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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

SSL: A software specification language

SSL (Software Specification Language) is a new formalism for the definition of specifications for software systems. The language provides a linear format for the representation of the information normally displayed in a two-dimensional module inter-dependency diagram. In comparing SSL to FORTRAN or ALGOL, it is found to be largely complementary to the algorithmic (procedural) languages. SSL is capable of representing explicitly module interconnections and global data flow, information which is deeply imbedded in the algorithmic languages. On the other hand, SSL is not designed to depict the control flow within modules. The SSL level of software design explicitly depicts intermodule data flow as a functional specification.

Austin, S. L.↗
NASA NTRS1985

Maintenance of Time and Frequency in the DSN Using the Global Positioning System

The Deep Space Network must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. The DSN has three tracking complexes, located approximately equidistantly around the Earth. Various methods are used to coordinate the clocks among the three complexes. These methods include Loran-C, TV Line 10, very long baseline interferometry (VLBI), and the Global Positioning System (GPS). The GPS is becoming increasingly important because of the accuracy, precision, and rapid availability of the data; GPS receivers have been installed at each of the DSN complexes and are used to obtain daily time offsets between the master clock at each site and UTC(USNO/NBS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN frequency and timing system (DFT). A brief history of the GPS timing receivers in the DSN, a description of the data and information flow, data on the performance of the DSN master clocks and GPS measurement system, and a description of hydrogen maser frequency steering using these data are presented.

Clements, P. A.↗
NASA NTRS1985

The next generation geophysical investigation of the moon

Planetary geophysics has mainly the objective to determine the structure, composition, and state of a given body and the relationship between internal processes and surface tectonic features. The moon represents an obvious initial case for application of geophysical techniques to bodies other than the earth. As a result of the Apollo program and associated scientific investigations, some initial progress was made toward geophysical exploration of the moon. The obtained results are briefly discussed, and some major unresolved issues are pointed out. The present status of lunar geophysical data sets is evaluated, taking into account the issues cited and the extent to which future orbital surveys and surface measurements may resolve the remaining problems. Attention is given to seismic data, electromagnetic sounding data, heat-flow data, gravity/topography data, and paleomagnetic data.

Hood, L. L.↗
NASA NTRS1988

MODIS information, data and control system (MIDACS) level 2 functional requirements

The MODIS Information, Data and Control System (MIDACS) Level 2 Functional Requirements Document establishes the functional requirements for MIDACS and provides a basis for the mutual understanding between the users and the designers of the EosDIS, including the requirements, operating environment, external interfaces, and development plan. In defining the requirements and scope of the system, this document describes how MIDACS will operate as an element of the EOS within the EosDIS environment. This version of the Level 2 Requirements Document follows an earlier release of a preliminary draft version. The sections on functional and performance requirements do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. Indeed, the team members have not yet been selected and the team has not yet been formed; however, it has been possible to identify many relevant requirements based on the present concept of EosDIS and through interviews and meetings with key members of the scientific community. These requirements have been grouped by functional component of the data system, and by function within each component. These requirements have been merged with the complete set of Level 1 and Level 2 context diagrams, data flow diagrams, and data dictionary.

Han, D.↗
NASA NTRS2008

The Solar Dynamics Observatory: Your Eye On The Sun

The Sun hiccups and satellites die. That is what NASA's Living With a Star Program is all about. The Solar Dynamics Observatory (SDO) is the first Space Weather Mission in LWS. SDO's main goal is to understand, driving towards a predictive capability, those solar variations that influence life on Earth and humanity's technological systems. The past decade has seen an increasing emphasis on understanding the entire Sun, from the nuclear reactions at the core to the development and loss of magnetic loops in the corona. SDO's three science investigations (HMI, AIA, and EVE) will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere and geospace as the solar wind, energetic particles, and variations in the solar irradiance. SDO will return full-disk Dopplergrams, full-disk vector magnetograms, full-disk images at nine E/UV wavelengths, and EUV spectral irradiances, all taken at a rapid cadence. This means you can "observe the database" to study events, but we can also move forward in producing quantitative models of what the Sun is doing today. SDO is scheduled to launch in 2008 on an Atlas V rocket from the Kennedy Space Center, Cape Canaveral, Florida. The satellite will fly in a 28 degree inclined geosynchronous orbit about the longitude of New Mexico, where a dedicated Ka-band ground station will receive the 150 Mbps data flow. How SDO data will transform the study of the Sun and its affect on Space Weather studies will be discussed.

