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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

End-to-end communication test on variable length packet structures utilizing AOS testbed

This paper describes a communication test, which successfully demonstrated the transfer of losslessly compressed images in an end-to-end system. These compressed images were first formatted into variable length Consultative Committee for Space Data Systems (CCSDS) packets in the Advanced Orbiting System Testbed (AOST). The CCSDS data Structures were transferred from the AOST to the Radio Frequency Simulations Operations Center (RFSOC), via a fiber optic link, where data was then transmitted through the Tracking and Data Relay Satellite System (TDRSS). The received data acquired at the White Sands Complex (WSC) was transferred back to the AOST where the data was captured and decompressed back to the original images. This paper describes the compression algorithm, the AOST configuration, key flight components, data formats, and the communication link characteristics and test results.

Miller, Warner H.↗
NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗
NASA NTRS1994

A new piston control strategy for segmented mirrors

One approach to the adaptive control of large segmented mirrors involves sending tilt commands to each segment and allowing each segment to minimize the distance between its edges and those of (all or some of) its neighbors. This approach has been adopted in the Phased Array Mirror, Extendible Large Aperture (PAMELA) testbed now located at NASA's Marshall Space Flight Center, Huntsville, AL. This approach minimizes (1) the communication between the sensors and the segment actuators and (2) computations required by the central controlling computer. This report discusses issues that large segmented mirrors built around the PAMELA concept (such as SELENE) will face when they migrate to integrated, and presumably to digital, on-segment computational ability and high bandwidth response.

Olivier, Philip D.↗
NASA NTRS1994

Software-Implemented Fault Tolerance in Communications Systems

Software-implemented fault tolerance (SIFT) is used in many computer-based command, control, and communications (C(3)) systems to provide the nearly continuous availability that they require. In the communications subsystem of Space Station Alpha, SIFT algorithms are used to detect and recover from failures in the data and command link between the Station and its ground support. The paper presents a review of these algorithms and discusses how such techniques can be applied to similar systems found in applications such as manufacturing control, military communications, and programmable devices such as pacemakers. With support from the Tracking and Communication Division of NASA's Johnson Space Center, researchers at the University of Wyoming are developing a testbed for evaluating the effectiveness of these algorithms prior to their deployment. This testbed will be capable of simulating a variety of C(3) system failures and recording the response of the Space Station SIFT algorithms to these failures. The design of this testbed and the applicability of the approach in other environments is described.

Gantenbein, Rex E.↗
NASA NTRS1988

Space Station power system autonomy demonstration

The Systems Autonomy Demonstration Program (SADP) represents NASA's major effort to demonstrate, through a series of complex ground experiments, the application and benefits of applying advanced automation technologies to the Space Station project. Lewis Research Center (LeRC) and Marshall Space Flight Center (MSFC) will first jointly develop an autonomous power system using existing Space Station testbed facilities at each center. The subsequent 1990 power-thermal demonstration will then involve the cooperative operation of the LeRC/MSFC power system with the Johnson Space Center (JSC's) thermal control and DMS/OMS testbed facilities. The testbeds and expert systems at each of the NASA centers will be interconnected via communication links. The appropriate knowledge-based technology will be developed for each testbed and applied to problems requiring intersystem cooperation. Primary emphasis will be focused on failure detection and classification, system reconfiguration, planning and scheduling of electrical power resources, and integration of knowledge-based and conventional control system software into the design and operation of Space Station testbeds.

Kish, James A.↗
NASA NTRS2016

Architecture for Cognitive Networking within NASA's Future Space Communications Infrastructure

Future space mission concepts and designs pose many networking challenges for command, telemetry, and science data applications with diverse end-to-end data delivery needs. For future end-to-end architecture designs, a key challenge is meeting expected application quality of service requirements for multiple simultaneous mission data flows with options to use diverse onboard local data buses, commercial ground networks, and multiple satellite relay constellations in LEO, GEO, MEO, or even deep space relay links. Effectively utilizing a complex network topology requires orchestration and direction that spans the many discrete, individually addressable computer systems, which cause them to act in concert to achieve the overall network goals. The system must be intelligent enough to not only function under nominal conditions, but also adapt to unexpected situations, and reorganize or adapt to perform roles not originally intended for the system or explicitly programmed. This paper describes an architecture enabling the development and deployment of cognitive networking capabilities into the envisioned future NASA space communications infrastructure. We begin by discussing the need for increased automation, including inter-system discovery and collaboration. This discussion frames the requirements for an architecture supporting cognitive networking for future missions and relays, including both existing endpoint-based networking models and emerging information-centric models. From this basis, we discuss progress on a proof-of-concept implementation of this architecture, and results of implementation and initial testing of a cognitive networking on-orbit application on the SCaN Testbed attached to the International Space Station.

