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At least 253 records · Page 14

Update on Integrated Optical Design Analyzer

Updated information on the Integrated Optical Design Analyzer (IODA) computer program has become available. IODA was described in Software for Multidisciplinary Concurrent Optical Design (MFS-31452), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 8a. To recapitulate: IODA facilitates multidisciplinary concurrent engineering of highly precise optical instruments. The architecture of IODA was developed by reviewing design processes and software in an effort to automate design procedures. IODA significantly reduces design iteration cycle time and eliminates many potential sources of error. IODA integrates the modeling efforts of a team of experts in different disciplines (e.g., optics, structural analysis, and heat transfer) working at different locations and provides seamless fusion of data among thermal, structural, and optical models used to design an instrument. IODA is compatible with data files generated by the NASTRAN structural-analysis program and the Code V (Registered Trademark) optical-analysis program, and can be used to couple analyses performed by these two programs. IODA supports multiple-load-case analysis for quickly accomplishing trade studies. IODA can also model the transient response of an instrument under the influence of dynamic loads and disturbances.

Moore, James D., Jr.↗

Flight Planning Branch Space Shuttle Lessons Learned

Planning products and procedures that allow the mission flight control teams and the astronaut crews to plan, train and fly every Space Shuttle mission have been developed by the Flight Planning Branch at the NASA Johnson Space Center. As the Space Shuttle Program ends, lessons learned have been collected from each phase of the successful execution of these Shuttle missions. Specific examples of how roles and responsibilities of console positions that develop the crew and vehicle attitude timelines will be discussed, as well as techniques and methods used to solve complex spacecraft and instrument orientation problems. Additionally, the relationships and procedural hurdles experienced through international collaboration have molded operations. These facets will be explored and related to current and future operations with the International Space Station and future vehicles. Along with these important aspects, the evolution of technology and continual improvement of data transfer tools between the shuttle and ground team has also defined specific lessons used in the improving the control teams effectiveness. Methodologies to communicate and transmit messages, images, and files from Mission Control to the Orbiter evolved over several years. These lessons have been vital in shaping the effectiveness of safe and successful mission planning that have been applied to current mission planning work in addition to being incorporated into future space flight planning. The critical lessons from all aspects of previous plan, train, and fly phases of shuttle flight missions are not only documented in this paper, but are also discussed as how they pertain to changes in process and consideration for future space flight planning.

Price, Jennifer B.↗

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗

Glenn Heat Transfer Simulation and Solver Graphical User Interface: Development and Testing

In the Tui ine Branch of the Turbomachinery and Propulsion Systems Division, researching and developing efficient turbine aerothermodynamics technologies is the main objective. Creating effective turbines for jet engines is a process which, if based purely on physical experimental testing, would be extremely expensive. It is for this reason, and also for the reasons of speed and ease, that the Turbine Branch spends a large amount of effort working with simulations of turbines. Specifically, they focus their work on two main fields: Computational Field Dynamics (CFD), and Experimental data analysis. The experimental field involves comparing experimental results to simulated results, whereas the CFD field involves running these simulations. The simulations are applied to aerodynamics and heat transfer cases, for both steady and unsteady flow conditions. By and large this work is applied to the domain of flow and heat transfer in axial turbines. The main application used to run these heat flow simulations is GlennHT. This program, recently rewritten in FORTRAN 90, allows the user to input a job file which specifies all the necessary parameters needed to simulate flow through a user-defined grid. There are several other executables used as well, ranging in application from converting grid files to and from particular formats, to merging blocks in a connectivity file, to converting connectivity files to a GlennHT compatible format. All of these executables are run from the command line in a terminal; some of them have interactive prompts where the user must specify the files to be manipulated after the program starts, while others take all of their parameters from the command line. With this amount of variation comes a good deal of commands and formats to memorize, which can cause slower and less efficient work, as users may forget how to execute a certain program, or not remember the pathnames of the files they wish to use. Two years ago, steps were made to expedite this process with a graphical user interface (GUI) that combines the functionality of all the executables along with adding some new functionality, such as residuals graphing and boundary conditions creation. Upon my beginning here at Glenn, many parts of the GUI, which was developed in Java, were nonfunctional. There were also issues with cross-platforming, as systems in the branch were transitioning from Silicon Graphics (SGI) machines to Linux machines. My goals this summer are to finish the parts of the GUI that are not yet completed, fix parts that did not work correctly, expand the functionality to include other useful features, such as grid surface highlighting, and make the system compatible with both Linux and SGI. I will also be heavily testing the system and providing sufficient documentation on how to use the GUI, as no such documentation existed previously.

