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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 397 records · Page 22
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NASA NTRSDate not supplied

Interpretable Tree-Based and Graph Neural Network Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Materials discovery↗
NASA NTRS2015

NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications

There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.

Telecommunication↗
NASA NTRS2018

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle S.↗
NASA NTRS2018

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle↗
NASA NTRS1993

Model reduction for the dynamics and control of large structural systems via neutral network processing direct numerical optimization

Three neural network processing approaches in a direct numerical optimization model reduction scheme are proposed and investigated. Large structural systems, such as large space structures, offer new challenges to both structural dynamicists and control engineers. One such challenge is that of dimensionality. Indeed these distributed parameter systems can be modeled either by infinite dimensional mathematical models (typically partial differential equations) or by high dimensional discrete models (typically finite element models) often exhibiting thousands of vibrational modes usually closely spaced and with little, if any, damping. Clearly, some form of model reduction is in order, especially for the control engineer who can actively control but a few of the modes using system identification based on a limited number of sensors. Inasmuch as the amount of 'control spillover' (in which the control inputs excite the neglected dynamics) and/or 'observation spillover' (where neglected dynamics affect system identification) is to a large extent determined by the choice of particular reduced model (RM), the way in which this model reduction is carried out is often critical.

Becus, Georges A.↗
NASA NTRS1993

The MESUR Mission

The MESUR mission will place a network of small, robust landers on the Martian surface, making a coordinated set of observations for at least one Martian year. MESUR presents some major challenges for development of instruments, instrument deployment systems, and on board data processing techniques. The instrument payload has not yet been selected, but the straw man payload is (1) a three-axis seismometer; (2) a meteorology package that senses pressure, temperature, wind speed and direction, humidity, and sky brightness; (3) an alphaproton-X-ray spectrometer (APXS); (4) a thermal analysis/evolved gas analysis (TA/EGA) instrument; (5) a descent imager, (6) a panoramic surface imager; (7) an atmospheric structure instrument (ASI) that senses pressure, temperature, and acceleration during descent to the surface; and (8) radio science. Because of the large number of landers to be sent (about 16), all these instruments must be very lightweight. All but the descent imager and the ASI must survive landing loads that may approach 100 g. The meteorology package, seismometer, and surface imager must be able to survive on the surface for at least one Martian year. The seismometer requires deployment off the lander body. The panoramic imager and some components of the meteorology package require deployment above the lander body. The APXS must be placed directly against one or more rocks near the lander, prompting consideration of a micro rover for deployment of this instrument. The TA/EGA requires a system to acquire, contain, and heat a soil sample. Both the imagers and, especially, the seismometer will be capable of producing large volumes of data, and will require use of sophisticated data compression techniques.

Squyres, S. W.↗
NASA NTRS1995

MSAT PIM and multipactor test program

The MSAT satellite system will provide telephone, fax and low data rate communication services to mobile users throughout North America. The space segment of the MSAT system must supply high radiated power densities on the ground to allow communication with small mobile terminals. Therefore, the high power handling requirement (multipactor, PIM and thermal dissipation) are very important performance parameters for mobile satellite communication systems. Large separate transmit and receive L-Band deployable reflectors are used on MSAT to reduce the risk of PIM (passive intermodulation). In addition, PIM and multipactor avoidance were major design drivers for the L-Band high power transmit output network and antenna. This paper provides an overview of the designs selected and the extensive qualification and verification program undertaken on MSAT to meet the challenging PIM and multipactor requirements. The test campaigns at component, sub-system and system levels and the associated test results are presented. The manufacturing and assembly approaches taken to allow the PIM and Multipactor to be met are also briefly described.

Patenaude, Y.↗
NASA NTRS2004

Impact of CGNS on CFD Workflow

CFD tools are an integral part of industrial and research processes, for which the amount of data is increasing at a high rate. These data are used in a multi-disciplinary fluid dynamics environment, including structural, thermal, chemical or even electrical topics. We show that the data specification is an important challenge that must be tackled to achieve an efficient workflow for use in this environment. We compare the process with other software techniques, such as network or database type, where past experiences showed how difficult it was to bridge the gap between completely general specifications and dedicated specific applications. We show two aspects of the use of CFD General Notation System (CGNS) that impact CFD workflow: as a data specification framework and as a data storage means. Then, we give examples of projects involving CFD workflows where the use of the CGNS standard leads to a useful method either for data specification, exchange, or storage.

