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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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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↗
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.↗
NASA NTRS1989

Test Data of Flow Field of Shuttle SRM Nozzle Joint with Bond Defects, Using Unheated Air

The nozzle-to-case joint on the Shuttle SRM (as redesigned after the Challenger accident) features an adhesive sealant filling and bonding the joint, with a wiper O-ring to prevent the adhesive from reaching and disabling the closure O-ring. Flawless implementation of that joint design would ensure that hot, corrosive propellant combustion gases never reach the closure O-ring. However, understanding the flow field related to bonding defects is prudent. A comprehensive test program was conducted to quantify such flow fields and associated heating environments. A two-dimensional, full-scale model represented 65 inches of the nozzle joint, using unheated air as the test medium, in a blowdown mode. Geometry variations modeled RSRM assembly tolerances, and two types of bonding defects: pullaways and blowholes. A range of the magnitude of each type defect was tested. Also a range of operational parameters was tested, representative of the RSRM flow environment, including duplication of RSRM Mach and Reynolds numbers. Extensive instrumentation was provided to quantify pressures, heat rates, and velocities. The resulting data established that larger geometric defects cause larger pressure and larger heating, at the closure O-ring region. Velocity trends were not so straight-forward. Variations in assembly tolerances did not generally affect flow fields or heating. Operational parameters affected flow fields and heating as might be expected, increasing density or velocity increased heating. Complete details of this test effort are presented.

Hair, Leroy M.↗
NASA NTRS2001

The Role of Advanced Information System Technology in Remote Sensing for NASA's Earth Science Enterprise in the 21st Century

Future NASA Earth observing satellites will carry high-precision instruments capable of producing large amounts of scientific data. The strategy will be to network these instrument-laden satellites into a web-like array of sensors to facilitate the collection, processing, transmission, storage, and distribution of data and data products - the essential elements of what we refer to as "Information Technology." Many of these Information Technologies will enable the satellite and ground information systems to function effectively in real-time, providing scientists with the capability of customizing data collection activities on a satellite or group of satellites directly from the ground. In future systems, extremely large quantities of data collected by scientific instruments will require the fastest processors, the highest communication channel transfer rates, and the largest data storage capacity to insure that data flows smoothly from the satellite-based instrument to the ground-based archive. Autonomous systems will control all essential processes and play a key role in coordinating the data flow through space-based communication networks. In this paper, we will discuss those critical information technologies for Earth observing satellites that will support the next generation of space-based scientific measurements of planet Earth, and insure that data and data products provided by these systems will be accessible to scientists and the user community in general.

Prescott, Glenn↗
NASA NTRS1975

HAL/SM system functional design specification

The functional design of a preprocessor, and subsystems is described. A structure chart and a data flow diagram are included for each subsystem. Also a group of intermodule interface definitions (one definition per module) is included immediately following the structure chart and data flow for a particular subsystem. Each of these intermodule interface definitions consists of the identification of the module, the function the module is to perform, the identification and definition of parameter interfaces to the module, and any design notes associated with the module. Also described are compilers and computer libraries.

Ross, C.↗
NASA NTRS1988

Strategies for concurrent processing of complex algorithms in data driven architectures

The purpose is to document research to develop strategies for concurrent processing of complex algorithms in data driven architectures. The problem domain consists of decision-free algorithms having large-grained, computationally complex primitive operations. Such are often found in signal processing and control applications. The anticipated multiprocessor environment is a data flow architecture containing between two and twenty computing elements. Each computing element is a processor having local program memory, and which communicates with a common global data memory. A new graph theoretic model called ATAMM which establishes rules for relating a decomposed algorithm to its execution in a data flow architecture is presented. The ATAMM model is used to determine strategies to achieve optimum time performance and to develop a system diagnostic software tool. In addition, preliminary work on a new multiprocessor operating system based on the ATAMM specifications is described.

Stoughton, John W.↗
NASA NTRS1982

Deep space payload launches via the Space Transportation System

The launching of deep space payloads via the Space Shuttle vehicle of the Space Transportation System, rather than via expendable launch vehicles, is described. Changes in procedures and data flow configurations for both the flight project and DSN during the launch period are required. A typical Galileo launch period sequence of events and telemetry and command data flow configurations are described.

Berman, A. L.↗
NASA NTRS1988

A strategy for reducing turnaround time in design optimization using a distributed computer system

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software.

Young, Katherine C.↗
NASA NTRS1983

The 1986 launch of the Galileo spacecraft via the Space Transportation System

Beginning with the Galileo spacecraft launch, deep space payloads will be launched via the Space Shuttle. This change from the previous use of expendable launch vehicles will introduce large changes in procedures and data flow configurations for both the flight project and the Deep Space Network during the launch period. The planned Galileo launch period sequence of events and telemetry and command data flow configurations are described.

Berman, A. L.↗