space networks↗
NASA NTRS1994

Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activiy

This paper describes the Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activity performed by Code 540 in support of the Ecom project. Ecom is the ground-to-ground data transport system for operational EOS traffic. The National Aeronautic and Space Administration (NASA) Communications (Nascom) Division, Code 540, is responsible for implementing Ecom. Ecom interfaces with various systems to transport EOS forward link commands, return link telemetry, and science payload data. To understand the complexities surrounding the design and implementation of Ecom, it is necessary that sufficient testbedding, modeling, and analysis be conducted prior to the design phase. These activities, when grouped, are referred to as the EMAT activity. This paper describes work accomplished to date in each of the three major EMAT activities: modeling, analysis, and testbedding.

Desai, Vishal↗
NASA NTRS1991

Overview of the Telescience Testbed Program

The NASA's Telescience Testbed Program (TTP) conducted by the Ames Research Center is described with particular attention to the objectives, the approach used to achieve these objectives, and the expected benefits of the program. The goal of the TTP is to gain operational experience for the Space Station Freedom and the Earth Observing System programs, using ground testbeds, and to define the information and communication systems requirements for the development and operation of these programs. The results of TTP are expected to include the requirements for the remote coaching, command and control, monitoring and maintenance, payload design, and operations management. In addition, requirements for technologies such as workstations, software, video, automation, data management, and networking will be defined.

Rasmussen, Daryl N.↗
NASA NTRS2010

High-Efficiency K-Band Space Traveling-Wave Tube Amplifier for Near-Earth High Data Rate Communications

The RF performance of a new K-Band helix conduction cooled traveling-wave tube amplifier (TWTA) is presented in this paper. A total of three such units were manufactured, tested and delivered. The first unit is currently flying onboard NASA s Lunar Reconnaissance Orbiter (LRO) spacecraft and has flawlessly completed over 2000 orbits around the Moon. The second unit is a proto-flight model. The third unit will fly onboard NASA s International Space Station (ISS) as a very compact and lightweight transmitter package for the Communications, Navigation and Networking Reconfigurable Testbed (CoNNeCT), which is scheduled for launch in 2011. These TWTAs were characterized over the frequencies 25.5 to 25.8 GHz. The saturated RF output power is >40 W and the saturated RF gain is >46 dB. The saturated AM-to- PM conversion is 3.5 /dB and the small signal gain ripple is 0.46 dB peak-to-peak. The overall efficiency of the TWTA, including that of the electronic power conditioner (EPC) is as high as 45 percent.

Simons, Rainee N.↗
NASA NTRS2010

High-Efficiency K-Band Space Traveling-Wave Tube Amplifier for Near-Earth High Data Rate Communications

The RF performance of a new K-Band helix conduction cooled traveling-wave tube amplifier (TWTA), is presented in this paper. A total of three such units were manufactured, tested and delivered. The first unit is currently flying onboard NASA's Lunar Reconnaissance Orbiter (LRO) spacecraft and has flawlessly completed over 2000 orbits around the Moon. The second unit is a proto-flight model. The third unit will fly onboard NASA's International Space Station (ISS) as a very compact and lightweight transmitter package for the Communications, Navigation and Networking Reconfigurable Testbed (CoNNeCT), which is scheduled for launch in 2011. These TWTAs were characterized over the frequencies 25.5 to 25.8 GHz. The saturated RF output power is greater than 40 W and the saturated RF gain is greater than 46 dB. The saturated AM-to-PM conversion is 3.5 /dB and the small signal gain ripple is 0.46 dB peak-to-peak. The overall efficiency of the TWTA, including that of the electronic power conditioner (EPC) is as high as 45%.