Pesnell, William Dean↗
NASA NTRS2008

The Solar Dynamics Observatory

The Solar Dynamics Observatory (SDO) is the first Space Weather Mission in NASA's Living With a Star Program. SDO's main goal is to understand, driving towards a predictive capability, those solar variations that influence life on Earth and humanity's technological systems. The past decade has seen an increasing emphasis on understanding the entire Sun, from the nuclear reactions at the core to the development and loss of magnetic loops in the corona. SDO's three science investigations (HMI, AIA, and EVE) will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere and geospace as the solar wind, energetic particles, and variations in the solar irradiance. SDO will return full-disk Dopplergrams, full-disk vector magnetograms, full-disk images at nine EIUV wavelengths, and EUV spectral irradiances, all taken at a rapid cadence. This means you can 'observe the database' to study events, but we can also move forward in producing quantitative models of what the Sun is doing today. SDO is scheduled to launch in 2008 on an Atlas V rocket from the Kennedy Space Center, Cape Canaveral, Florida. The satellite will fly in a 28 degree inclined geosynchronous orbit about the longitude of New Mexico, where a dedicated Ka-band ground station will receive the 150 Mbps data flow. How SDO data will transform the study of the Sun and its affect on Space Weather studies will be discussed.

Pesnell, William D.↗
NASA NTRS2010

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

NASA's Human Research Program (HRP) and Space Life Sciences Directorate (SLSD), not unlike many NASA organizations today, struggle with the inherent inefficiencies caused by dependencies on heterogeneous data systems and silos of data and information spread across decentralized discipline domains. The capture of operational and research-based data/information (both in-flight and ground-based) in disparate IT systems impedes the extent to which that data/information can be efficiently and securely shared, analyzed, and enriched into knowledge that directly and more rapidly supports HRP's research-focused human system risk mitigation efforts and SLSD s operationally oriented risk management efforts. As a result, an integrated effort is underway to more fully understand and document how specific sets of risk-related data/information are generated and used and in what IT systems that data/information currently resides. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as the data supply chain), HRP and SLSD are building an information architecture plan to leverage their existing, shared IT infrastructure. In addition, it is important to create a centralized structured tool to represent risks including attributes such as likelihood, consequence, contributing factors, and the evidence supporting the information in all these fields. Representing the risks in this way enables reasoning about the risks, e.g. revisiting a risk assessment when a mitigation strategy is unavailable, updating a risk assessment when new information becomes available, etc. Such a system also provides a concise way to communicate the risks both within the organization as well as with collaborators. Understanding and, hence, harnessing the human system risk-related data supply chain enhances both organizations' abilities to securely collect, integrate, and share data assets that improve human system research and operations.

Buquo, Lynn↗
NASA NTRS2011

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

An Information Architecture facilitates the understanding and, hence, harnessing of the human system risk-related data supply chain which enhances the ability to securely collect, integrate, and share data assets that improve human system research and operations. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as a data supply chain), the Human Research Program (HRP) and Space Life Science Directorate (SLSD) are building an information architecture plan to leverage their existing, and often shared, IT infrastructure.