Kardamis, Joseph R.↗

NASA Flight Planning Branch Space Shuttle Lessons Learned

Planning products and procedures that allowed the mission Flight Control Teams and the Astronaut crews to plan, train and fly every Space Shuttle mission were developed by the Flight Planning Branch at the NASA Johnson Space Center in Houston, Texas. As the Space Shuttle Program came to a close, lessons learned were collected from each phase of the successful execution of these Space Shuttle missions. Specific examples of how roles and responsibilities of console positions that develop the crew and vehicle attitude timelines have been analyzed and will be discussed. Additionally, the relationships and procedural hurdles experienced through international collaboration have molded operations. These facets will be explored and related to current and future operations with the International Space Station and future vehicles. Along with these important aspects, the evolution of technology and continual improvement of data transfer tools between the Space Shuttle and ground team has also defined specific lessons used in improving the control team s effectiveness. Methodologies to communicate and transmit messages, images, and files from the Mission Control Center to the Orbiter evolved over several years. These lessons were vital in shaping the effectiveness of safe and successful mission planning and have been applied to current mission planning work in addition to being incorporated into future space flight planning. The critical lessons from all aspects of previous plan, train, and fly phases of Space Shuttle flight missions are not only documented in this paper, but are also discussed regarding how they pertain to changes in process and consideration for future space flight planning.

Clevenger, Jennifer D.↗

Regional technology transfer program

The continuing operation is reported of a jointly state- and NASA-sponsored Regional Dissemination Center serving the southeastern United States. The NC/STRC offers automated searching of large information collections, such as that assembled by NASA, with emphasis on textile-related files to serve regional industry. During this period, NC/STRC conducted an in-depth analysis of its marketing programs and prepared a series of brochures aimed at various segments of industry. Heavy emphasis was also placed on the Library Search Service inaugurated by NC/STRC, and a total of 32 universities now participate in this service. Smaller schools are served through the university network. Although the nationwide industrial recession caused a general drop in search requests, NC/STRC processed a total of 838 retrospective searches during this period: 39.97% for its industrial clients, 22.9% for university libraries, and 37.1% for other RDC's.

Source record↗

Electromagnetic scattering calculations on the Intel Touchstone Delta

During the first year's operation of the Intel Touchstone Delta system, software which solves the electric field integral equations for fields scattered from arbitrarily shaped objects has been transferred to the Delta. To fully realize the Delta's resources, an out-of-core dense matrix solution algorithm that utilizes some or all of the 90 Gbyte of concurrent file system (CFS) has been used. The largest calculation completed to date computes the fields scattered from a perfectly conducting sphere modeled by 48,672 unknown functions, resulting in a complex valued dense matrix needing 37.9 Gbyte of storage. The out-of-core LU matrix factorization algorithm was executed in 8.25 h at a rate of 10.35 Gflops. Total time to complete the calculation was 19.7 h-the additional time was used to compute the 48,672 x 48,672 matrix entries, solve the system for a given excitation, and compute observable quantities. The calculation was performed in 64-b precision.

Cwik, Tom↗

BOREAS TE-9 NSA Canopy Biochemistry

The BOREAS TE-9 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJR, OBS, UBS, and OA sites, including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

Orion Script Generator

NASA Engineering's Orion Script Generator (OSG) is a program designed to run on Exploration Flight Test One Software. The script generator creates a SuperScript file that, when run, accepts the filename for a listing of Compact Unique Identifiers (CUIs). These CUIs will correspond to different variables on the Orion spacecraft, such as the temperature of a component X, the active or inactive status of another component Y, and so on. OSG will use a linked database to retrieve the value for each CUI, such as "100 05," "True," and so on. Finally, OSG writes SuperScript code to display each of these variables before outputting the ssi file that allows recipients to view a graphical representation of Orion Flight Test One's status through these variables. This project's main challenge was creating flexible software that accepts and transfers many types of data, from Boolean (true or false) values to "Unsigned Long Long'' values (any number from 0 to 18,446,744,073,709,551,615). We also needed to allow bit manipulation for each variable, requiring us to program functions that could convert any of the multiple types of data into binary code. Throughout the project, we explored different methods to optimize the speed of working with the CUI database and long binary numbers. For example, the program handled extended binary numbers much more efficiently when we stored them as collections of Boolean values (true or false representing 1 or 0) instead of as collections of character strings or numbers. We also strove to make OSG as user-friendly and accommodating of different needs as possible its default behavior is to display a current CUI's maximum value and minimum value with three to five intermediate values in between, all in descending order. Fortunately, users can also add other input on the same lines as each CUI name to request different high values, low values, display options (ascending, sine, and so on), and interval sizes for generating intermediate values. Developing input validation took up quite a bit of time, but OSG's flexibility in the end was worth it.

Dooling, Robert J.↗

Earth feature identification and tracking technology development

The paper discusses needs for smart sensing in terrestrial and atmospheric remote sensing as related to current technology and a scheduled Shuttle experiment. An approach is outlined involving Shuttle-borne experiments to develop earth feature identification and tracking technology including a Feature Identification and Location Experiment (FILE) scheduled for flight on the NASA Shuttle with an objective of classifying earth features into categories of bare land, water, vegetation, and clouds, snow, and ice. The plan for evolution of the FILE-related technology leads to capabilities for pointing instruments to predetermined sites, reacquiring earth features or landmarks, and tracking features such as coastlines and rivers. Technology concepts relative to an overall system transfer function is discussed, and the development status outlined.

