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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Formation Flying for Satellites and Unmanned Aerial Vehicles

The shrinking size of satellites and unmanned aerial vehicles (UAVs) is enabling lower cost missions. As sensors and electronics continue to downsize, the next step is multiple vehicles providing different perspectives or variations for more precise measurements. While flying a single satellite or UAV autonomously is a challenge, flying multiple vehicles in a precise formation is even more challenging. The goal of this project is to develop a scalable mesh network between vehicles (satellites or UAVs) to share real-time position data and maintain formations autonomously. Newly available low-cost, commercial off-the-shelf credit card size computers will be used as the basis for this network. Mesh networking techniques will be used to provide redundant links and a flexible network. The Small Projects Rapid Integration and Test Environment Lab will be used to simulate formation flying of satellites. UAVs built by the Aero-M team will be used to demonstrate the formation flying in the West Test Area. The ability to test in flight on NASA-owned UAVs allows this technology to achieve a high Technology Readiness Level (TRL) (TRL-4 for satellites and TRL-7 for UAVs). The low cost of small UAVs and the availability of a large test range (West Test Area) dramatically reduces the expense of testing. The end goal is for this technology to be ready to use on any multiple satellite or UAV mission.

Merrill, Garrick↗
NASA NTRS2018

Automatic Speech Recognition for Launch Control Center Communication Using Recurrent Neural Networks with Data Augmentation and Custom Language Model

Transcribing voice communications in NASA’s launch control center is important for information utilization. However, automatic speech recognition in this environment is particularly challenging due to the lack of training data, unfamiliar words in acronyms, multiple different speakers and accents, and conversational characteristics of speaking. We used bidirectional deep recurrent neural networks to train and test speech recognition performance. We showed that data augmentation and custom language models can improve speech recognition accuracy. Transcribing communications from the launch control center will help the machine analyze information and accelerate knowledge generation.

Chow, Edward↗
NASA NTRS2003

An evolving Mars telecommunications network to enable exploration and increase science data return

The coming decade of Mars exploration involves a variety of unique telecommunications challenges. Increasing spatial and spectral resolution of in situ science instruments drive the need for increased bandwidth. At the same time, many innovative and low-cost in situ mission concepts are enabled by energy-efficient relay communications. In response to these needs, the Mars Exploration Program has established a plan for an evolving orbital infrastructure that can provide enhancing and enabling telecommunications services to future Mars missions. We will present the evolving capabilities of this network over the coming decade in terms of specific quantitative metrics such as data volume per sol and required lander energy per Gb of returned data for representative classes of Mars exploration spacecraft.

Mars Telecommunication↗
NASA NTRSDate not supplied

Using AI/ML to Address Satellite Cloud Remote Sensing Challenges

Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.

Benjamin Scarino↗
NASA NTRSDate not supplied

Simulation of the Aerosol Size Distribution Using a Neural Network Surrogate for the Modal Aerosol Module (MAM7)

One objective of atmospheric simulations is to quantify the distribution of aerosols and their properties. Accurate parameterizations of the processes governing aerosol mass, particle number, and particle size distribution are important for predicting the Earth’s net radiative balance and aerosol-cloud interactions. The Modal Aerosol Module (MAM7) is a two-moment aerosol model that simulates mass, number, and size distribution of seven modes comprised of internally mixed aerosol species. The two-moment scheme adds significant computational expense but allows for the prediction of varying particle size distribution relative to the bulk method which predicts only total mass. In this work, we developed a neural network surrogate model for MAM7 (MAMnet) to predict the aerosol number concentration in NASA’s Global Earth Observing System (GEOS) without adding prohibitive computational expense. MAMnet, can be driven by output from a single moment, mass-based, aerosol scheme (Goddard Chemistry Aerosol and Radiation model (GOCART)) or from reanalysis products (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)). MAMnet was trained using number concentrations from a 5-year GEOS/MAM7 simulation at 1-degree horizontal resolution and using the total mass calculated across modes as inputs, as well as temperature and air density. The model architecture for MAMnet was based on AlexNet, the 2012 winner of the ImageNet Large Scale Visual Recognition Challenge. While some modifications were necessary to accommodate our problem, important aspects of the network were preserved. MAMnet was able to reproduce zonal dynamics and spatial distributions of the aerosol number concentration however predictability in the upper troposphere was poor.

