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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Cross Support Transfer Service (CSTS) Framework Library

Within the Consultative Committee for Space Data Systems (CCSDS), there is an effort to standardize data transfer between ground stations and control centers. CCSDS plans to publish a collection of transfer services that will each address the transfer of a particular type of data (e.g., tracking data). These services will be called Cross Support Transfer Services (CSTSs). All of these services will make use of a common foundation that is called the CSTS Framework. This library implements the User side of the CSTS Framework. "User side" means that the library performs the role that is typically expected of the control center. This library was developed in support of the Goddard Data Standards program. This technology could be applicable for control centers, and possibly for use in control center simulators needed to test ground station capabilities. The main advantages of this implementation are its flexibility and simplicity. It provides the framework capabilities, while allowing the library user to provide a wrapper that adapts the library to any particular environment. The main purpose of this implementation was to support the inter-operability testing required by CCSDS. In addition, it is likely that the implementation will be useful within the Goddard mission community (for use in control centers).

Ray, Timothy↗
NASA NTRS2025

Cognitive Engine One: A Cross-Layer Framework for Autonomy in Multi-Provider Space Communications Environments

Spacecraft information needs, along with the communications environments in which data transfers occur, are becoming increasingly dynamic. Earth orbit is served by dozens of ground station and relay satellite providers – each with unique protocols and service capabilities. In this context, we present a system to automate end-to-end space communications across the protocol stack for each of several providers. The proposed system schedules contacts with providers, configures point-to-point RF links, and ensures data is transferred to its destination. Data monitoring and rescheduling provide an automated failover capability in the event of unsuccessful contacts. We verify system performance in a high-fidelity emulation testbed. Results from several scenarios demonstrate favorable system performance across a variety of mission use cases.

space communications↗
NASA NTRS1949

Heat transfer from high-temperature surfaces to fluids II : correlation of heat-transfer and friction data for air flowing in inconel tube with rounded entrance

A heat transfer investigation, which was an extension of a previously reported NACA investigation, was conducted with air flowing through an electrically heated inconel tube with a rounded entrance,an inside diameter of 0.402 inch, and a length of 24 inches over a range of conditions, which included Reynolds numbers up to 500,000, average surface temperatures up to 2050 degrees R, and heat-flux densities up to 150,000 Btu per hour per square foot. Conventional methods of correlating heat-transfer data wherein properties of the air were evaluated at the average bulk, film, and surface temperatures resulted in reductions of Nusselt number of about 38, 46, and 53 percent, respectively, for an increase in surface temperature from 605 degrees to 2050 degrees R at constant Reynolds number. A modified correlation method in which the properties of air were based on the surface temperature and the Reynolds number was modified by substituting the product of the density at the inside tube wall and the bulk velocity for the conventional mass flow per unit cross-sectional area, resulted in a satisfactory correlation of the data for the extended ranges of conditions investigated.

Lowdermilk, Warren H↗
DOE OSTI2025

Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science Addendum

Activation detectors developed at LLNL for measuring real-time neutron fluence from fusion sources are used in the broader fusion community. The recommended fluence operating range of this diagnostic is 5x10 2 – 1x10 6 n/cm2. The upper limit on this fluence range is set by the dead time caused by data transfer between the detector and data acquisition computer. Delaying the start of counting is a possible strategy to operate these detectors in higher fluences.

42 ENGINEERING↗
NASA NTRS1972

Subcooled forced convection boiling of trichlorotrifluoroethane

Experimental heat-transfer data were obtained for the forced-convection boiling of trichlorotrifluoroethane (R-113 or Freon-113) in a vertical annular test annular test section. The 97 data points obtained covered heat transfer by forced convection, local boiling, and fully-developed boiling. Correlating methods were obtained which accurately predicted the heat flux as a function of wall superheat (boiling curve) over the range of parameters studied.

Dougall, R. S.↗
NASA NTRS1978

Evaporator film coefficients of grooved heat pipes

The heat transfer rate in the meniscus attachment region of a grooved heat pipe evaporator is studied theoretically. The analysis shows that the evaporation takes place mainly in the region where the liquid changes its shape sharply. However, comparisons with available heat transfer data indicate that the heat transfer rate in the meniscus varying region is substantially reduced probably due to groove wall surface roughness.

Kamotani, Y.↗
NASA NTRS1992

State of the Data Union, 1992

This is the first report on the State of the Data Union (SDU) for the NASA Office of Space Science and Applications (OSSA). OSSA responsibilities include the collection, analysis, and permanent archival of data critical to space science research. The nature of how this is done by OSSA is evolving to keep pace with changes in space research. Current and planned missions have evolved to be more complex and multidisciplinary, and are generating much more data and lasting longer than earlier missions. New technologies enable global access to data, transfer of huge volumes of data, and increasingly complex analysis. The SDU provides a snapshot of this dynamic environment, identifying trends in capabilities and requirements. The current space science data environment is described and parameters which capture the pulse of key functions within that environment are presented. Continuous efforts of OSSA to improve the availability and quality of data provided to the scientific community are reported, highlighting efforts such as the Data Management Initiative.

