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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Payload/GSE/data system interface: Users guide for the VPF (Vertical Processing Facility)

Payload/GSE/data system interface users guide for the Vertical Processing Facility is presented. The purpose of the document is three fold. First, the simulated Payload and Ground Support Equipment (GSE) Data System Interface, which is also known as the payload T-0 (T-Zero) System is described. This simulated system is located with the Cargo Integration Test Equipment (CITE) in the Vertical Processing Facility (VPF) that is located in the KSC Industrial Area. The actual Payload T-0 System consists of the Orbiter, Mobile Launch Platforms (MLPs), and Launch Complex (LC) 39A and B. This is referred to as the Pad Payload T-0 System (Refer to KSC-DL-116 for Pad Payload T-0 System description). Secondly, information is provided to the payload customer of differences between this simulated system and the actual system. Thirdly, a reference guide of the VPF Payload T-0 System for both KSC and payload customer personnel is provided.

Source record↗
NASA NTRS2012

User Guide to the PDS Dataset for the Cassini Composite Infrared Spectrometer (CIRS)

This User Guide to the Cassini Composite Infrared Spectrometer (CIRS) has been written with two communities in mind. First and foremost, scientists external to the Cassini Project who seek to use the CIRS data as archived in the Planetary Data System (PDS). In addition, it is intended to be a comprehensive reference guide for those internal to the CIRS team.

Nixon, Conor A.↗
NASA NTRS1994

An optimization program based on the method of feasible directions: Theory and users guide

The theory and user instructions for an optimization code based on the method of feasible directions are presented. The code was written for wide distribution and ease of attachment to other simulation software. Although the theory of the method of feasible direction was developed in the 1960's, many considerations are involved in its actual implementation as a computer code. Included in the code are a number of features to improve robustness in optimization. The search direction is obtained by solving a quadratic program using an interior method based on Karmarkar's algorithm. The theory is discussed, focusing on the important and often overlooked role played by the various parameters guiding the iterations within the program. Also discussed is a robust approach for handling infeasible starting points. The code was validated by solving a variety of structural optimization test problems that have known solutions obtained by other optimization codes. It has been observed that this code is accurate and robust: it has solved a variety of problems from different starting points. However, the code is inefficient in that it takes considerable CPU time as compared with certain other available codes. Further work is required to improve its efficiency while retaining its robustness.

Ashok D. Belegundu↗
NASA NTRS1980

Earth Observations Division version of the Laboratory for Applications of Remote Sensing System (EOD-LARSYS) user guide for the IBM 370/148. Volume 2: User reference manual

This document presents instructions for analysts who use the EOD-LARSYS as programmed on the Purdue University IBM 370/148 (recently replaced by the IBM 3031) computer. It presents sample applications, control cards, and error messages for all processors in the system and gives detailed descriptions of the mathematical procedures and information needed to execute the system and obtain the desired output. EOD-LARSYS is the JSC version of an integrated batch system for analysis of multispectral scanner imagery data. The data included is designed for use with the as built documentation (volume 3) and the program listings (volume 4). The system is operational from remote terminals at Johnson Space Center under the virtual machine/conversational monitor system environment.

Aucoin, P. J.↗
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 NTRS2024

Uranus Global Reference Atmospheric Model (Uranus-GRAM) 2024: User Guide

Engineers and mission planners designing vehicles that pass through Uranus’ atmosphere require an atmospheric model that calculates the mean values and variations of atmospheric properties. The Uranus Global Reference Atmospheric Model(Uranus-GRAM)is an engineering- oriented model that provides this information based on data from Voyager observations. Uranus- GRAM is designed to offer mission planners the flexibility to select input parameters such as time, latitude, and longitude. Uranus-GRAM outputs atmospheric constituent data and mean values for atmospheric density, temperature, pressure, and zonal wind along a user defined path. Uranus-GRAM also provides dispersions of density and zonal wind. Uranus-GRAM is one option in the GRAM Suite that shares a common software core with the other planetary GRAMs while maintaining Uranus specific models. Additionally, documentation, including this User Guide, a Programmer’s Manual, and trajectory code interfaces has been made available with the software release. This Technical Memorandum summarizes the atmospheric data model in Uranus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Section 2 describes the input atmospheric data files and how they are used in Uranus-GRAM. Section 3 explains the process to obtain the Uranus-GRAM code, the data files, and how to set up and run the program. Appendices A through E provide additional details regarding the Uranus-GRAM input and output files. Appendix F provides a history of Uranus-GRAM revisions.

atmospheric models↗
NASA NTRS1980

Shuttle Simulation Turbulence Tapes SSTT users guide

A guide for potential users of Shuttle Simulation Turbulence Tapes is presented. It provides an appropriate description of the characteristics of the simulated turbulence stored on the tapes as well as instructions regarding their proper use. The characteristics of the turbulence series, including the spectral shape, cutoff frequencies, and variation of turbulence parameters with altitude, are discussed.