Wilson, R. G.↗

BOREAS HYD-3 Tree Measurements

The BOREAS HYD-3 team collected several data sets related to the hydrology of forested areas. This data set contains measurements of canopy density (closure), stem density, and DBH from a variety of sites. Canopy density measurements were made during the FFC-W and FFC-T 1994 in both the SSA and the NSA. Stem density measurements were made during FFC-W 1996 in the SSA only. Canopy density measurements were made using a forest densiometer, while measurements of stem density and DBH were made using standard techniques. This study was undertaken to predict spatial distributions of energy transfer, snow properties important to the hydrology, remote sensing signatures, and transmissivity of gases through the snow and their relation to forests in boreal ecosystems. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hardy, Janet P.↗

A regional technology transfer program

The final report is presented for the North Carolina Science and Technology Research Center's 14th consecutive contract period as a NASA Industrial Applications Center, serving the information needs of nine Southeastern states. Included in the report are figures for and analysis of marketing efforts, file usage, search delivered, and other services performed for clients; and information on staff changes, workshops, and special projects in 1978. An appendix contains copies of NC/STRC magazine advertisements, letters from clients, and supplementary information on NC/STRC staff and services.

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AirShow 1.0 CFD Software Users' Guide

AirShow is visualization post-processing software for Computational Fluid Dynamics (CFD). Upon reading binary PLOT3D grid and solution files into AirShow, the engineer can quickly see how hundreds of complex 3-D structured blocks are arranged and numbered. Additionally, chosen grid planes can be displayed and colored according to various aerodynamic flow quantities such as Mach number and pressure. The user may interactively rotate and translate the graphical objects using the mouse. The software source code was written in cross-platform Java, C++, and OpenGL, and runs on Unix, Linux, and Windows. The graphical user interface (GUI) was written using Java Swing. Java also provides multiple synchronized threads. The Java Native Interface (JNI) provides a bridge between the Java code and the C++ code where the PLOT3D files are read, the OpenGL graphics are rendered, and numerical calculations are performed. AirShow is easy to learn and simple to use. The source code is available for free from the NASA Technology Transfer and Partnership Office.

Mohler, Stanley R., Jr.↗

Transferring data objects: A focused Ada investigation

The use of the Ada language does not guarantee that data objects will be in the same form or have the same value after they have been stored or transferred to another system. There are too many possible variables in such things as the formats used and other protocol conditions. Differences may occur at many different levels of support. These include program level, object level, application level, and system level. A standard language is only one aspect of making a complex system completely homogeneous. Many components must be standardized and the various standards must be integrated. The principal issues in providing for interaction between systems are of exchanging files and data objects between systems which may not be compatible in terms of their host computer, operating system or other factors. A typical resolution of the problem of invalidating data involves at least a common external form, for data objects and for representing the relationships and attributes of data collections. Some of the issues dealing with the transfer of data are listed and consideration is given on how these issues may be handled in the Ada language.

Legrand, Sue↗

Longitudinal and transverse magnetic field program procedure and detailed specification for Sigma 5

A computer program and procedure for plotting the contour of the data transferred from the Marshall Space Flight Center solar magnetography is presented. The plotted data then can be easily compared with solar data from other sources, such as the Solar Maximum Mission. From the data file for circular polarization the longitudinal program plots the contours for filtered longitudinal plot and intensity plot by choosing the positive and negative contour levels, intensity levels, and also X,Y plotting ranges which need to be used. In a similar manner the transverse program generates the transverse contour plot, azimuth plot, and intensity plot from the linear polarization data files.

Wang, C. K.↗

FAST User Guide

The Flow Analysis Software Toolkit, FAST, is a software environment for visualizing data. FAST is a collection of separate programs (modules) that run simultaneously and allow the user to examine the results of numerical and experimental simulations. The user can load data files, perform calculations on the data, visualize the results of these calculations, construct scenes of 3D graphical objects, and plot, animate and record the scenes. Computational Fluid Dynamics (CFD) visualization is the primary intended use of FAST, but FAST can also assist in the analysis of other types of data. FAST combines the capabilities of such programs as PLOT3D, RIP, SURF, and GAS into one environment with modules that share data. Sharing data between modules eliminates the drudgery of transferring data between programs. All the modules in the FAST environment have a consistent, highly interactive graphical user interface. Most commands are entered by pointing and'clicking. The modular construction of FAST makes it flexible and extensible. The environment can be custom configured and new modules can be developed and added as needed. The following modules have been developed for FAST: VIEWER, FILE IO, CALCULATOR, SURFER, TOPOLOGY, PLOTTER, TITLER, TRACER, ARCGRAPH, GQ, SURFERU, SHOTET, and ISOLEVU. A utility is also included to make the inclusion of user defined modules in the FAST environment easy. The VIEWER module is the central control for the FAST environment. From VIEWER, the user can-change object attributes, interactively position objects in three-dimensional space, define and save scenes, create animations, spawn new FAST modules, add additional view windows, and save and execute command scripts. The FAST User Guide uses text and FAST MAPS (graphical representations of the entire user interface) to guide the user through the use of FAST. Chapters include: Maps, Overview, Tips, Getting Started Tutorial, a separate chapter for each module, file formats, and system administration.

Walatka, Pamela P.↗

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