Source record↗
NASA NTRS2000

An Integrated MEMS Sensor Cluster System for Aerospace Applications

Efforts to reduce viscous drag on airfoils could results in a considerable saving for the operation of flight vehicles including those of space transportation. This reduction of viscous drag effort requires measurement and active control of boundary layer flow property on an airfoil. Measurement of viscous drag of the boundary layer flow over an airfoil with minimal flow disturbance is achievable with newly developed MEMS sensor clusters. These sensor clusters provide information that can be used to actively control actuators to obtain desired flow properties or design a vehicle to satisfy particular boundary layer flow criteria. A series of MEMS sensor clusters has been developed with a data acquisition and control module for local measurements of shear stress, pressure, and temperature on an airfoil. The sensor cluster consists of two shear stress sensors, two pressure sensors, and two temperature sensors on a surface area of 1.24 mm x 1.86 mm. Each sensor is 300 microns square and is placed on a flexible polyimide sheet. The shear stress sensor is a polysilicon hot-film resistor, which is insulated by a vacuum cavity of 200 x 200 x 2 microns. The pressure sensors are silicon piezoresistive type, and the temperature sensors are also hot film polysilicon resistors. The total size of the cluster including sensors and electrical leads is 1 Omm x 1 Omm x 0.1 mm. A typical sensitivity of shear stress sensor is 150 mV/Pascal, the pressure sensors are an absolute type with a measurement range from 9 to 36 psia with 0.8mV/V/psi sensitivity, and the temperature sensors have a measurement resolution of 0.1 degree C. The sensor clusters are interfaced to a data acquisition and control module that consists of two custom ASICs (Application Specific Integrated Circuits) and a micro-controller. The data acquisition and control module transfers data to a host PC that configures and controls a total of three sensor clusters. Functionality of the entire system has been tested in the laboratory, and preliminary test results are presented.

Kahng, Seun↗
DOE OSTI2020

Distributed Computing for the Project 8 Experiment

The Project 8 collaboration aims to measure the absolute neutrino mass or improve on the current limit by measuring the tritium beta decay electron spectrum. We present the current distributed computing model for the Project 8 experiment. Project 8 is in its second phase of data taking with a near continuous data rate of 1Gbps. The current computing model uses DIRAC (Distributed Infrastructure with Remote Agent Control) for its workflow and data management. A detailed meta-data assignment using the DIRAC File Catalog is used to automate raw data transfers and subsequent stages of data processing. The DIRAC system is deployed on containers managed using a Kubernetes cluster to provide a scalable infrastructure. A modified DIRAC Site Director provides the ability to submit jobs using Singularity on opportunistic High-Performance Computing (HPC) sites.

Distributed Computing, Kubernetes, DIRAC, Project ↗
DOE OSTI2022

FPGA-based computing system for processing data in size, weight, and power constrained environments

Technologies that are well-suited for use in size, weight, and power (SWAP)-constrained environments are described herein. A host controller dispatches data processing instructions to hardware acceleration engines (HAEs) of one or more field programmable gate arrays (FPGAs) and further dispatches data transfer instructions to a memory controller, such that the HAEs perform processing operations on data stored in local memory devices of the HAEs in parallel with other data being transferred from external memory devices coupled to the FPGA(s) to the local memory devices.

Napier, Matthew↗
DOE OSTI2023

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Implementation of a standard format for GPS common view data

A new format for standardizing common view time transfer data, recommended by the Consultative Committee for the Definition of the Second, is being implemented in receivers commonly used for contributing data for the generation of International Atomic Time. We discuss three aspects of this new format that potentially improve GPS common-view time transfer: (1) the standard specifies the method for treating short term data, (2) it presents data in consistent formats including needed terms not previously available, and (3) the standard includes a header of parameters important for the GPS common-view process. In coordination with the release of firmware conforming to this new format the Bureau International des Poids et Mesures will release future international track schedules consistent with the new standard.

Weiss, Marc A.↗
NASA NTRS2004

Effects of Freestream Turbulence on Turbine Blade Heat Transfer

Experiments have shown that moderate turbulence levels can nearly double turbine blade stagnation region heat transfer. Data have also shown that heat transfer is strongly affected by the scale of turbulence as well as its level. In addition to the stagnation region, turbulence is often seen to increase pressure surface heat transfer. This is especially evident at low to moderate Reynolds numbers. Vane and rotor stagnation region, and vane pressure surface heat transfer augmentation is often seen in a pre-transition environment. Accurate predictions of transition and relaminarization are critical to accurately predicting blade surface heat transfer. An approach is described which incorporates the effects of both turbulence level and scale into a CFD analysis. The model is derived from experimental data for cylindrical and elliptical leadng edges. Results using this model are compared to experimental data for both vane and rotor geometries. The comparisons are made to illustrate that using a model which includes the effects of turbulence length scale improves agreement with data, and to illustrate where improvements in the modeling are needed.