Tatom, F. B.↗
NASA NTRS2020

Neptune Global Reference Atmospheric Model (Neptune-GRAM): User Guide

This Technical Memorandum (TM) presents the Neptune Global Reference Atmospheric Model (Neptune-GRAM) and its updated features. Neptune-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Neptune. This TM summarizes the atmospheric data model in Neptune-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Neptune-GRAM input and output files and how to interpret Neptune-GRAM results are also provided.

H L Justh↗
NASA NTRS2020

Titan Global Reference Atmospheric Model (Titan-GRAM): User Guide

This Technical Memorandum summarizes the atmospheric data model in Titan-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Section 2 describes the input atmospheric data files and how they are used in Titan-GRAM. Section 3 explains the process to obtain the Titan-GRAM code and data files and how to set up and run the program. Appendices A through E provide additional details regarding the Titan-GRAM input and output files. Appendix F provides a history of Titan-GRAM revisions.

Titan Global Reference Atmospheric Model,↗
NASA NTRS2021

Uranus Global Reference Atmospheric Model (Uranus-GRAM): User Guide

This Technical Memorandum (TM) presents the Uranus Global Reference Atmospheric Model (Uranus-GRAM) and the updated features of the GRAMs. Uranus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Uranus. This TM summarizes the atmospheric data model in Uranus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Uranus-GRAM input and output files and how to interpret Uranus-GRAM results are also provided.

Uranus Global Reference Atmospheric Model↗
NASA NTRS2021

Jupiter Global Reference Atmospheric Model (Jupiter-GRAM): User Guide

This Technical Memorandum (TM) presents the Jupiter Global Reference Atmospheric Model (Jupiter-GRAM) and the updated features of the GRAMs. Jupiter-GRAM is an engineering-oriented atmospheric model that estimates mean values of atmospheric properties for Jupiter. This TM summarizes the atmospheric data model in Jupiter-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Jupiter-GRAM input and output files and how to interpret Jupiter-GRAM results are also provided.

atmospheric models↗
NASA NTRS2021

Earth Global Reference Atmospheric Model (Earth-GRAM): User Guide

This Technical Memorandum (TM) presents the Earth Global Reference Atmospheric Model (Earth-GRAM) and the updated features of the GRAMs. Earth-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Earth. This TM summarizes the atmospheric data model in Earth-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Earth-GRAM input and output files and how to interpret Earth-GRAM results are also provided.

Atmospheric Models↗
NASA NTRS2021

Venus Global Reference Atmospheric Model (Venus-GRAM): User Guide

This Technical Memorandum (TM) presents the Venus Global Reference Atmospheric Model (Venus-GRAM) and the updated features of the GRAMs. Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Venus. This TM summarizes the atmospheric data model in Venus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Venus-GRAM input and output files and how to interpret Venus-GRAM results are also provided.

atmospheric models↗
NASA NTRS2021

Mars Global Reference Atmospheric Model (Mars-GRAM): User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) and the updated features of the GRAMs. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric models↗
NASA NTRS2024

Mars Global Reference Atmospheric Model (Mars-GRAM) 2024: User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) 2024 and its updated features. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric density↗
NASA NTRS2006

User Guide for Compressible Flow Toolbox Version 2.1 for Use With MATLAB(Registered Trademark); Version 7

This report provides a user guide for the Compressible Flow Toolbox, a collection of algorithms that solve almost 300 linear and nonlinear classical compressible flow relations. The algorithms, implemented in the popular MATLAB programming language, are useful for analysis of one-dimensional steady flow with constant entropy, friction, heat transfer, or shock discontinuities. The solutions do not include any gas dissociative effects. The toolbox also contains functions for comparing and validating the equation-solving algorithms against solutions previously published in the open literature. The classical equations solved by the Compressible Flow Toolbox are: isentropic-flow equations, Fanno flow equations (pertaining to flow of an ideal gas in a pipe with friction), Rayleigh flow equations (pertaining to frictionless flow of an ideal gas, with heat transfer, in a pipe of constant cross section.), normal-shock equations, oblique-shock equations, and Prandtl-Meyer expansion equations. At the time this report was published, the Compressible Flow Toolbox was available without cost from the NASA Software Repository.

Melcher, Kevin J.↗
NASA NTRS1990

Satellite radar altimetry over ice. Volume 4: Users' guide for Antarctica elevation data from Seasat

A gridded surface-elevation data set and a geo-referenced data base for the Seasat radar altimeter data over Greenland are described. This is a user guide to accompany the data provided to data centers and other users. The grid points are on a polar stereographic projection with a nominal spacing of 20 km. The gridded elevations are derived from the elevation data in the geo-referenced data base by a weighted fitting of a surface in the neighborhood of each grid point. The gridded elevations are useful for the creating of large-scale contour maps, and the geo-referenced data base is useful for regridding, creating smaller-scale contour maps, and examinating individual elevation measurements in specific geographic areas. Tape formats are described, and a FORTRAN program for reading the data tape is listed and provided on the tape.

Zwally, H. Jay↗