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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Continuous system modeling

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Cellier, Francois E.↗
NASA NTRS1991

VLSI synthesis of digital application specific neural networks

Neural networks tend to fall into two general categories: (1) software simulations, or (2) custom hardware that must be trained. The scope of this project is the merger of these two classifications into a system whereby a software model of a network is trained to perform a specific task and the results used to synthesize a standard cell realization of the network using automated tools.

Beagles, Grant↗
NASA NTRS1994

Exobiology opportunities from Discovery-class missions

Discovery-class missions that are now planned, and those in the concept stage, have the potential to expand our knowledge of the origins and evolution of biogenic compounds, and ultimately, of the origins of life in the solar system. This class of missions, recently developed within NASA's Solar System Exploration Program, is designed to meet important scientific objectives within stringent guidelines--$150 million cap on development cost and a 3-year cap on the development schedule. The Discovery Program will effectively enable "faster, cheaper" missions to explore the inner solar system. The first two missions are Mars Environmental Survey (MESUR) Pathfinder and Near Earth Asteroid Rendezvous (NEAR). MESUR Pathfinder will be the first Discovery mission, with launch planned for November/December 1996. It will be primarily a technical demonstration and validation of the MESUR Program--a network of automated landers to study the internal structure, meteorology, and surface properties of Mars. Besides providing engineering data, Pathfinder will carry atmospheric instrumentation and imaging capabilities, and may deploy a microrover equipped with an alpha proton X-ray spectrometer to determine elemental composition, particularly the lighter elements of exobiological interest. NEAR is expected to be launched in 1998 and to rendezvous with a near-Earth asteroid for up to 1 year. During this time, the spacecraft will assess the asteroid's mass, size, density, map its surface topography and composition, determine its internal properties, and study its interaction with the interplanetary environment. A gamma ray or X-ray spectrometer will be used to determine elemental composition. An imaging spectrograph, with 0.35 to 2.5 micron spectral range, will be used to determine the asteroid's compositional disbribution. Of the 11 Discovery mission concepts that have been designated as warranting further study, several are promising in terms of determining the composition and chemical evolution of organic matter on small planetary bodies. The following mission concepts are of particular interest to the Exobiology Program: Cometary coma chemical composition, comet nucleus tour, near earth asteroid returned sample, small missions to asteroids and comets, and solar wind sample return. The following three Discovery mission concepts that have been targeted for further consideration are relevant to the study of the evolution of biogenic compounds: Comet nucleus penetrator, mainbelt asteroid rendezvous explorer, and the Mars polar Pathfinder.

Meyer, Michael A.↗
NASA NTRS2005

The Hurricane-Flood-Landslide Continuum

In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.

Negri, Andrew J.↗
NASA NTRS1997

Autonomous Rapid Inspection of Aerospace Structures

Aging aircraft structures and composite materials are requiring rapid inspection of large areas. Removal from the aircraft for NDE at an inspection facility is not economical as compared to field inspection. Detection and characterization of defects are labor intensive, time consuming and when the process is manual the result are subjected to human error.

control inspection systems↗
NASA NTRS2010

Web Design for Space Operations: An Overview of the Challenges and New Technologies Used in Developing and Operating Web-Based Applications in Real-Time Operational Support Onboard the International Space Station, in Astronaut Mission Planning and Mission Control Operations

The International Space Station (ISS) Operations Planning Team, Mission Control Centre and Mission Automation Support Network (MAS) have all evolved over the years to use commercial web-based technologies to create a configurable electronic infrastructure to manage the complex network of real-time planning, crew scheduling, resource and activity management as well as onboard document and procedure management required to co-ordinate ISS assembly, daily operations and mission support. While these Web technologies are classified as non-critical in nature, their use is part of an essential backbone of daily operations on the ISS and allows the crew to operate the ISS as a functioning science laboratory. The rapid evolution of the internet from 1998 (when ISS assembly began) to today, along with the nature of continuous manned operations in space, have presented a unique challenge in terms of software engineering and system development. In addition, the use of a wide array of competing internet technologies (including commercial technologies such as .NET and JAVA ) and the special requirements of having to support this network, both nationally among various control centres for International Partners (IPs), as well as onboard the station itself, have created special challenges for the MCC Web Tools Development Team, software engineers and flight controllers, who implement and maintain this system. This paper presents an overview of some of these operational challenges, and the evolving nature of the solutions and the future use of COTS based rich internet technologies in manned space flight operations. In particular this paper will focus on the use of Microsoft.s .NET API to develop Web-Based Operational tools, the use of XML based service oriented architectures (SOA) that needed to be customized to support Mission operations, the maintenance of a Microsoft IIS web server onboard the ISS, The OpsLan, functional-oriented Web Design with AJAX

Khan, Ahmed↗
NASA NTRS2004

NASA Tech Briefs, April 2004

Topics covered include: Analysis of SSEM Sensor Data Using BEAM; Hairlike Percutaneous Photochemical Sensors; Video Guidance Sensors Using Remotely Activated Targets; Simulating Remote Sensing Systems; EHW Approach to Temperature Compensation of Electronics; Polymorphic Electronic Circuits; Micro-Tubular Fuel Cells; Whispering-Gallery-Mode Tunable Narrow-Band-Pass Filter; PVM Wrapper; Simulation of Hyperspectral Images; Algorithm for Controlling a Centrifugal Compressor; Hybrid Inflatable Pressure Vessel; Double-Acting, Locking Carabiners; Position Sensor Integral with a Linear Actuator; Improved Electromagnetic Brake; Flow Straightener for a Rotating-Drum Liquid Separator; Sensory-Feedback Exoskeletal Arm Controller; Active Suppression of Instabilities in Engine Combustors; Fabrication of Robust, Flat, Thinned, UV-Imaging CCDs; Chemical Thinning Process for Fabricating UV-Imaging CCDs; Pseudoslit Spectrometer; Waste-Heat-Driven Cooling Using Complex Compound Sorbents; Improved Refractometer for Measuring Temperatures of Drops; Semiconductor Lasers Containing Quantum Wells in Junctions; Phytoplankton-Fluorescence-Lifetime Vertical Profiler; Hexagonal Pixels and Indexing Scheme for Binary Images; Finding Minimum-Power Broadcast Trees for Wireless Networks; and Automation of Design Engineering Processes.

