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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Rapid Model Import Tool (RMIT)

Our project is about developing a tool to implement conversion of 3D Computer Aided Design (CAD) models produced with software such as Delmia, 3DS Max, or Maya, into a size and format compatible with the Unity 3D environment. RMIT will be used to aid KSC engineering personnel in the design, development, testing, operations, and training on spacecraft, launch vehicles, facilities, and ground support equipment. For our project, we are using Blender, a free/open-source 3D graphics software, with the goal of developing, testing, and deploying a 3D CAD model converter tool. I worked on using Blender to import 3D CAD models exported from CATIA software into Collada file format. The Collada file format has file extension DAE. Importing the Collada DAE file as is into Blender, generates dots and dashes. In 3DS Max, there is an existing OpenCollada plugin and with that plugin, 3DS Max can import the DAE file successfully. But, Blender does not seem to have an OpenCollada plugin, so I worked on writing a new OpenCollada plugin for Blender. Since 3DS Max was able to display the image, I looked into comparing differences between the original DAE file and the DAE file exported from 3DS Max using the OpenCollada plugin. As Collada documents describing digital assets are XML files with file extension DAE, Collada files contains XML tags, making them easily modifiable. After some research, it appears that Blender does not like primitive 2D tags like tristrips and trifans. Changing those tags to polygons slightly improved the image, but the pieces were exploded. I found after further research comparing differences between the original file and the file exported from 3DS Max that the values inside the translate tags in the original file are scaled down by a factor of 25.4 in the exported file from 3DS Max, representing the millimeters to inches conversion (1 inch = 25.4 millimeters). After scaling down values inside all of the translate tags by 25.4, the exploded pieces stuck back in, but the image needed further improvement. I have been able to create a new plugin in Blender that takes the original DAE file, replaces the primitive 2D tags tristrips and trifans with polygons, scales down the values inside the translate tags by a factor of 25.4, and saves the changes into a temporary DAE file. After the temporary DAE file is imported into Blender, the temp file is then deleted, keeping the original DAE file intact. Starting with a DAE file that is exported using the NASA Enterprise Visualization Application (NEVA), a Collada exporter, from CATIA gives better results. NEVA is a Design Visualization product that is used for exporting 3D models from CATIA. With NEVA, the up axis is defined in the top-level node if navigation gravity is enabled. With that file, just replacing the primitive tags tristrips and trifans with polygons in yields a much improved image in Blender. As we identify more differences between the original DAE file and the DAE file exported from 3DS Max, this plugin can be improved further. Our goal is to have a model that is formatted and sized for import into Unity, and we are trying out different 3D programs to see which will work best.

Ayyangar, Arjun↗
NASA NTRS2013

Hyperspectral Imager-Tracker

The Hyperspectral Imager-Tracker (HIT) is a technique for visualization and tracking of low-contrast, fast-moving objects. The HIT architecture is based on an innovative and only recently developed concept in imaging optics. This innovative architecture will give the Light Prescriptions Innovators (LPI) HIT the possibility of simultaneously collecting the spectral band images (hyperspectral cube), IR images, and to operate with high-light-gathering power and high magnification for multiple fast- moving objects. Adaptive Spectral Filtering algorithms will efficiently increase the contrast of low-contrast scenes. The most hazardous parts of a space mission are the first stage of a launch and the last 10 kilometers of the landing trajectory. In general, a close watch on spacecraft operation is required at distances up to 70 km. Tracking at such distances is usually associated with the use of radar, but its milliradian angular resolution translates to 100- m spatial resolution at 70-km distance. With sufficient power, radar can track a spacecraft as a whole object, but will not provide detail in the case of an accident, particularly for small debris in the onemeter range, which can only be achieved optically. It will be important to track the debris, which could disintegrate further into more debris, all the way to the ground. Such fragmentation could cause ballistic predictions, based on observations using high-resolution but narrow-field optics for only the first few seconds of the event, to be inaccurate. No optical imager architecture exists to satisfy NASA requirements. The HIT was developed for space vehicle tracking, in-flight inspection, and in the case of an accident, a detailed recording of the event. The system is a combination of five subsystems: (1) a roving fovea telescope with a wide 30 field of regard; (2) narrow, high-resolution fovea field optics; (3) a Coude optics system for telescope output beam stabilization; (4) a hyperspectral-mutispectral imaging assembly; and (5) image analysis software with effective adaptive spectral filtering algorithm for real-time contrast enhancement.

Agurok, Llya↗
NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗
NASA NTRS2012

