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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Technology Infusion of CodeSonar into the Space Network Ground Segment (RII07): Software Assurance Symposium Technical Summary

Presents a source code analysis tool (CodeSonar) for use in the Space Network Ground Segment. The Space Network requires 99.9% proficiency and 97.0% availability of systems. Software has historically accounted for an annual average of 28% of the Space Network loss of availability and proficiency. CSCI A and CSCI B account for 42% of the previous eight months of software data loss. The technology infusion of CodeSonar into the Space Network Ground segment is meant to aid in determining the impact of the technology on the project both in the expenditure of effort and the technical results of the technology. Running a CodeSonar analysis and performing a preliminary review of the results averaged 3.5 minutes per finding (approximately 20 hours total). An additional 40 hours is estimated to analyze the 37 findings deemed too complex for the initial review. Using CodeSonar's tools to suppress known non-problems, delta tool runs will not repeat findings that have been marked as non-problems, further reducing the time needed for review. The 'non-interesting' finding rate of 70% is a large number, but filtering, search, and detailed contextual features of CodeSonar reduce the time per finding. Integration of the tool into the build process may also provide further savings by preventing developers from having to configure and operate the tool separately. These preliminary results show the tool to be easy to use and incorporate into the engineering process. These findings also provide significant potential improvements in proficiency and availability on the part of the software. As time-to-fix data become available a better cost trade can be made on person hours saved versus tool cost. Selective factors may be necessary to determine where best to apply CodeSonar to balance cost and benefits.

Benson, Markland J.↗
NASA NTRS1984

Satellite Precipitation and Cloud Experiment (SPACE)

An experiment plan was formulated to support an investigation of the precipitation processes associated with mesoscale systems and the interaction of rain producing cloud complexes with the meso and macro-scale environment. The field program necessary to accomplish the scientific goals is designed to incorporate satellite information (VIS and IR as well as VAS data), special radiosonde and surface observing capabilities, radar observations of storms development, special observations from aircraft and ground based lightning measurements. The observing network comprises rawinsonde stations located in northern Alabama and eastern Tennessee. A high density raingauge network and the MSFC lightning location network also cover the area. Coordination with NASA U2 and ER2 aircraft programs and with the operational requirements of the microburst severe thunderstorm program can assure the most efficient utilization of the observing resources.

Arnold, J. E.↗
NASA NTRS2020

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗
NASA NTRS1993

Data communication network at the ASRM facility

The main objective of the report is to present the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi. This report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing critical and manufacturing non-critical. The manufacturing critical buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B 1000. The manufacturing non-critical buildings will be connected by 10BASE-FL to the Business Information System (BIS) in the main computing center. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing critical hub and one of the OIS hubs. The network structure described in this report will be the basis for simulations to be carried out next year. The Comdisco's Block Oriented Network Simulator (BONeS) will be used for the network simulation. The main aim of the simulations will be to evaluate the loading of the OIS, the BIS, the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Moorhead, Robert J., II↗
NASA NTRS2005

Evidence of Urban-Induced Precipitation Variability in Arid Climate Regimes

Water is essential to life in the Earth system. The water cycle components that sustain life are becoming more scarce and polluted. The most recent (1999-2004) drought experienced in the southwestern United States is the seventh worst in the approximately 500-year proxy tree-ring record. As a result, many regions contemplated drought emergencies in which severe water restrictions are implemented. Though larger weather and climate processes likely control drought processes, there is increasing evidence that anthropogenic or human-related activities can significantly alter precipitation processes. Urbanization is an example of anthropogenic forcing. Recent studies continue to provide evidence that urban environments can modify or induce precipitation under a specific set of conditions. Arid and semi-arid regions of the southwestern United States and other parts of the world are rapidly developing and placing greater demands on the environmental system. In the past fifty years, Phoenix has expanded from a predominantly agricultural center to an urbanized region with extent 700 percent larger than its size in the middle of the twentieth century. Riyadh's population grew from about a half million people in 1972 to almost two million by 2000. Saudi Arabia experienced urbanization later than many other countries; in the early 1970s its urban-rural ratio was still about 1:3. By 1990 the ratio had reversed to about 3:l. In the mid-1970s Riyadh's population was increasing by about 10 percent a year. Irrigation also significantly increased between 1972 and 1990 southeast of Riyadh. The study employs a 108-year precipitation historical data record, global climate observing network observations and satellite data to identify possible anomalies in rainfall in and around two major arid urban areas, Phoenix, Arizona and Riyadh, Saudi Arabia. It provides statistically sound evidence that rainfall distribution and magnitude is statistically different in post-urban than in pre-urban (1900-1950) Phoenix. The study hypothesis that a complex interaction between the city landscape, irrigated lands, and nearby mountains have created preferred regions for rainfall development. The study also provides early evidence that rapidly urbanizing parts of the arid Middle East may also be experiencing different precipitation regimes in response to urbanization and irrigation.

