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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
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.↗
DOE OSTI2025

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗
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.↗
DOE OSTI2026

Sap Velocity Data for East River Watershed Sites (2023-2025)

This dataset includes sap velocity measurements for aspen (populus tremuloides), fir (abies lasiocarpa), spruce (Engelmann spruce) and lodgepole pine (pinus contorta) trees at nine sites in the East River Watershed near Gothic, CO. This dataset was generated following a similar method as a previous dataset (Dataset. doi:10.15485/1647654) but was conducted at different sites in the area and now includes lodgepole pine. Site selection was done to explicitly improve understanding of topographic controls of tree water use. The data collection began in June 2023 and we provide data until December 2025 - though data collection is ongoing. The sap flux data were collected using ICT SFM1 sensors and are presented in both units of cm h^-1 and as kg h^-1 by multiplying the sap flux by the sapwood area of the tree. All sap flow data has been been corrected using estimates of wounding diameter, water content of wood and sap wood depth. We also provide a normalized sap velocity estimate by subtracting each measurement from that trees' annual minimum and dividing by that trees' annual maximum. This provides data for each tree and year on a 0-1 scale. This data entry contains one CSV file that includes all available sap flow data. The timestamps are provided in local time as year, day of year and hour and each measurement contains an associated latitude, longitude and site number which can be used to identify trees in a given stand. Each species is given a numeric value as: 1= populus tremuloides, 2=Engelmann spruce, 3=abies lasiocarpa and 4=pinus contorta.

abies↗
DOE OSTI2011

Google.org US Resource Project Update

The results from a new geothermal resource assessment of the United States, including for the first time detailed data for much of the eastern US, are summarized along with the techniques used to accomplish the assessment. Bottom hole temperature (BHT) data were incorporated in the eastern US, where conventional heat flow data is sparse, using BHT corrections and calculated conductivities from a regional lithology model; comparing results to overlapping conventional heat flow and BHT data for error calibration. A total of 5,000 points are now available in the northeast as opposed to the 1,000 used to produce the 2004 Geothermal Map of North America. Where neither heat flow or BHT data were not available, geophysical data (regional gravity and magnetics) were used as an ancillary predictor to the process for areas with sedimentary cover. The effectiveness of that process is demonstrated. This study uses the new heat flow data to improve the calculated heat in place to 10 km for the US. Based the preliminary results from this wok, the Appalachian Basin may contain some of the most favorable potential targets for EGS geothermal exploration in the eastern 1/3 of the United States and especially in eastern West Virginia, where temperatures of at least 150°C are predicted at a depth of 4.5 km in localized areas.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utah FORGE: Well 16A(78)-32 Stimulation Tracer Test Results

This archive contains data from the tracer test performed during the Utah FORGE well 16A(78)-32 stimulation. This includes: 1. the raw data file from Pason in the csv format; 2. a one-page Word document from Pason that explains the headers and units used in their data file; 3. an Excel spreadsheet with concentration data and relevant Pason flow data; 4. a Word document with jpg versions of concentration charts (Figs. 1-3) and a tracer mass recovery chart (Fig. 4).

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Directional Laplacian Centrality for Cyber Situational Awareness

Cyber operations is drowning in diverse, high-volume, multi-source data. To get a full picture of current operations and identify malicious events and actors, analysts must see through data generated by a mix of human activity and benign automated processes. Although many monitoring and alert systems exist, they typically use signature-based detection methods. We introduce a general method rooted in spectral graph theory to discover patterns and anomalies without a priori knowledge of signatures. We derive and propose a new graph-theoretic centrality measure based on the derivative of the graph Laplacian matrix in the direction of a vertex. To build intuition about our measure, we show how it identifies the most central vertices in standard network datasets and compare to other graph centrality measures. Finally, we focus our attention on studying its effectiveness in identifying important IP addresses in network flow data. Using both real and synthetic network flow data, we conduct several experiments to test our measure’s sensitivity to two types of injected attack profiles and show that vertices participating in injected attack profiles exhibit noticeable changes in our centrality measures, even when the injected anomalies are relatively small, and in the presence of simulated network dynamics.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
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↗
DOE OSTI2023

CSEM, Bottomhole Pressure, Salinity, and Flow-Rate Data Collected in Sep. 2020 for Proj. DE-FE0031785

This dataset consists of two directories: first directory named as EM for the controlled source electromagnetic (CSEM) survey data that are zipped per day for September 22, 23, 24, 25, and 27, 2020, and second directory named as "Bottomhole Pressure, Salinity, and Flow-Rate" for the simultaneous collection of bottomhole pressure and salinity and pump flow rate during the CSEM surveys.

CSEM↗
DOE OSTI2023

MHTLS Cross-flow Heat Exchanger Temperature Performance Data

The presentation and supporting information provide data on the performance of an engineering-scale cross-flow heat exchanger used in hydrothermal liquefaction (HTL). Temperature profiles are provide for the process of waste water treatment sludges and a food waste. The data can be used to model larger-scale heat exchangers used in HTL.

Bioenergy Technologies Tags Heat Exchanger HTL MHT↗
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.↗
DOE OSTI2021

Diolkos: Improving ethernet throughput through dynamic port selection

In large networked systems, a sudden increase in traffic could slowdown the network significantly, impacting network quality for multiple users. We present Diolkos, a system that leverages smart switches to dynamically re-reroute data flows in response to drops in performance. In contrast to other techniques, our tool predicts the future throughput at each port in a switch if a data flow were to be sent through it, and updates which port should be taken to maximize throughput. We use several techniques to predict network switch performance on a software defined network (SDN) mimicking topologies commonly found in datacenters. Experimentally, we demonstrate the effectiveness of choosing a port to send flows through based on predicted performance. We found that using a distributed predictive technique achieves a 24% improvement over using a traditional heuristic technique.

port selection, performance enhancement, Neural Ne↗
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.↗