Katherine H Breen↗
NASA NTRSDate not supplied

Extending the Life of NASA’s Tracking and Data Relay Satellite (TDRS)-8: TDRS-8 Power Challenges And Planning for End of Mission

The United States National Aeronautics and Space Administration (NASA) Near Space Network’s Space Relay (SR) System provides communication relay services to a number of scientific and manned space missions with its Tracking and Data Relay Satellite (TDRS) constellation. NASA’s eighth Tracking and Data Relay Satellite (TDRS) has been experiencing a decline in the health of its power subsystem, and recent reliability analyses indicate that the end of its mission serving the Space Relay is imminent. Launched in 2000, TDRS-8 is the oldest TDRS built upon a Boeing 601 platform, and as such it is the first TDRS to experience these age-related failures. The most prevalent elements of the power subsystem to decline are the solar array circuitry and the Bus Voltage Limiters (BVLs), which prevent too much power from the solar arrays being transferred to the bus by shunting excess current. This means that while the loss of solar array circuits introduces concerns that the solar arrays will continue providing the spacecraft with enough current to remain power positive, the loss of BVLs introduces a concern that the bus may not be adequately protected from overvoltage events. Spacecraft engineers at the TDRS primary ground terminal, the White Sands Complex (WSC) in Las Cruces, New Mexico, and at NASA's Goddard Space Flight Center (GSFC) have also been working in collaboration with Boeing to develop innovative techniques to extend the serviceable life of TDRS-8.

tdrs↗
NASA NTRS2022

Impacts of Climate Change on Global Food Trade Networks

Countries' reliance on global food trade networks implies that regionally different climate change impacts on crop yields will be transmitted across borders. This redistribution constitutes a significant challenge for climate adaptation planning and may affect how countries engage in cooperative action. This paper investigates the long-term (2070–2099) potential impacts of climate change on global food trade networks of three key crops: wheat, rice and maize. We propose a simple network model to project how climate change impacts on crop yields may be translated into changes in trade. Combining trade and climate impact data, our analysis proceeds in three steps. First, we use network community detection to analyse how the concentration of global production in present-day trade communities may become disrupted with climate change impacts. Second, we study how countries may change their network position following climate change impacts. Third, we study the total climate-induced change in production plus import within trade communities. Results indicate that the stability of food trade network structures compared to today differs between crops, and that countries' maize trade is least stable under climate change impacts. Results also project that threats to global food security may depend on production change in a few major global producers, and whether trade communities can balance production and import loss in some vulnerable countries. Overall, our model contributes a baseline analysis of cross-border climate impacts on food trade networks.

climate change↗
NASA NTRS2011

The NASA Fireball Network All-Sky Cameras

The construction of small, inexpensive all-sky cameras designed specifically for the NASA Fireball Network is described. The use of off-the-shelf electronics, optics, and plumbing materials results in a robust and easy to duplicate design. Engineering challenges such as weather-proofing and thermal control and their mitigation are described. Field-of-view and gain adjustments to assure uniformity across the network will also be detailed.

Suggs, Rob M.↗
NASA NTRS2000

On-Board Fiber-Optic Network Architectures for Radar and Avionics Signal Distribution

Continued progress in both civil and military avionics applications is overstressing the capabilities of existing radio-frequency (RF) communication networks based on coaxial cables on board modem aircrafts. Future avionics systems will require high-bandwidth on- board communication links that are lightweight, immune to electromagnetic interference, and highly reliable. Fiber optic communication technology can meet all these challenges in a cost-effective manner. Recently, digital fiber-optic communication systems, where a fiber-optic network acts like a local area network (LAN) for digital data communications, have become a topic of extensive research and development. Although a fiber-optic system can be designed to transport radio-frequency (RF) signals, the digital fiber-optic systems under development today are not capable of transporting microwave and millimeter-wave RF signals used in radar and avionics systems on board an aircraft. Recent advances in fiber optic technology, especially wavelength division multiplexing (WDM), has opened a number of possibilities for designing on-board fiber optic networks, including all-optical networks for radar and avionics RF signal distribution. In this paper, we investigate a number of different novel approaches for fiber-optic transmission of on-board VHF and UHF RF signals using commercial off-the-shelf (COTS) components. The relative merits and demerits of each architecture are discussed, and the suitability of each architecture for particular applications is pointed out. All-optical approaches show better performance than other traditional approaches in terms of signal-to-noise ratio, power consumption, and weight requirements.

Alam, Mohammad F.↗
NASA NTRS1991

Reliability and availability modeling of coupled communication networks - A simplified modeling approach

The network-complexity of LANs and of LANs that are interconnected by bridges and routers poses a challenging reliability-modeling problem. The present effort toward these problems' solution attempts to simplify them by reducing their number of states through truncation and state merging, as suggested by Shooman and Laemmel (1990). Through the use of state merging, it becomes possible to reduce the Bateman-Cortes 161 state model to a two state model with a closed-form solution. In the case of coupled networks, a technique which allows for problem-decomposition must be used.

Shooman, Martin L.↗
NASA NTRS1994

Scientific analysis of satellite ranging data

A network of satellite laser ranging (SLR) tracking systems with continuously improving accuracies is challenging the modelling capabilities of analysts worldwide. Various data analysis techniques have yielded many advances in the development of orbit, instrument and Earth models. The direct measurement of the distance to the satellite provided by the laser ranges has given us a simple metric which links the results obtained by diverse approaches. Different groups have used SLR data, often in combination with observations from other space geodetic techniques, to improve models of the static geopotential, the solid Earth, ocean tides, and atmospheric drag models for low Earth satellites. Radiation pressure models and other non-conservative forces for satellite orbits above the atmosphere have been developed to exploit the full accuracy of the latest SLR instruments. SLR is the baseline tracking system for the altimeter missions TOPEX/Poseidon, and ERS-1 and will play an important role in providing the reference frame for locating the geocentric position of the ocean surface, in providing an unchanging range standard for altimeter calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. However, even with the many improvements in the models used to support the orbital analysis of laser observations, there remain systematic effects which limit the full exploitation of SLR accuracy today.

