employs a novel image-differencing algorithm, optimized for the detection of point-source transient events. These events are vetted for reliability using a machine-learned classifier and combined with contextual information to generate data-rich alert packets. The packets become available for distribution typically within 13 minutes (95th percentile) of observation. Detected events are also linked to generate candidate moving-object tracks using a novel algorithm. Objects that move fast enough to streak in the individual exposures are also extracted and vetted. We present some preliminary results of the calibration performance delivered by the real-time pipeline. The reconstructed astrometric accuracy per science image with respect to Gaia DR1 is typically 45 to 85 milliarcsec. This is the RMS per-axis on the sky for sources extracted with photometric S/N ≥10 and hence corresponds to the typical astrometric uncertainty down to this limit. The derived photometric precision (repeatability) at bright unsaturated fluxes varies between 8 and 25 millimag. The high end of these ranges corresponds to an airmass approaching ∼2—the limit of the public survey. Photometric calibration accuracy with respect to Pan-STARRS1 is generally better than 2%. The products support a broad range of scientific applications: fast and young supernovae; rare flux transients; variable stars; eclipsing binaries; variability from active galactic nuclei; counterparts to gravitational wave sources; a more complete census of Type Ia supernovae; and solar-system objects.

Frank J. Masci↗
NASA NTRSDate not supplied

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.

quantum↗
NASA NTRS2003

Genetic control of Drosophila nerve cord development

The Drosophila ventral nerve cord has been a central model system for studying the molecular genetic mechanisms that control CNS development. Studies show that the generation of neural diversity is a multistep process initiated by the patterning and segmentation of the neuroectoderm. These events act together with the process of lateral inhibition to generate precursor cells (neuroblasts) with specific identities, distinguished by the expression of unique combinations of regulatory genes. The expression of these genes in a given neuroblast restricts the fate of its progeny, by activating specific combinations of downstream genes. These genes in turn specify the identity of any given postmitotic cell, which is evident by its cellular morphology and choice of neurotransmitter.

Review↗
NASA NTRS2015

Representing Extremes in Agricultural Models

AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

Agricultural systems↗