A Spreadsheet for the Mixing of Rows of Jets with a Confined Crossflow in a Rectangular Duct: Supplement to NASA/TM-2006-214226
No abstract available
Holdeman, James D.↗
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There and Back Again - Connecting Assurance Statements to Analysis Spreadsheets in Support of Evidence Based Assurance for the Ground Systems Development and Operation Program
No abstract available
evidence-based assurance↗
The Lewice Console
Lewice (LEWis ICE accretion program) is software used by literally hundreds of users in the aeronautics community for predicting ice shapes, collections efficiencies, and anti-icing heat requirements for aircraft. LEWICE performs its analysis in minutes on a desktop PC, allowing the user to run several parameter studies for design purposes. The ice shape predictions have been used to assess performance degradation both as an input to a CFD program or experimentally in flight or in a wind tunnel. This information is important to ensure an airplane s safe passage through an icing cloud. Currently, Lewice runs as a DOS program that accepts many different inputs such as cloud conditions, wing shapes, and thermal deicing inputs. Usually, such experimental data is stored in spreadsheets. However, Lewice inputs are text files; therefore, they must be generated by the user. Lewice s outputs (collection efficiency, ice shapes and thicknesses) are also text files; to plot the data, users must generate a spreadsheet with this output. Because all Lewice J/O is in the form of text files, using Lewice can be tricky and time-consuming. Our goal was to improve Lewice s usability by creating a user interface that would automatically generate Lewice input from a spreadsheet and automatically put Lewice output into spreadsheets with charts. Additionally, this user interface would automatically convert units (as Lewice only accepts input in certain units) and offer several output options. I call this program the Lewice Console. The Lewice Console is an easy to use interface for Lewice written in Visual Basic. It allows users to run Lewice given a spreadsheet listing experimental conditions. It automatically generates the input to Lewice, does necessary unit conversions, runs Lewice, and produces a spreadsheet with charts plotting the data. It allows users to import data from previously generated Lewice inputs into a spreadsheet. It also allows users to batch run Lewice on several different inputs to automatically generate multiple output spreadsheets. You can also generate plots of actual data vs. experimental data. These capabilities are just the beginning for the Lewice Console. Lewice is capable of running a full deicing experiment given a geometry and heating apparatus information. However, users find it difficult to run such experiments due to the number of inputs and the difficult input file format. The Lewice Console would simplify experiment generation by allowing the user to interactively draw a geometry, place heating apparatus, and specify information about each part. The input to Lewice would be automatically generated from the experiment the user draws on the screen. The Lewice Console would simplify the experiment building process. Currently, Lewice runs as a DOS program that accepts many different inputs such as
Armstrong, Aaron E.↗
Definition and maintenance of a telemetry database dictionary
A telemetry dictionary database includes a component for receiving spreadsheet workbooks of telemetry data over a web-based interface from other computer devices. Another component routes the spreadsheet workbooks to a specified directory on the host processing device. A process then checks the received spreadsheet workbooks for errors, and if no errors are detected the spreadsheet workbooks are routed to another directory to await initiation of a remote database loading process. The loading process first converts the spreadsheet workbooks to comma separated value (CSV) files. Next, a network connection with the computer system that hosts the telemetry dictionary database is established and the CSV files are ported to the computer system that hosts the telemetry dictionary database. This is followed by a remote initiation of a database loading program. Upon completion of loading a flatfile generation program is manually initiated to generate a flatfile to be used in a mission operations environment by the core ground system.
Knopf, William P.↗
Engine Icing Data - An Analytics Approach
Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.
Engine Icing↗
LOTUS 123 - A tool for modelling and simulation of spaceborne sensor performance
LOTUS 123 is used for modeling and simulation of the performance characteristics of spaceborne sensors. Using a spreadsheet, input and output parameters can be displayed and modified with a flexibility that would be difficult to achieve using standard programming languages such as FORTRAN or 'C'. Spreadsheets also provide both display and hardcopy output capabilities to assist in visualizing the results of computations. Macros can be developed to perform looping and logical comparisons, and many new spreadsheets allow linking to subroutines written in FORTRAN or 'C'. Tradeoff analyses are performed to arrive at sensor designs with optimal SNR and resolution. Examples of macros and types of computations are discussed with general considerations for spreadsheet layout and design.
Montgomery, Harry E.↗
NASA/NOAA: Earth Science Electronic Theater 1999
The Electronic Theater (E-theater) presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization and Analysis Laboratory (VAL/912), and Scientific Visualization Studio (SVS/930), as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science E-Theater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April '98 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; and others will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach. Many of these visualizations have been widely disseminated through the world wide web pages of the HPCC/LTP/RSD program which can be found at http://rsd.gsfc.nasa.gov/rsd The one min interval animations of Hurricane Luis on ABC Nightline and the color perspective rendering of Hurricane Fran published by TIME, LIFE, Newsweek, Popular Science, National Geographic, Scientific American, and the "Weekly Reader" are some of the examples which will be shown.
