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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 NTRS2004

Modular Engine Noise Component Prediction System (MCP) Program Users' Guide

This is a user's manual for Modular Engine Noise Component Prediction System (MCP). This computer code allows the user to predict turbofan engine noise estimates. The program is based on an empirical procedure that has evolved over many years at The Boeing Company. The data used to develop the procedure include both full-scale engine data and small-scale model data, and include testing done by Boeing, by the engine manufacturers, and by NASA. In order to generate a noise estimate, the user specifies the appropriate engine properties (including both geometry and performance parameters), the microphone locations, the atmospheric conditions, and certain data processing options. The version of the program described here allows the user to predict three components: inlet-radiated fan noise, aft-radiated fan noise, and jet noise. MCP predicts one-third octave band noise levels over the frequency range of 50 to 10,000 Hertz. It also calculates overall sound pressure levels and certain subjective noise metrics (e.g., perceived noise levels).

Golub, Robert A.↗
NASA NTRS1986

Confidence limits for small numbers of events in astrophysical data

The calculation of limits for small numbers of astronomical counts is based on standard equations derived from Poisson and binomial statistics; although the equations are straightforward, their direct use is cumbersome and involves both table-interpolations and several mathematical operations. Convenient tables and approximate formulae are here presented for confidence limits which are based on such Poisson and binomial statistics. The limits in the tables are given for all confidence levels commonly used in astrophysics.

Gehrels, N.↗
NASA NTRS2019

Simulation-to-Flight 1 (STF-1): Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2019, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC Technologies, and four independent professor-student teams at West Virginia University.

CubeSat↗
NASA NTRS2019

STF-1 Ground Operations - Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2018, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC2 Technologies, and four independent professor-student teams at West Virginia University.

Suder, Mark↗
NASA NTRS2006

A Decohesive Constitutive Formulation for Modeling Failure of Sea Ice

One of the dominant characteristics of Arctic ice as reflected by RADARSAT Geophysical Processor System data is the development and persistence of leads. Experimental data from small specimens as well as in situ data from Arctic ice suggest that failure may occur under compression. Presented here is a decohesive constitutive model for which one of the distinguishing new features is that failure is predicted under uniaxial compression. More generally, the model specifically indicates when a lead is initiated, provides the orientation of the lead, gives the mode of failure, and allows one to numerically determine the width of leads. In addition, the approach allows multiple failure planes, a feature that is necessary to simulate crack branching. Pre-existing planes of weakness such as those formed from previous leads can be incorporated. Sample calculations indicate how such a model can be used for large-scale numerical simulations.

Schreyer, H. L.↗
NASA NTRS1989

Flap-lag stability data for a small-scale isolated hingeless rotor in forward flight

An isolated, hingeless rotor with discrete flap and lead-lag flexures and relatively rigid blades was tested in the Aeroflightdynamics Directorate's 7- by 10-Foot Wind Tunnel. The lead-lag stability of a structurally simple rotor configuration in forward flight was determined. The model tested had no cyclic pitch control, and was therefore operated untrimmed at several collective pitch angles, at shaft angles from 0 deg to -20 deg, and at advance ratios as high as 0.55. Two inplane natural frequencies, 0.61/rev and 0.72/rev, were tested for configuration both with and without structural flap lag coupling. Concomitant hover testing of the model was also conducted. Representative plots of the frequency and damping data are presented to show general trends, and complete tabular data and model properties information are included for use in detailed correlation exercises. The most prominent feature of the forward flight data is an abrupt increase in damping with advance ratio at certain high-speed, high shaft-angle conditions, with high flapping loads. The hover data are consistent with previous experimental and theoretical results for hingeless rotors without kinematic couplings. Overall, the data quality is very good and the data are expected to be useful in the development and validation of rotor aeroelastic stability analyses.

Mcnulty, Michael J.↗
NASA NTRS2012

Development of an Integrated Data Acquisition System for a Small Flight Probe

In support of the SPRITE concept, an integrated data acquisition system has been developed and fabricated for preliminary testing. The data acquisition system has been designed to condition traditional thermal protection system sensors, store their data to an on-board memory card, and in parallel, telemeter to an external system. In the fall of 2010, this system was integrated into a 14 in. diameter, 45 degree sphere cone probe instrumented with thermal protection system sensors. This system was then tested at the NASA Ames Research Center Aerodynamic Heating Facility's arc jet at approximately 170 W/sq. cm. The first test in December 2010 highlighted hardware design issues that were redesigned and implemented leading to a successful test in February 2011.

Swanson, Gregory T.↗
DOE OSTI2022

Tools for Visualization and Analysis of Small-Angle Neutron Scattering Data: Descriptions and Examples

A great deal of progress has been made in improving the data reduction experience for the SANS instruments at the SNS and HFIR at ORNL. The existing data reduction toolset, drtsans, makes it possible to integrate data analysis and visualization tools into the data reduction scripts, thereby providing new opportunities for more automated data processing for users of the SNS and HFIR. Here, the first set of tools developed is described with usage examples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

More Tools for Visualization and Analysis of Small-Angle Neutron Scattering Data: Descriptions and Examples

With the adoption of drtsans as the data reduction software for the GP-SANS, Bio-SANS and EQ-SANS instruments at ORNL, tools for data visualization and analysis that can be integrated into drtsans scripts are needed to further improve the user experience. New tools that do not need to be incorporated directly into data reduction scripts can also positively impact users during their experiments. In this report, a new set of tools is presented that complements the previous set released. The set includes tools for both fitting data and for visualizing data.