Shepherd, J. Marshall↗
NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗
NASA NTRS2000

Data Retrieval Algorithms for Validating the Optical Transient Detector and the Lightning Imaging Sensor

A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions. Solutions for the plane (i.e., no earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated datasets, and the relative influence of bearing and arrival time data an the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA:s Optical Transient Detector and Lightning Imaging Sensor. A quadratic planar solution that is useful when only three arrival time measurements are available is also introduced. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in sc)iirce location, Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated datasets, and the results are generally better than those obtained from the three-station linear planar method when bearing errors are about 2 deg.

Koshak, W. J.↗
NASA NTRS1991

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications.

Katz, Randy H.↗
NASA NTRS2024

High-Rate Delay Tolerant Networking (HDTN) User Guide Version 1.3.0

Delay Tolerant Networking (DTN) has been identified as a key technology to enable and facilitate the development and growth of future space networks. Classically, space communications networks are collections of disparate links that are manually managed either point-to-point or use space relays. The accelerating accessibility of space enables a new scaling of space nodes, yet both the manual management of configurations and scheduling and the lack of structure connecting links precisely prohibit scaling. This challenge gives rise to newer and larger classes of communications needs that are met by DTN, which must overcome the disconnection, disruption, latency, and mobility featured in space communications systems. DTN joins the underlying links as an overlay, and can be made to communicate over any protocol stack. The core actions of DTN are store, carry, and forward, where data are stored instead of dropped if there is no immediately available outduct. It does this by taking the DTN unit of data, bundles, and providing necessary layers to adapt these bundles to the underlying transport protocols of choice; these are called convergence layers. DTN's Bundle Protocol (BP) can then be used on top of terrestrial protocol stacks, such as TCP/IP, as well as protocols for space, such as LTP/AOS, all in the same network. For emphasis it is noted that bundles can be of essentially any size, and hence this convergence to lower layers of choice is necessary. Existing DTN implementations have operated in constrained environments with limited resources, resulting in low data speeds. However, as various technologies have advanced, data transfer rates and efficiency have advanced, which has pushed the need for a DTN implementation for ground systems and for spacecraft that is performance-oriented in order to not impose an unnecessary bottleneck. High-rate Delay Tolerant Networking (HDTN) takes advantage of modern hardware platforms to substantially reduce latency and improve throughput compared to today’s DTN operations. The HDTN implementation maintains interoperability with existing deployments of DTN that conform to IETF RFCs 4838, 5050, and 9171. At the same time, HDTN defines a new data format better suited to higher-rate operation. It defines and adopts a massively parallel pipelined and message-oriented architecture, allowing the system to scale gracefully as its resources increase. HDTN’s architecture also supports hooks to replace various processing pipeline elements with specialized hardware accelerators. This offers improved Size, Weight, and Power (SWaP) characteristics while reducing development complexity and cost.

Delay Tolerant Networking↗
NASA NTRS2002

Internet Data Delivery for Future Space Missions

Ongoing work at National Aeronautics and Space Administration Goddard Space Flight Center (NASA/GSFC), seeks to apply standard Internet applications and protocols to meet the technology challenge of future satellite missions. Internet protocols and technologies are under study as a future means to provide seamless dynamic communication among heterogeneous instruments, spacecraft, ground stations, constellations of spacecraft, and science investigators. The primary objective is to design and demonstrate in the laboratory the automated end-to-end transport of files in a simulated dynamic space environment using off-the-shelf, low-cost, commodity-level standard applications and protocols. The demonstrated functions and capabilities will become increasingly significant in the years to come as both earth and space science missions fly more sensors and as the need increases for more network-oriented mission operations. Another element of increasing significance will be the increased cost effectiveness of designing, building, integrating, and operating instruments and spacecraft that will come to the fore as more missions take up the approach of using commodity-level standard communications technologies. This paper describes how an IP (Internet Protocol)-based communication architecture can support all existing operations concepts and how it will enable some new and complex communication and science concepts. The authors identify specific end-to-end data flows from the instruments to the control centers and scientists, and then describe how each data flow can be supported using standard Internet protocols and applications. The scenarios include normal data downlink and command uplink as well as recovery scenarios for both onboard and ground failures. The scenarios are based on an Earth orbiting spacecraft with downlink data rates from 300 Kbps to 4 Mbps. Included examples are based on designs currently being investigated for potential use by the Global Precipitation Measurement (GPM) mission.

Rash, James↗
NASA NTRS1989

Systems analysis for DSN microwave antenna holography

Proposed systems for Deep Space Network (DSN) microwave antenna holography are analyzed. Microwave holography, as applied to antennas, is a technique which utilizes the Fourier Transform relation between the complex far-field radiation pattern of an antenna and the complex aperture field distribution to provide a methodology for the analysis and evaluation of antenna performance. Resulting aperture phase and amplitude distribution data are used to precisely characterize various crucial performance parameters, including panel alignment, subreflector position, antenna aperture illumination, directivity at various frequencies, and gravity deformation. Microwave holographic analysis provides diagnostic capacity as well as being a powerful tool for evaluating antenna design specifications and their corresponding theoretical models.