Hasler, A. Fritz↗
NASA/NOAA: Earth Science Electronic Theater 1999. Earth Science Observations, Analysis and Visualization: Roots in the 60s - Vision for the Next Millennium
The Etheater presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966, to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA''s visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science ETheater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April 198 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; etc. will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach.
Hasler, A. Fritz↗
Simplifying CEA through Excel, VBA, and Subeq
Many people use compound equilibrium programs for very different reasons, varying from refrigerators to light bulbs to rockets. A commonly used equilibrium program is CEA. CEA can take various inputs such as pressure, temperature, and volume along with numerous reactants and run them through equilibrium equations to obtain valuable output information, including products formed and their relative amounts. A little over a year ago, Bonnie McBride created the program subeq with the goal to simplify the calling of CEA. Subeq was also designed to be called by other programs, including Excel, through the use of Visual Basic for Applications (VBA). The largest advantage of using Excel is that it allows the user to input the information in a colorful and user-friendly environment while allowing VBA to run subeq, which is in the form of a FORTRAN DLL (Dynamic Link Library). Calling subeq in this form makes it much faster than if it were converted to VBA. Since subeq requires such large lists of reactant and product names, all of which can't be passed in as an array, subeq had to be changed to accept very long strings of reactants and products. To pass this string and adjust the transfer of input and output parameters, the subeq DLL had to be changed. One program that does this is Compaq Visual FORTRAN, which allows DLLs to be edited, debugged, and compiled. Compaq Visual FORTRAN uses FORTRAN 90/95, which has additional features to that of FORTRAN 77. My goals this summer include finishing up the excel spreadsheet of subeq, which I started last summer, and putting it on the Internet so that others can use it without having to download my spreadsheet. To finish up the spreadsheet I will need to work on debugging current options and problems. I will also work on making it as robust as possible, so that all errors that may arise will be clearly communicated to the user. New features will be added old ones will be changed as I receive comments from people using the spreadsheet. To implement this onto the Internet, I will need to develop an XML input/output format and learn how to write HTML.
Foster, Ryan↗
Station Program Note Pull Automation
Upon commencement of my internship, I was in charge of maintaining the CoFR (Certificate of Flight Readiness) Tool. The tool acquires data from existing Excel workbooks on NASA's and Boeing's databases to create a new spreadsheet listing out all the potential safety concerns for upcoming flights and software transitions. Since the application was written in Visual Basic, I had to learn a new programming language and prepare to handle any malfunctions within the program. Shortly afterwards, I was given the assignment to automate the Station Program Note (SPN) Pull process. I developed an application, in Python, that generated a GUI (Graphical User Interface) that will be used by the International Space Station Safety & Mission Assurance team here at Johnson Space Center. The application will allow its users to download online files with the click of a button, import SPN's based on three different pulls, instantly manipulate and filter spreadsheets, and compare the three sources to determine which active SPN's (Station Program Notes) must be reviewed for any upcoming flights, missions, and/or software transitions. Initially, to perform the NASA SPN pull (one of three), I had created the program to allow the user to login to a secure webpage that stores data, input specific parameters, and retrieve the desired SPN's based on their inputs. However, to avoid any conflicts with sustainment, I altered it so that the user may login and download the NASA file independently. After the user has downloaded the file with the click of a button, I defined the program to check for any outdated or pre-existing files, for successful downloads, to acquire the spreadsheet, convert it from a text file to a comma separated file and finally into an Excel spreadsheet to be filtered and later scrutinized for specific SPN numbers. Once this file has been automatically manipulated to provide only the SPN numbers that are desired, they are stored in a global variable, shown on the GUI, and transferred over to a new Excel worksheet for comparison. I managed to get my application to acquire the CSWG (Computer Safety Working Group) and the SPNWG (Space Station Working Group) SPN's with just two mouse clicks for each pull, as opposed to several from the original process. When all three pulls are performed, an Excel sheet containing all three different results will be generated for the user to compare and determine which SPN's will be presented or reviewed the following month. The experience from this internship has been spectacular. As a high school senior who will begin attending college in the fall, this internship has been both educationally and occupationally beneficial. The internship has allowed me the opportunities to learn new programming languages, effectively network with NASA personnel from a variety of departments at JSC, and allowed me to learn new professional skills and etiquette. My internship at NASA's Johnson Space Center has further motivated me to pursue a Master's degree in Software Engineering and strive for a prosperous career with NASA as a civil servant.