42 ENGINEERING↗
DOE OSTI2023

Another Set of Python Tools for Visualizing and Manipulating Small-Angle Neutron Scattering Data: Descriptions and Examples

The GP-SANS, Bio-SANS and EQ-SANS instruments at ORNL utilize drtsans for data reduction. drtsans is built on Python, and it can be run using python scripts and Jupyter notebooks. The flexibility afforded by Python makes it possible to incorporate additional actions into the scripts used for data reduction, such as analysis and visualization. Here, a new set of tools for visualizing and manipulating SANS data that can be incorporated into the data reduction scripts for the ORNL SANS instruments, or employed during post–processing, is presented that expands the capabilities of the two previously-released tool sets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1972

Small rocket exhaust plume data

During recent cryodeposit tests with an 0.18-N thruster, the mass flux in the plume back field was measured for the first time for nitrogen, carbon dioxide, and a mixture of nitrogen, hydrogen, and ammonia at various inlet pressures. This mixture simulated gases that would be generated by a hydrazine plenum attitude propulsion system. The measurements furnish a base upon which to build a mathematical model of plume back flow that will be used in predicting the mass distribution in the boundary region of other plumes. The results are analyzed and compared with existing analytical predictions.

Chirivella, J. E.↗
NASA NTRS1980

Appendix C: A comparative study of small scale remotely sensed data for monitoring clearcutting in hardwood forests

Manual photointerpretation techniques were used to analyze images acquired by high altitude aircraft, the Skylab multispectral and Earth terrain camera (ETC), the LANDSAT multispectral scanner, and the LANDSAT-3 return beam vidicon camera. A color-additive viewer, and digital image analysis were also used on the LANDSAT MSS imagery. The value of each type of remotely sensed data was judged by the ease and accuracy of clearcut identification, and by the amount of detail discernible, especially regarding revegetation. Results of a site study in the Allegheny National Forest, Pennsylvania indicate that high altitude aerial photography, especially color infrared photography acquired during the growing season, is well suited for identifying clearcuts and assessing revegetation. Although photographs acquired with Skylab's ETC also yielded good results, only incomplete inventories of clearcuts could be made using LANDSAT imagery. Results for the Adirondack region of New York State were similar for the aircraft and satellite photography, but even less satisfactory for the LANDSAT imagery.

Hafker, W. R.↗
NASA NTRS1994

Controller for the Electronically Scanned Thinned Array Radiometer (ESTAR) instrument

A prototype controller for the ESTAR (electronically scanned thinned array radiometer) instrument has been designed and tested. It manages the operation of the digital data subsystem (DDS) and its communication with the Small Explorer data system (SEDS). Among the data processing tasks that it coordinates are FEM data acquisition, noise removal, phase alignment and correlation. Its control functions include instrument calibration and testing of two critical subsystems, the output data formatter and Walsh function generator. It is implemented in a Xilinx XC3064PC84-100 field programmable gate array (FPGA) and has a maximum clocking frequency of 10 MHz.

Zomberg, Brian G.↗
NASA NTRSDate not supplied

FUN3D Analyses in Support of the 1st AIAA Stability and Control Prediction Workshop

The 1st AIAA Stability and Control Prediction Workshop was created to establish best practices for the prediction of stability & control derivatives using computational fluid dynamics and assess the limitations of these computational methods when those best practices are applied. The inaugural workshop considers the ONERA version of the NASA/Boeing Common Research Model(CRM), which includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. Wind tunnel tests have been conducted for this configuration with longitudinal tests having been previously published, in addition to unpublished data at small sideslip angles that will serve as ‘blind’ data for workshop data comparisons. Participants were provided a ‘family’ of unstructured grids for the full-span ONERA CRM model with the wind-tunnel sting included. This family of mixed-element grids consists of 5 levels of refinement (tiny, coarse, medium, fine, and extra fine) with surface and volume mesh scaling, resulting in a size range of 14.6 to 53.4 million nodes. In addition, a medium refinement mesh has been provided for the ONERA CRM configuration without a sting to evaluate the sting’s impact on static longitudinal stability characteristics. In addition to these workshop-provided grids, the present work also considers an equivalent ‘family’ of computational grids generated using Heldenmesh™, a rapid grid generation software by Helden Aerospace Corporation for creating high-quality, three-dimensional, mixed-element unstructured meshes. Because of the authors’ familiarity with this software, these additional grids were generated as a comparison to the workshop-provided grids and to better understand the implications of using volume-mirrored grids for stability and control predictions. The present work will contribute to the workshop with test case data generated using the NASA FUN3D code, a parallelized, unstructured, node-based, finite-volume discretization, Reynolds-averaged Navier-Stokes flow solver. Numerical simulations will be conducted using the Quadratic Constitutive Relationship (QCR) version of the Spalart-Allmaras (SA) turbulence model with negative turbulence variable provisions. Both steady and2nd-order, time-accurate simulation results are to be generated and compared for select test cases, as time permits, to investigate their impact on FUN3D predictions. The present work will consider the three primary workshop test cases: (1) grid convergence study, (2) Mach number effect on static stability, and (3) wind tunnel sting increments. Additionally, data will be provided for the two optional test cases, which include:(1) static stability derivative calculations and (2)sideslip angle sweeps. In each of the test cases, the vehicle is stationary, and the body is assumed to be rigid, where vehicle deformation has been accounted for in the model configuration geometry. For all test cases, longitudinal and lateral force and moment aerodynamic coefficients will be provided for the total configuration, in addition to a component-level breakdown that includes the port wing, starboard wing, fuselage, and tail.

CFD↗