Rochblatt, D. J.↗
NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗
NASA NTRS2008

Web-Enabled Optoelectronic Particle-Fallout Monitor

A Web-enabled optoelectronic particle- fallout monitor has been developed as a prototype of future such instruments that (l) would be installed in multiple locations for which assurance of cleanliness is required and (2) could be interrogated and controlled in nearly real time by multiple remote users. Like prior particle-fallout monitors, this instrument provides a measure of particles that accumulate on a surface as an indication of the quantity of airborne particulate contaminants. The design of this instrument reflects requirements to: Reduce the cost and complexity of its optoelectronic sensory subsystem relative to those of prior optoelectronic particle fallout monitors while maintaining or improving capabilities; Use existing network and office computers for distributed display and control; Derive electric power for the instrument from a computer network, a wall outlet, or a battery; Provide for Web-based retrieval and analysis of measurement data and of a file containing such ancillary data as a log of command attempts at remote units; and Use the User Datagram Protocol (UDP) for maximum performance and minimal network overhead.

Lineberger, Lewis P.↗
NASA NTRS2013

Contact Graph Routing Enhancements Developed in ION for DTN

The Interplanetary Overlay Network (ION) software suite is an open-source, flight-ready implementation of networking protocols including the Delay/Disruption Tolerant Networking (DTN) Bundle Protocol (BP), the CCSDS (Consultative Committee for Space Data Systems) File Delivery Protocol (CFDP), and many others including the Contact Graph Routing (CGR) DTN routing system. While DTN offers the capability to tolerate disruption and long signal propagation delays in transmission, without an appropriate routing protocol, no data can be delivered. CGR was built for space exploration networks with scheduled communication opportunities (typically based on trajectories and orbits), represented as a contact graph. Since CGR uses knowledge of future connectivity, the contact graph can grow rather large, and so efficient processing is desired. These enhancements allow CGR to scale to predicted NASA space network complexities and beyond. This software improves upon CGR by adopting an earliest-arrival-time cost metric and using the Dijkstra path selection algorithm. Moving to Dijkstra path selection also enables construction of an earliest- arrival-time tree for multicast routing. The enhancements have been rolled into ION 3.0 available on sourceforge.net.

Segui, John S.↗
NASA NTRS1999

The Unit of Lightning

For the past century, scientists have made quantitative measurements of lightning discharges. In the process, they refined the definition of a lightning unit, or basic quantum of lightning, in order to base it on observable parameters. Although many components of a lightning discharge have been identified, lightning usually occur in groups of discharges or pulses that, although complex, can be organized into units of flashes. This unit definition is based mainly on measurements of lightning from electric field, video, and ground flash lightning locating networks. More recent instrumentation with various combinations of high sensitivity, high temporal, or high spatial resolution often measure signals produced by lightning that do not cleanly divide into flashes. The data from these systems indicate the need or a more fundamental unit for lightning. Such a unit would be of benefit for both basic understanding of lightning and comparing lightning information between instruments. Without a common lightning unit definition, intercomparisons are difficult. For an example, the Lightning Detection And Ranging system (LDAR) at Kennedy Space Center (KSC) have detected ,flash' rates as high as 600 per minute while analysis based on the Advanced Ground Based Field Mill network (AGBFM) detect only 33 "flashes" per minute in the same area and time periods. The satellite based Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) sometimes see single "flashes" that last longer than 10 seconds. Such long duration flashes are not found in electric field records or ground strike location system data sets. The unit of lightning should be based on the fundamental components of the lightning discharge. This should make the unit as generally applicable as possible. For example, studies of NO(x) production by lightning depend on parameters of the individual lightning channels and not the summary flash characteristics. For such studies, the best unit of lightning may be closer to the classical stroke in the electric field data sets, flash in the LDAR data sets, and group in the OTD/LIS data sets. For this type of study, however, more than just the stroke count information is needed. In this paper, we will outline the current definitions of the unit of lightning and propose new basic definitions for the unit of lightning. Since different instruments detect lightning in different ways and different studies may need almost mutually exclusive aspects of the lightning discharge, there may not be a single definition of the unit of lightning that can be applied to all systems and all studies. However, common components can be found since all instrumentation are detecting aspects of the same phenomenon.

Mach, Douglas M.↗
NASA NTRS2013

Towards Efficient Scientific Data Management Using Cloud Storage

A software prototype allows users to backup and restore data to/from both public and private cloud storage such as Amazon's S3 and NASA's Nebula. Unlike other off-the-shelf tools, this software ensures user data security in the cloud (through encryption), and minimizes users operating costs by using space- and bandwidth-efficient compression and incremental backup. Parallel data processing utilities have also been developed by using massively scalable cloud computing in conjunction with cloud storage. One of the innovations in this software is using modified open source components to work with a private cloud like NASA Nebula. Another innovation is porting the complex backup to- cloud software to embedded Linux, running on the home networking devices, in order to benefit more users.

He, Qiming↗
NASA NTRS2023

A Community Convention for Ecological Forecasting: Output Files and Metadata Version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.

Michael C. Dietze↗
NASA NTRS2021

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States

Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.

Elias Ayrey↗