Source record↗
NASA NTRS2022

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo↗
NASA NTRS2000

Internet Access to Spacecraft

The Operating Missions as Nodes on the Internet (OMNI) project at NASA's Goddard Space flight Center (GSFC), is demonstrating the use of standard Internet protocols for spacecraft communication systems. This year, demonstrations of Internet access to a flying spacecraft have been performed with the UoSAT-12 spacecraft owned and operated by Surrey Satellite Technology Ltd. (SSTL). Previously, demonstrations were performed using a ground satellite simulator and NASA's Tracking and Data Relay Satellite System (TDRSS). These activities are part of NASA's Space Operations Management Office (SOMO) Technology Program, The work is focused on defining the communication architecture for future NASA missions to support both NASA's "faster, better, cheaper" concept and to enable new types of collaborative science. The use of standard Internet communication technology for spacecraft simplifies design, supports initial integration and test across an IP based network, and enables direct communication between scientists and instruments as well as between different spacecraft, The most recent demonstrations consisted of uploading an Internet Protocol (IP) software stack to the UoSAT- 12 spacecraft, simple modifications to the SSTL ground station, and a series of tests to measure performance of various Internet applications. The spacecraft was reconfigured on orbit at very low cost. The total period between concept and the first tests was only 3 months. The tests included basic network connectivity (PING), automated clock synchronization (NTP), and reliable file transfers (FTP). Future tests are planned to include additional protocols such as Mobile IP, e-mail, and virtual private networks (VPN) to enable automated, operational spacecraft communication networks. The work performed and results of the initial phase of tests are summarized in this paper. This work is funded and directed by NASA/GSFC with technical leadership by CSC in arrangement with SSTL, and Vytek Wireless.

Rash, James↗
NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Miller, Jerry↗
NASA NTRS1997

Automated Generation of Tracking Plans for a Network of Communication Antennas

This paper describes the Deep Space Network Antenna Operations Planner (DPLAN), a system for automatically generating antenna tracking plans for an automated set of highly sensitive radio science and telecommunications antennas. DPLAN accepts current equipment configuration information and a set of requested track services and uses a knowledge base of antenna operations procedures to produce a plan of activities to provide the services using the allocated equipment.

Deep↗
NASA NTRS2011

The NASA Fireball Network Database

The NASA Meteoroid Environment Office (MEO) has been operating an automated video fireball network since late-2008. Since that time, over 1,700 multi-station fireballs have been observed. A database containing orbital data and trajectory information on all these events has recently been compiled and is currently being mined for information. Preliminary results are presented here.

Moser, Danielle E.↗
NASA NTRS2018

Automated Pneumothorax Diagnosis using Deep Neural Networks

Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.

US Army collaboration↗
NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Miller, Jerry↗
NASA NTRS1994

Automated mainframe data collection in a network environment

The progress and direction of the computer industry have resulted in widespread use of dissimilar and incompatible mainframe data systems. Data collection from these multiple systems is a labor intensive task. In the past, data collection had been restricted to the efforts of personnel specially trained on each system. Information is one of the most important resources an organizations has. Any improvement in an organization's ability to access and manage that information provides a competitive advantage. This problem of data collection is compounded at NASA sites by multi-center and contractor operations. The Centralized Automated Data Retrieval System (CADRS) is designed to provide a common interface that would permit data access, query, and retrieval from multiple contractor and NASA systems. The methods developed for CADRS have a strong commercial potential in that they would be applicable for any industry that needs inter-department, inter-company, or inter-agency data communications. The widespread use of multi-system data networks, that combine older legacy systems with newer decentralized networks, has made data retrieval a critical problem for information dependent industries. Implementing the technology discussed in this paper would reduce operational expense and improve data collection on these composite data systems.

Gross, David L.↗
NASA NTRS1994

Automated Induction Of Rule-Based Neural Networks

Prototype expert systems implemented in software and are functionally equivalent to neural networks set up automatically and placed into operation within minutes following information-theoretic approach to automated acquisition of knowledge from large example data bases. Approach based largely on use of ITRULE computer program.

Smyth, Padhraic J.↗
NASA NTRS1994

Performance evaluation of the NASA/KSC CAD/CAE and office automation LAN's

This study's objective is the performance evaluation of the existing CAD/CAE (Computer Aided Design/Computer Aided Engineering) network at NASA/KSC. This evaluation also includes a similar study of the Office Automation network, since it is being planned to integrate this network into the CAD/CAE network. The Microsoft mail facility which is presently on the CAD/CAE network was monitored to determine its present usage. This performance evaluation of the various networks will aid the NASA/KSC network managers in planning for the integration of future workload requirements into the CAD/CAE network and determining the effectiveness of the planned FDDI (Fiber Distributed Data Interface) migration.

Zobrist, George W.↗