Dual-Doppler Feasibility Study

When two or more Doppler weather radar systems are monitoring the same region, the Doppler velocities can be combined to form a three-dimensional (3-D) wind vector field thus providing for a more intuitive analysis of the wind field. A real-time display of the 3-D winds can assist forecasters in predicting the onset of convection and severe weather. The data can also be used to initialize local numerical weather prediction models. Two operational Doppler Radar systems are in the vicinity of Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS); these systems are operated by the 45th Space Wing (45 SW) and the National Weather Service Melbourne, Fla. (NWS MLB). Dual-Doppler applications were considered by the 45 SW in choosing the site for the new radar. Accordingly, the 45th Weather Squadron (45 WS), NWS MLB and the National Aeronautics and Space Administration tasked the Applied Meteorology Unit (AMU) to investigate the feasibility of establishing dual-Doppler capability using the two existing systems. This study investigated technical, hardware, and software requirements necessary to enable the establishment of a dual-Doppler capability. Review of the available literature pertaining to the dual-Doppler technique and consultation with experts revealed that the physical locations and resulting beam crossing angles of the 45 SW and NWS MLB radars make them ideally suited for a dual-Doppler capability. The dual-Doppler equations were derived to facilitate complete understanding of dual-Doppler synthesis; to determine the technical information requirements; and to determine the components of wind velocity from the equation of continuity and radial velocity data collected by the two Doppler radars. Analysis confirmed the suitability of the existing systems to provide the desired capability. In addition, it is possible that both 45 SW radar data and Terminal Doppler Weather Radar data from Orlando International Airport could be used to alleviate any radar geometry issues at the NWS MLB radar, such as the "cone of silence" or beam blockage. In the event of a radar outage at one of the sites, the multi-radar algorithms would provide continuing coverage of the area through use of the data from the remaining operational radar sites. There are several options to collect, edit, synthesize and display dual-Doppler data sets. These options include commercial packages available for purchase and a variety of freeware packages available from the National Center for Atmospheric Research (NCAR) for processing raw radar data. However, evaluation of the freeware packages revealed that they do not have sufficient documentation and configuration control to be certified for 45 SW use. Additionally, a TI data line must be installed/leased from the NWS MLB office and CCAFS to enable the receipt of NWS MLB raw radar data to use in the dual-Doppler synthesis. Integration of the TI data line into the Eastern Range infrastructure that will meet the security requirements necessary for 45 SW use is time-consuming and costly. Overall evaluation indicates that establishment of the dual-Doppler capability using the existing operational radar systems is desirable and feasible with no technical concerns. Installation of such a system represents a significant enhancement to forecasting capabilities at the 45 WS and at NWS MLB. However, data security and cost considerations must be evaluated in light of current budgetary constraints. In any case, gaining the dual-Doppler capability will provide opportunities for better visualization of the wind field and better forecasting of the onset of convection and severe weather events to support space launch operations at KSC and CCAFS.

Huddleston, Lisa L.↗
NASA NTRS2014

CEO Sites Mission Management System (SMMS)

Late in fiscal year 2011, the Crew Earth Observations (CEO) team was tasked to upgrade its science site database management tool, which at the time was integrated with the Automated Mission Planning System (AMPS) originally developed for Earth Observations mission planning in the 1980s. Although AMPS had been adapted and was reliably used by CEO for International Space Station (ISS) payload operations support, the database structure was dated, and the compiler required for modifications would not be supported in the Windows 7 64-bit operating system scheduled for implementation the following year. The Sites Mission Management System (SMMS) is now the tool used by CEO to manage a heritage Structured Query Language (SQL) database of more than 2,000 records for Earth science sites. SMMS is a carefully designed and crafted in-house software package with complete and detailed help files available for the user and meticulous internal documentation for future modifications. It was delivered in February 2012 for test and evaluation. Following acceptance, it was implemented for CEO mission operations support in April 2012. The database spans the period from the earliest systematic requests for astronaut photography during the shuttle era to current ISS mission support of the CEO science payload. Besides logging basic image information (site names, locations, broad application categories, and mission requests), the upgraded database management tool now tracks dates of creation, modification, and activation; imagery acquired in response to requests; the status and location of ancillary site information; and affiliations with studies, their sponsors, and collaborators. SMMS was designed to facilitate overall mission planning in terms of site selection and activation and provide the necessary site parameters for the Satellite Tool Kit (STK) Integrated Message Production List Editor (SIMPLE), which is used by CEO operations to perform daily ISS mission planning. The CEO team uses the SMMS for three general functions - database queries of content and status, individual site creation and updates, and mission planning. The CEO administrator of the science site database is able to create or modify the content of sites and activate or deactivate them based on the requirements of the sponsors. The administrator supports and implements ISS mission planning by assembling, reporting, and activating mission-specific site selections for management; deactivating sites as requirements are met; and creating new sites, such as International Charter sites for disasters, as circumstances warrant. In addition to the above CEO internal uses, when site planning for a specific ISS mission is complete and approved, the SMMS can produce and export those essential site database elements for the mission into XML format for use by onboard Earth-location systems, such as Worldmap. The design, development, and implementation of the SMMS resulted in a superior database management system for CEO science sites by focusing on the functions and applications of the database alone instead of integrating the database with the multipurpose configuration of the AMPS. Unlike the AMPS, it can function and be modified within the existing Windows 7 environment. The functions and applications of the SMMS were expanded to accommodate more database elements, report products, and a streamlined interface for data entry and review. A particularly elegant enhancement in data entry was the integration of the Google Earth application for the visual display and definition of site coordinates for site areas defined by multiple coordinates. Transfer between the SMMS and Google Earth is accomplished with a Keyhole Markup Language (KML) expression of geographic data (see figures 3 and 4). Site coordinates may be entered into the SMMS panel directly for display in Google Earth, or the coordinates may be defined on the Google Earth display as a mouse-controlled polygonal definition and transferred back into the SMMS as KML input. This significantly reduces the possibility of errors in coordinate entries and provides visualization of the scale of the site being defined. CEO now has a powerful tool for managing and defining sites on the Earth's surface for both targets of astronaut photography or other onboard remote sensing systems. It can also record and track results by sponsor, collaborator, or type of study.

Trenchard, Mike↗
NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