Simons, Rainee N.↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS1999

The SGI/CRAY T3E: Experiences and Insights

The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

Bernard, Lisa Hamet↗
NASA NTRS1989

MIT-KSC space life sciences telescience testbed

A Telescience Life Sciences Testbed is being developed. The first phase of this effort consisted of defining the experiments to be performed, investigating the various possible means of communication between KSC and MIT, and developing software and hardware support. The experiments chosen were two vestibular sled experiments: a study of ocular torsion produced by Y axis linear acceleration, based on the Spacelab D-1 072 Vestibular Experiment performed pre- and post-flight at KSC; and an optokinetic nystagmus (OKN)/linear acceleration interaction experiment. These two experiments were meant to simulate actual experiments that might be performed on the Space Station and to be representative of space life sciences experiments in general in their use of crew time and communications resources.

Source record↗
NASA NTRS2020

Air Traffic Management TestBed Traffic Viewer: Developer's Guide

The Air Traffic Management (ATM) TestBed is a Platform as a Service that is being developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The platform is designed to provide cloud services including back-end, big-data analytics tools, on-demand computing resource management, data storage, and communication middleware. The ATM TestBed reduces the time to test concepts and technologies, supports interactions among various methods such as human-in-the-loop and automation-in-the-loop simulations, and enables collaborative simulations by sharing technologies and tools in the ATM community. The Traffic Viewer application provides a graphical user interface tool for visualizing real and simulated air traffic as well as airspace definition in two-dimensional space. This guide describes a high-level design and implementation of Traffic Viewer and provides information for a new developer or a user to add new capabilities by following the software design and leveraging existing capabilities.

Lai, Chok Fung↗
NASA NTRS1989

Telescience workstation

As part of the Telescience Testbed Pilot Program, the Universities Space Research Association/ Research Institute for Advanced Computer Science (USRA/RIACS) proposed to support remote communication by providing a network of human/machine interfaces, computer resources, and experimental equipment which allows: remote science, collaboration, technical exchange, and multimedia communication. The telescience workstation is intended to provide a local computing environment for telescience. The purpose of the program are as follows: (1) to provide a suitable environment to integrate existing and new software for a telescience workstation; (2) to provide a suitable environment to develop new software in support of telescience activities; (3) to provide an interoperable environment so that a wide variety of workstations may be used in the telescience program; (4) to provide a supportive infrastructure and a common software base; and (5) to advance, apply, and evaluate the telescience technolgy base. A prototype telescience computing environment designed to bring practicing scientists in domains other than their computer science into a modern style of doing their computing was created and deployed. This environment, the Telescience Windowing Environment, Phase 1 (TeleWEn-1), met some, but not all of the goals stated above. The TeleWEn-1 provided a window-based workstation environment and a set of tools for text editing, document preparation, electronic mail, multimedia mail, raster manipulation, and system management.

Brown, Robert L.↗
NASA NTRS2016

Architecture for Cognitive Networking within NASAs Future Space Communications Infrastructure

Future space mission concepts and designs pose many networking challenges for command, telemetry, and science data applications with diverse end-to-end data delivery needs. For future end-to-end architecture designs, a key challenge is meeting expected application quality of service requirements for multiple simultaneous mission data flows with options to use diverse onboard local data buses, commercial ground networks, and multiple satellite relay constellations in LEO, MEO, GEO, or even deep space relay links. Effectively utilizing a complex network topology requires orchestration and direction that spans the many discrete, individually addressable computer systems, which cause them to act in concert to achieve the overall network goals. The system must be intelligent enough to not only function under nominal conditions, but also adapt to unexpected situations, and reorganize or adapt to perform roles not originally intended for the system or explicitly programmed. This paper describes architecture features of cognitive networking within the future NASA space communications infrastructure, and interacting with the legacy systems and infrastructure in the meantime. The paper begins by discussing the need for increased automation, including inter-system collaboration. This discussion motivates the features of an architecture including cognitive networking for future missions and relays, interoperating with both existing endpoint-based networking models and emerging information-centric models. From this basis, we discuss progress on a proof-of-concept implementation of this architecture as a cognitive networking on-orbit application on the SCaN Testbed attached to the International Space Station.

space networks↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