Smith, David E.↗
NASA NTRS2001

Achieving the Earth Science Enterprise Vision for the 21st Century: Platform Challenges

The ESE observational architecture of the future vision is dramatically different from that of today. The vision suggests observations from multiple orbits, collaborating space assets, and even seamless integration of space and other assets. Observations from GEO or from Libration points rather than from LEO suggest spacecraft carrying instruments with large deployable apertures. Minimization of launch costs suggests that these large apertures have long life, be extremely mass and volume efficient, and have low life cycle cost. Another significant challenge associated with high latitude orbits is high precision pointing and control. Finally, networks of spacecraft flying in predetermined constellation will be required either to apply complementary assets to an observation or to extend the virtual aperture beyond that attainable with a single spacecraft. These changes dictate development of new technology on several fronts, which are outlined in this paper. A section on high speed communications will outline requirements and approaches now envisioned. Sensorwebs will be developed from the viewpoint of work already begun for both space and for terrestrial networks. Precision guidance, navigation and control will be addressed from the perspective of precision flying for repeat pass interferometry and extreme pointing stability for advanced altimetry. A separate section will address requirements for distributed systems. Large lightweight deployables will be discussed with an emphasis on inflatable technology and its predicted benefits for large aperture instruments. For each technology area listed, current state-of-the-art, technological approaches for future development, and projected levels of performance are outlined.

Lemmerman, Loren↗
NASA NTRS2008

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗
NASA NTRSDate not supplied

Cooperative Clustering Techniques Applied to Contact Graph Routing

Routing in the space internet has to face many unique challenges - from unplanned disconnections and interruptions to predictable intermittent connectivity due to high network mobility and long propagation delays. NASA’s current approach to such routing is Contact Graph Routing (CGR), using a graph formed of prescheduled communication contacts to compute routes through the network. While this approach manages to tackle issues of connectivity and propagation delays, it is a global approach that requires continuous knowledge of the entire network. In a potential future Solar Space Internet (SSI) such an approach on its own cannot scale to large networks with thousands of members. In this presentation we propose clustering as a solution to CGR scalability. Clustering has been used in many networking problems as a way to subdivide the network and allow for localized routing and better scalability. Using techniques from graph theory and game theory, we explore various existing clustering algorithms and adapt them to the Contact Graph Routing setting. Finally, we propose a way to combine multiple algorithms to create a Delay Tolerant Clustering Protocol.

Yael Kirkpatrick↗
NASA NTRS1993

(abstract) Galileo Optical Link Takes a Step Towards Deep-Space Optical Communications

The Galileo Optical Experiment (GOPEX) is the first in a series of JPL optical communications experiments that are planned to 1) demonstrate the application of critical concepts, subsystems, and components to optical communications technology, 2) validate optical communications performance models, and 3) improve the conceptual design of a deep-space and near-Earth optical communications network. Such a network is envisioned to be global in extent, and will require construction of optical stations on several continents. Industry can play a role in the development of this new breaking technology by assisting in addressing some of the current technology challenges.

optical communications experiment space communicat↗
NASA NTRS2011

Intelligent Wireless Sensor Networks for System Health Monitoring

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.

networks↗
NASA NTRS2016

Architecture and CONOPS of Next-Generation Ground Network for Communications and Tracking of Interplanetary SmallSats

As small spacecraft venture out of Earth orbit, they will encounter challenges not experienced or addressed by the numerous low Earth orbit (LEO) CubeSat and Smallsat missions staged to date. The LEO CubeSats typically use low-cost, proven CubeSat radios, antennas, and university ground stations with small apertures. As more ambitious yet cost-constrained space mission concepts to the Moon and beyond are being developed, CubeSats and smallsats have the potential to provide a more affordable platform for exploring deep space and performing the associated science. Some of the challenges that have, so far, slowed the proliferation of small interplanetary spacecraft are those of communications and navigation.

Cheung, Kar-ming↗
NASA NTRS2018

Predicting Rapid Fire Growth (Flashover) Using Generative Adversarial Networks

A flashover occurs when a fire spreads very rapidly through crevices due to intense heat. Flashovers present one of the most frightening and challenging fire phenomena to those who regularly encounter them: firefighters. Firefighters’ safety and lives often depend on their ability to predict flashovers before they occur. Typical pre-flashover fire characteristics include dark smoke, high heat, and rollover (“angel fingers”) and can be quantified by color, size, and shape. Using a color video stream from a firefighter’s body camera, we applied generative adversarial neural networks for image enhancement. The neural networks were trained to enhance very dark fire and smoke patterns in videos and monitor dynamic changes in smoke and fire areas. Preliminary tests with limited flashover training videos showed that we predicted a flashover as early as 55 seconds before it occurred.

Lu, Thomas↗