Buquo, Lynn E.↗
NASA NTRS2019

Overcoming the Challenges of Data Integration and Automation

Artificial Intelligence (AI) and machine learning (ML) are gaining increased attention as a way to leverage the world's data to solve problems. Although AI and ML offer much potential, there are often misconceptions about the application of such techniques. This panel discussion includes speakers from airlines and the research community who will present machine learning approaches they have developed on a variety of aviation data including digital flight data, safety reporting data, and traffic flow data. They will explain the purpose of the application, the data used, and the lessons learned in the development and deployment of their solutions. The panel discussion will focus on common pitfalls in developing and AI solution, the dangers of the current hype around AI, tips for gaining value from a machine learning solution, how to determine whether a machine learning approach is appropriate for a problem, and more.

Matthews, Bryan L.↗
NASA NTRS1999

TRMM Realtime Data Production, Transfer, and Future Plans

The Tropical Rainfall Measuring Mission, a joint US NASA and Japan NASDA mission, was launched on November 27, 1997 from Tanegashima Island, Japan on a NASDA provided H-II launch vehicle. The TRMM objectives are: to obtain and study multi-year science data sets of tropical and sub- tropical rainfall measurement; to understand how interactions between the sea, air, and land masses produce changes in global rainfall and climate; to help improve modeling of tropical rainfall processes; to test, evaluate, and improve the performance of satellite rainfall estimates measurements and techniques. The routine production and quick distribution of standard products provides an important underpinning to these objectives. The determination of standard TRMM algorithms and the requirements for routine production and distribution fall within the authority of the joint US-Japan Science Team. In April of 1998, the Joint TRMM Science team requested that TRMM data be made available in near real-time to approved international agencies and modelers. This request was an addition to the routine production of the standard TRMM data products. The science team requested that near-realtime products be as small as possible to facilitate their transfer via networks. Indeed, it was determined that only network transfer would be available. This presentation provides an overview of the type of products available from the realtime system and how the TRMM system was developed at the lowest cost in the shortest amount of time. It then describes the real-time data flow. The presentation also summarizes how the science quality of real-time data is maintained. It describes how interested groups can get access to this data and the importance of networks for the future of real-time data expansion. The presentation concludes real-time possibilities and improvements possible as part of the proposed Global Precipitation Mission. High speed network access availability is an important catalyst to real-time data flow during the proposed mission.

Stocker, Erich Franz↗
DOE OSTI2025

Preserving nonlinear constraints in variational flow filtering data assimilation

Data assimilation aims to estimate the states of a dynamical system by optimally combining sparse and noisy observations of the physical system with uncertain forecasts produced by a computational model. The states of many dynamical systems of interest obey nonlinear physical constraints, and the corresponding dynamics is confined to a certain sub-manifold of the state space. Standard data assimilation techniques applied to such systems yield posterior states lying outside the manifold, violating the physical constraints. This work focuses on particle flow filters which use stochastic differential equations to evolve state samples from a prior distribution to samples from an observation-informed posterior distribution. The variational Fokker-Planck (VFP)—a generic particle flow filtering framework—is extended to incorporate non-linear, equality state constraints in the analysis. To this end, two algorithmic approaches that modify the VFP stochastic differential equation are discussed: (i) VFPSTAB, to inexactly preserve constraints with the addition of a stabilizing drift term, and (ii) VFPDAE, to exactly preserve constraints by treating the VFP dynamics as a stochastic differential-algebraic equation (SDAE). Additionally, an implicit-explicit time integrator is developed to evolve the VFPDAE dynamics. The strength of the proposed approach for constraint preservation in data assimilation is demonstrated on three test problems: the double pendulum, Korteweg-de-Vries, and the incompressible Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Thermal regime of the continental lithosphere

From studies of the global heat flow data set, it has been generalized, with respect to the continental lithosphere, that there is a negative correlation between heat flow and the lithosphere's tectonic edge, and that the lithosphere's thermal evolution is similar to that of the ocean basins, resulting in a 'stable geotherm' in both environments. It is presently noted that a regional study perspective for heat flow data leads to doubts concerning the general applicability of either statement. Rao et al. (1982) have demonstrated that the data are not normally distributed, and that it is not possible to establish a negative correlation between heat flow and age in a rigorous statistical fashion. While some sites of stable continental blocks may have a geotherm that is by chance similar to that for old ocean basins, this need not hold true generally, and many stable continental terranes will be characterized by geotherms very different from those for old ocean basins.