Poinot, M.↗
NASA NTRS2017

Earth Science Project Office (ESPO) Field Experiences During ORACLES, ATom, KORUS and POSIDON

Very often, scientific field campaigns entail years of planning and incur substantial cost, especially if they involve the operation of large research aircraft in remote locations. Deploying and operating these aircrafts even for short periods of time poses challenges that, if not addressed properly, can have significant negative consequences and potentially jeopardize the success of a scientific campaign. Challenges vary from country to country and range from safety, health, and security risks to differences in cultural and social norms. Our presentation will focus on sharing experiences on the ESPO 2016 conducted field campaigns ORACLES, ATom, KORUS and POSIDON. We will focus on the best practices, lessons learned, international relations and coordination aspects of the country-specific experiences. This presentation will be part of the ICARE Conference (2nd International Conference on Airborne Research for the Environment (ICARE 2017) that will focus on "Developing the infrastructure to meet future scientific challenges". This unique conference and gathering of facility support experts will not only allow for dissemination and sharing of knowledge but also promote collaboration and networking among groups that support scientific research using airborne platforms around the globe.

Salazar, Vidal↗
NASA NTRS2018

Future of Big Earth Data Analytics

The state of the art of Big Earth Data Analytics can be expected to evolve rapidly in the coming years. The forces driving evolution come from both growth in the data and advancement in the field of data analytics. In the data area, advances in sensor instrumentation and platform miniaturization are increasing both data resolution and coverage, resulting in enormous growth in data Volume. Increases in temporal resolution in particular also generate demands for higher data Velocity. At the same time, the proliferation of instruments and the platforms on which they reside is increasing the Variety of datasets. The Variety increase in turn leads to questions about the Veracity of the data. In the algorithm area, powerful machine learning methods are coming to the fore, particularly Deep Neural Networks. These are powerful at detecting interesting features in the data, integrating many different measurements (i.e., data fusion), and classification problems. However, they are still challenging when seeking explanations of how natural or socio-economic phenomena work using Earth Observations. Thus, classical analysis techniques will remain relevant when the emphasis is on forming or testing explanations, as well as to support interactive data exploration.

Lynnes, Christopher↗
NASA NTRS1995

Searching for patterns in remote sensing image databases using neural networks

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Paola, Justin D.↗
NASA NTRSDate not supplied

Signal and Power Integrity Design Methodology for High-Performance Flight Computing Systems

Computing capabilities of space systems have in-creased onboard performance by orders of magnitude with the use of radiation-tolerant field-programmable gate arrays (FPGA)and processors. The incorporation of signal and power integrity analysis with printed circuit board (PCB) design in reliable computing architectures for space systems has become critical to enable future mission capabilities. Developers launch high-performance processors into a breadth of orbits and missions, running varying applications that create challenges for designing reliable computing hardware. Specifically, for these designs, academic and industry research has focused on component radiation performance, fault mitigation, and reliable architectures. How-ever, other design parameters including electromagnetic interference (EMI), PCB stackup, signal integrity (SI), voltage regulator module (VRM) design, and power distribution network (PDN)are often deprioritized or disregarded as the design matures. Since these characteristics are becoming more significant in high-performance processor designs, this research presents a hardware design and analysis methodology for high-performance, space-computing systems that focuses on a holistic design approach and PDN reliability. While these challenges exist across all space hardware, the reduced PCB dimensions imposed by SmallSats and CubeSats introduce additional hurdles, specifically to VRM and decoupling design. By examining the relationship between the PDN and radiation performance, an analytical relationship is developed that incorporates Total Ionizing Dose and Single-Event Transients to ensure reliability throughout the mission duration. The presented design methodology is applied to the SpaceCube v3.0 Mini, an FPGA-based on-board science data processing system developed at NASA Goddard Space Flight Center.

Advanced avionics↗
NASA NTRS2010

Space Communications and Navigation (SCaN) Integrated Network Architecture Definition Document (ADD): Executive Summary - Volume 1