Delgado, Ivan↗
Dynamic IT Security Database and Analytics for Launch Control Systems Software
During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.
it↗
Soft X Ray Telescope (SXT) focus error analysis
The analysis performed on the soft x-ray telescope (SXT) to determine the correct thickness of the spacer to position the CCD camera at the best focus of the telescope and to determine the maximum uncertainty in this focus position due to a number of metrology and experimental errors, and thermal, and humidity effects is presented. This type of analysis has been performed by the SXT prime contractor, Lockheed Palo Alto Research Lab (LPARL). The SXT project office at MSFC formed an independent team of experts to review the LPARL work, and verify the analysis performed by them. Based on the recommendation of this team, the project office will make a decision if an end to end focus test is required for the SXT prior to launch. The metrology and experimental data, and the spreadsheets provided by LPARL are used at the basis of the analysis presented. The data entries in these spreadsheets have been verified as far as feasible, and the format of the spreadsheets has been improved to make these easier to understand. The results obtained from this analysis are very close to the results obtained by LPARL. However, due to the lack of organized documentation the analysis uncovered a few areas of possibly erroneous metrology data, which may affect the results obtained by this analytical approach.
Ahmad, Anees↗
A simple node and conductor data generator for SINDA
This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.
Gottula, Ronald R.↗
Integrated developmental model of life-support capabilities in wheat
The objective of this project was to develop a model for CO2, O2, H2O, and nitrogen use during the life cycle of wheat. Spreadsheets and accompanying graphs were developed to illustrate plant population reactions to environmental parameters established in the Controlled Ecological Life Support System (CELSS) program at Kennedy Space Center, Fl. The spreadsheets and graphs were produced using validated biomass production chamber (BPC) data from BWT931. Conditions of the BPC during the 83 day plant growth period were as follows: The BPC area is 27.8 m(exp 2), volume is 113 m(exp 3). Temperatures during the 83 day plant growth period ranged from 16.3 to 24.8 C during the light cycle (except for day 69, when the minimum and maximum temperatures were 7.7 C and 7.9 C, respectively) and 14.5 C and 23.6 C during the dark cycle (except for day 49, when the minimum and maximum temperatures were 11.1 C and 11.3 C, respectively). Relative humidity was 85 percent for the first seven days of plant growth, and 70 percent thereafter. The plant leaf canopy area was 10 m(exp 2). Presented is a list and explanation of each spreadsheet and accompanying graph(s), conditions under which the data were collected, and formulas used to obtain each result.
Darnell, R. L.↗
Earth Science Multimedia Theater
The presentation will begin with the latest 1998 NASA Earth Science Vision for the next 25 years. A compilation of the 10 days of animations of Hurricane Georges which were supplied daily on NASA to Network television will be shown. NASA's visualizations of Hurricane Bonnie which appeared in the Sept 7 1998 issue of TIME magazine. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1 -min GOES images that will appear in the October BAMS. The visualizations are produced by the Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the "Digital-HyperRes-Panorama" Earth Science ETheater'98 recently presented in Tokyo, Paris and Phoenix. The presentation in Paris used a SGI/CRAY Onyx Infinite Reality Super Graphics Workstation at 2560 X 1024 resolution with dual synchronized video Epson 71 00 projectors on a 20ft wide screen. Earth Science Electronic Theater '999 is being prepared for a December 1 st showing at NASA HQ in Washington and January presentation at the AMS meetings in Dallas. The 1999 version of the Etheater will be triple wide with at resolution of 3840 X 1024 on a 60 ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense Hyperimage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, Hyperimage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing Hyperimage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS).
Hasler, A. F.↗
Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y
During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.
Chambers, L. H.↗
Design of Structurally Efficient Tapered Struts (SETS)
A study was conducted to develop mass efficient composite struts. A closed-form design methodology for composite struts was developed using well established analyses to predict Euler buckling, local wall buckling; compression strength, damage tolerance, and interlaminar shear at geometric gradients. The methodology was coded in a spreadsheet suitable for convenient and rapid sizing of tapered composite struts. This spreadsheet analysis was used to determine the influence of several variables such as material stiffness, strut diameter, and material allowables on strut weight for given loading conditions. The comparison showed that, while the Park Aerospace design method was well suited to preliminary sizing for a conservative design, the closed-form-analyses-based spreadsheet accounts for all possible failure modes and is a good optimum strut design tool. The report concludes with a set of recommendations for future work in analytical design and analysis methodology enhancements.
Ravi Deo↗
Project Assessment Skills Web Application
The purpose of this project is to utilize Ruby on Rails to create a web application that will replace a spreadsheet keeping track of training courses and tasks. The goal is to create a fast and easy to use web application that will allow users to track progress on training courses. This application will allow users to update and keep track of all of the training required of them. The training courses will be organized by group and by user, making readability easier. This will also allow group leads and administrators to get a sense of how everyone is progressing in training. Currently, updating and finding information from this spreadsheet is a long and tedious task. By upgrading to a web application, finding and updating information will be easier than ever as well as adding new training courses and tasks. Accessing this data will be much easier in that users just have to go to a website and log in with NDC credentials rather than request the relevant spreadsheet from the holder. In addition to Ruby on Rails, I will be using JavaScript, CSS, and jQuery to help add functionality and ease of use to my web application. This web application will include a number of features that will help update and track progress on training. For example, one feature will be to track progress of a whole group of users to be able to see how the group as a whole is progressing. Another feature will be to assign tasks to either a user or a group of users. All of these together will create a user friendly and functional web application.
Goff, Samuel J.↗