Morgan, P.↗
NASA NTRS1995

Advanced in Visualization of 3D Time-Dependent CFD Solutions

Numerical simulations of complex 3D time-dependent (unsteady) flows are becoming increasingly feasible because of the progress in computing systems. Unfortunately, many existing flow visualization systems were developed for time-independent (steady) solutions and do not adequately depict solutions from unsteady flow simulations. Furthermore, most systems only handle one time step of the solutions individually and do not consider the time-dependent nature of the solutions. For example, instantaneous streamlines are computed by tracking the particles using one time step of the solution. However, for streaklines and timelines, particles need to be tracked through all time steps. Streaklines can reveal quite different information about the flow than those revealed by instantaneous streamlines. Comparisons of instantaneous streamlines with dynamic streaklines are shown. For a complex 3D flow simulation, it is common to generate a grid system with several millions of grid points and to have tens of thousands of time steps. The disk requirement for storing the flow data can easily be tens of gigabytes. Visualizing solutions of this magnitude is a challenging problem with today's computer hardware technology. Even interactive visualization of one time step of the flow data can be a problem for some existing flow visualization systems because of the size of the grid. Current approaches for visualizing complex 3D time-dependent CFD solutions are described. The flow visualization system developed at NASA Ames Research Center to compute time-dependent particle traces from unsteady CFD solutions is described. The system computes particle traces (streaklines) by integrating through the time steps. This system has been used by several NASA scientists to visualize their CFD time-dependent solutions. The flow visualization capabilities of this system are described, and visualization results are shown.

Lane, David A.↗
NASA NTRS1973

The behavior of a compressible turbulent boundary layer in a shock-wave-induced adverse pressure gradient

The results of an experimental investigation of the mean- and fluctuating-flow properties of a compressible turbulent boundary layer in a shock-wave-induced adverse pressure gradient are presented. The turbulent boundary layer developed on the wall of an axially symmetric nozzle and test section whose nominal free-stream Mach number and boundary-layer thickness Reynolds number were 4 and 100,000, respectively. The adverse pressure gradient was induced by an externally generated conical shock wave. Mean and time-averaged fluctuating-flow data, including the complete experimental Reynolds stress tensor and experimental turbulent mass- and heat-transfer rates are presented for the boundary layer and external flow, upstream, within and downstream of the pressure gradient. The mean-flow data include distributions of total temperature throughout the region of interest. The turbulent mixing properties of the flow were determined experimentally with a hot-wire anemometer. The calibration of the wires and the interpretation of the data are discussed. From the results of the investigation, it is concluded that the shock-wave - boundary-layer interaction significantly alters the turbulent mixing characteristics of the boundary layer.

Rose, W. C.↗
NASA NTRS1983

Homogeneity of lava flows - Chemical data for historic Mauna Loan eruptions

Chemical analyses of basalts collected from the major historic eruptions of Mauna Loa volcano show that many of the flow fields are remarkably homogeneous in composition. Despite their large size (lengths 9-85 km), large areal extents (13-114 sq km), and various durations of eruption (1-450 days), many of the flow fields have compositional variability that is within, or close to, the analytical error for most elements. The flow fields that are not homogeneous vary mainly in olivine content in an otherwise homogeneous melt. Some are composite flow fields made up of several, apparently homogeneous subunits erupted at different elevations along the active volcanic rifts. Not all volcanoes produce lavas that are homogeneous like those of Mauna Loa. If studies such as this are to be used to evaluate compositional diversity in lavas where there is a lack of sampling control, such as on other planets, it is necessary to understand why some flow units and flow fields are compositionally homogeneous and others are not, and to develop criteria for distinguishing between them.

Rhodes, J. M.↗
NASA NTRS2012

Flow Analysis Tool White Paper

Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

Boscia, Nichole K.↗