The SCaN Program has defined an integrated network architecture that fully meets the Administrator s mandate to the Program, and will result in a NASA infrastructure capable of providing the needed and enabling communications services to future space missions. The integrated network architecture will increase SCaN operational efficiency and interoperability through standardization, commonality and technology infusion. It will enable NASA missions requiring advanced communication and tracking capabilities such as: a. Optical communication b. Antenna arraying c. Lunar and Mars Relays d. Integrated network management (service management and network control) and integrated service execution e. Enhanced tracking for navigation f. Space internetworking with DTN and IP g. End-to-end security h. Enhanced security services Moreover, the SCaN Program has created an Integrated Network Roadmap that depicts an orchestrated and coherent evolution path toward the target architecture, encompassing all aspects that concern network assets (i.e., operations and maintenance, sustaining engineering, upgrade efforts, and major development). This roadmap identifies major NASA ADPs, and shows dependencies and drivers among the various planned undertakings and timelines. The roadmap is scalable to accommodate timely adjustments in response to Agency needs, goals, objectives and funding. Future challenges to implementing this architecture include balancing user mission needs, technology development, and the availability of funding within NASA s priorities. Strategies for addressing these challenges are to: define a flexible architecture, update the architecture periodically, use ADPs to evaluate options and determine when to make decisions, and to engage the stakeholders in these evaluations. In addition, the SCaN Program will evaluate and respond to mission need dates for technical and operational capabilities to be provided by the SCaN integrated network. In that regard, the architecture defined in this ADD is scalable to accommodate programmatic and technical changes.

Younes, Badri A.↗
NASA NTRS2002

Computing, Information and Communications Technology (CICT) Website

The Computing, Information and Communications Technology Program (CICT) was established in 2001 to ensure NASA's Continuing leadership in emerging technologies. It is a coordinated, Agency-wide effort to develop and deploy key enabling technologies for a broad range of mission-critical tasks. The NASA CICT program is designed to address Agency-specific computing, information, and communications technology requirements beyond the projected capabilities of commercially available solutions. The areas of technical focus have been chosen for their impact on NASA's missions, their national importance, and the technical challenge they provide to the Program. In order to meet its objectives, the CICT Program is organized into the following four technology focused projects: 1) Computing, Networking and Information Systems (CNIS); 2) Intelligent Systems (IS); 3) Space Communications (SC); 4) Information Technology Strategic Research (ITSR).

Hardman, John↗
NASA NTRS2005

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe↗
NASA NTRS2008

The NASA Real Time Mission Monitor - A Situational Awareness Tool for Conducting Tropical Cyclone Field Experiments

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, aircraft state information, airborne and surface instruments, and weather state data in to a single visualization package for real time field experiment management. RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses (investigated African easterly waves and Tropical Storm Debby and Helene) during August-September 2006 in Cape Verde, the Tropical Composition, Cloud and Climate Coupling experiment during July-August 2007 in Costa Rica, and the Hurricane Aerosonde mission into Hurricane Noel in 2-3 November 2007. The integration and delivery of this information is made possible through data acquisition systems, network communication links, and network server resources built and managed by collaborators at NASA Marshall Space Flight Center (MSFC) and Dryden Flight Research Center (DFRC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols. Each field experiment presents unique challenges and opportunities for advancing the functionality of RTMM. A description of RTMM, the missions it has supported, and its new features that are under development will be presented.

Goodman, Michael↗
NASA NTRS2016

BBN-Based Portfolio Risk Assessment for NASA Technology R&D Outcome

The NASA Aeronautics Research Mission Directorate (ARMD) vision falls into six strategic thrusts that are aimed to support the challenges of the Next Generation Air Transportation System (NextGen). In order to achieve the goals of the ARMD vision, the Airspace Operations and Safety Program (AOSP) is committed to developing and delivering new technologies. To meet the dual challenges of constrained resources and timely technology delivery, program portfolio risk assessment is critical for communication and decision-making. This paper describes how Bayesian Belief Network (BBN) is applied to assess the probability of a technology meeting the expected outcome. The network takes into account the different risk factors of technology development and implementation phases. The use of BBNs allows for all technologies of projects in a program portfolio to be separately examined and compared. In addition, the technology interaction effects are modeled through the application of object-oriented BBNs. The paper discusses the development of simplified project risk BBNs and presents various risk results. The results presented include the probability of project risks not meeting success criteria, the risk drivers under uncertainty via sensitivity analysis, and what-if analysis. Finally, the paper shows how program portfolio risk can be assessed using risk results from BBNs of projects in the portfolio.

Geuther, Steven C.↗
NASA NTRS2017

Aeronautical Situational Awareness - Airport Surface

This paper advocates for a specific design approach, based on simple principals, yet addresses challenges faced by the system engineers when designing complex data and information infrastructure. The document provides guidance for breaking out various work elements in the overall network architecture design, so that communication systems are conceived and effectively realized regardless of their location, size and local specifics. Although targeted at the Global Airspace System (GAS) and National Airspace System (NAS), this framework can be applied to any network-centric architecture.

networking↗