Boyle, Robert J.↗
NASA NTRS2006

Cassini Archive Tracking System

The Cassini Archive Tracking System (CATS) is a computer program that enables tracking of scientific data transfers from originators to the Planetary Data System (PDS) archives. Without CATS, there is no systematic means of locating products in the archive process or ensuring their completeness. By keeping a database of transfer communications and status, CATS enables the Cassini Project and the PDS to efficiently and accurately report on archive status. More importantly, problem areas are easily identified through customized reports that can be generated on the fly from any Web-enabled computer. A Web-browser interface and clearly defined authorization scheme provide safe distributed access to the system, where users can perform functions such as create customized reports, record a transfer, and respond to a transfer. CATS ensures that Cassini provides complete science archives to the PDS on schedule and that those archives are available to the science community by the PDS. The three-tier architecture is loosely coupled and designed for simple adaptation to multimission use. Written in the Java programming language, it is portable and can be run on any Java-enabled Web server.

Conner, Diane↗
NASA NTRS1972

Atlas F entry aerothermic study

The feasibility of obtaining heat transfer data on an expended Atlas F booster launch vehicle was investigated in the altitude range of 300,000 to 200,000 feet during entry conditions, with a velocity in the range of 20,000 to 25,000 feet per second, and through a range of vehicle attitudes of plus or minus 90 degrees. These data are desired for correlation with turbulent heat transfer and boundary layer transition data obtained from wind tunnel test facilities. The data would also be valuable in assessing rarified gas and surface catalicity effects in a real gas environment.

Source record↗
NASA NTRS2006

CCSDS Time-Critical Onboard Networking Service

The Consultative Committee for Space Data Systems (CCSDS) is developing recommendations for communication services onboard spacecraft. Today many different communication buses are used on spacecraft requiring software with the same basic functionality to be rewritten for each type of bus. This impacts on the application software resulting in custom software for almost every new mission. The Spacecraft Onboard Interface Services (SOIS) working group aims to provide a consistent interface to various onboard buses and sub-networks, enabling a common interface to the application software. The eventual goal is reusable software that can be easily ported to new missions and run on a range of onboard buses without substantial modification. The system engineer will then be able to select a bus based on its performance, power, etc and be confident that a particular choice of bus will not place excessive demands on software development. This paper describes the SOIS Intra-Networking Service which is designed to enable data transfer and multiplexing of a variety of internetworking protocols with a range of quality of service support, over underlying heterogeneous data links. The Intra-network service interface provides users with a common Quality of Service interface when transporting data across a variety of underlying data links. Supported Quality of Service (QoS) elements include: Priority, Resource Reservation and Retry/Redundancy. These three QoS elements combine and map into four TCONS services for onboard data communications: Best Effort, Assured, Reserved, and Guaranteed. Data to be transported is passed to the Intra-network service with a requested QoS. The requested QoS includes the type of service, priority and where appropriate, a channel identifier. The data is de-multiplexed, prioritized, and the required resources for transport are allocated. The data is then passed to the appropriate data link for transfer across the bus. The SOIS supported data links may inherently provide the quality of service support requested by the intra-network layer. In the case where the data link does not have the required level of support, the missing functionality is added by SOIS. As a result of this architecture, re-usable software applications can be designed and used across missions thereby promoting common mission operations. In addition, the protocol multiplexing function enables the blending of multiple onboard networks. This paper starts by giving an overview of the SOIS architecture in section 11, illustrating where the TCONS services fit into the overall architecture. It then describes the quality of service approach adopted, in section III. The prototyping efforts that have been going on are introduced in section JY. Finally, in section V the current status of the CCSDS recommendations is summarized.

Parkes, Steve↗
NASA NTRS1978

SPAR data handling utilities

The SPAR computer software system is a collection of processors that perform particular steps in the finite-element structural analysis procedure. The data generated by each processor are stored on a data base complex residing on an auxiliary storage device, and these data are then used by subsequent processors. The SPAR data handling utilities use routines to transfer data between the processors and the data base complex. A detailed description of the data base complex organization is presented. A discussion of how these SPAR data handling utilities are used in an application program to perform desired user functions is given with the steps necessary to convert an existing program to a SPAR processor by incorporating these utilities. Finally, a sample SPAR processor is included to illustrate the use of the data handling utilities.

Giles, G. L.↗