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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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NASA NTRS2003

Mission interactive scenarion studio for autonomous spacecraft

We propose building a Studio enabling the use of diverse existing mission activity and scenario patterns, the creation of new ones, and the modeling of their effects using existing modeling tools. The core of the Studio is a component-based Type Library, which captures years of mission adaptation patterns in various forms. The Studio works as a content server to capture the developed adaptation knowledge for reuse and provides bridging into different mission uplink implementations, including the Mission Data System [l] (MDS) state/goal machinery. Various activities can be coordinated, controlled, and reused through the Studio's component interface to establish and model a mission scenario. A special component Factory mechanism will be in place to facilitate the adaptation of projects into the Studio. The architecture of the Studio reflects and enforces a division of knowledge and actions into three parts: Model, Controller, Viewer. The Model contains information about (a proposed version of) the spacecraft and mission. The Controller contains logic for constructing scenarios of mission activities. The information in the Model and Controller is principally in the form of reusable patterns. A Viewer can be a simple or complex software system. For example, Apgen [2,3] is one possible viewer, MDS is another. A 3-tiered infrastructure is used for the Studio, reflecting the Model, Controller, Viewer architecture [4,5]. The Studio is useful in pre-phase A of a project by enabling spacecraft design options to be played against desired mission scenarios. In later design phases of a project, the construction and modeling of more detailed scenarios is supported by the Studio.

autonomous spacecraft↗
NASA NTRS2001

Adjustable Autonomy Testbed

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Malin, Jane T.↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗
NASA NTRS2003

XML-Based Generator of C++ Code for Integration With GUIs

An open source computer program has been developed to satisfy a need for simplified organization of structured input data for scientific simulation programs. Typically, such input data are parsed in from a flat American Standard Code for Information Interchange (ASCII) text file into computational data structures. Also typically, when a graphical user interface (GUI) is used, there is a need to completely duplicate the input information while providing it to a user in a more structured form. Heretofore, the duplication of the input information has entailed duplication of software efforts and increases in susceptibility to software errors because of the concomitant need to maintain two independent input-handling mechanisms. The present program implements a method in which the input data for a simulation program are completely specified in an Extensible Markup Language (XML)-based text file. The key benefit for XML is storing input data in a structured manner. More importantly, XML allows not just storing of data but also describing what each of the data items are. That XML file contains information useful for rendering the data by other applications. It also then generates data structures in the C++ language that are to be used in the simulation program. In this method, all input data are specified in one place only, and it is easy to integrate the data structures into both the simulation program and the GUI. XML-to-C is useful in two ways: 1. As an executable, it generates the corresponding C++ classes and 2. As a library, it automatically fills the objects with the input data values.

Hua, Hook↗
NASA NTRS2001

Pre-Hardware Optimization of Spacecraft Image Processing Software Algorithms and Hardware Implementation

Spacecraft telemetry rates have steadily increased over the last decade presenting a problem for real-time processing by ground facilities. This paper proposes a solution to a related problem for the Geostationary Operational Environmental Spacecraft (GOES-8) image processing application. Although large super-computer facilities are the obvious heritage solution, they are very costly, making it imperative to seek a feasible alternative engineering solution at a fraction of the cost. The solution is based on a Personal Computer (PC) platform and synergy of optimized software algorithms and re-configurable computing hardware technologies, such as Field Programmable Gate Arrays (FPGA) and Digital Signal Processing (DSP). It has been shown in [1] and [2] that this configuration can provide superior inexpensive performance for a chosen application on the ground station or on-board a spacecraft. However, since this technology is still maturing, intensive pre-hardware steps are necessary to achieve the benefits of hardware implementation. This paper describes these steps for the GOES-8 application, a software project developed using Interactive Data Language (IDL) (Trademark of Research Systems, Inc.) on a Workstation/UNIX platform. The solution involves converting the application to a PC/Windows/RC platform, selected mainly by the availability of low cost, adaptable high-speed RC hardware. In order for the hybrid system to run, the IDL software was modified to account for platform differences. It was interesting to examine the gains and losses in performance on the new platform, as well as unexpected observations before implementing hardware. After substantial pre-hardware optimization steps, the necessity of hardware implementation for bottleneck code in the PC environment became evident and solvable beginning with the methodology described in [1], [2], and implementing a novel methodology for this specific application [6]. The PC-RC interface bandwidth problem for the class of applications with moderate input-output data rates but large intermediate multi-thread data streams has been addressed and mitigated. This opens a new class of satellite image processing applications for bottleneck problems solution using RC technologies. The issue of a science algorithm level of abstraction necessary for RC hardware implementation is also described. Selected Matlab functions already implemented in hardware were investigated for their direct applicability to the GOES-8 application with the intent to create a library of Matlab and IDL RC functions for ongoing work. A complete class of spacecraft image processing applications using embedded re-configurable computing technology to meet real-time requirements, including performance results and comparison with the existing system, is described in this paper.

Kizhner, Semion↗
NASA NTRS2013

Sample Analysis at Mars Instrument Simulator

The Sample Analysis at Mars Instrument Simulator (SAMSIM) is a numerical model dedicated to plan and validate operations of the Sample Analysis at Mars (SAM) instrument on the surface of Mars. The SAM instrument suite, currently operating on the Mars Science Laboratory (MSL), is an analytical laboratory designed to investigate the chemical and isotopic composition of the atmosphere and volatiles extracted from solid samples. SAMSIM was developed using Matlab and Simulink libraries of MathWorks Inc. to provide MSL mission planners with accurate predictions of the instrument electrical, thermal, mechanical, and fluid responses to scripted commands. This tool is a first example of a multi-purpose, full-scale numerical modeling of a flight instrument with the purpose of supplementing or even eliminating entirely the need for a hardware engineer model during instrument development and operation. SAMSIM simulates the complex interactions that occur between the instrument Command and Data Handling unit (C&DH) and all subsystems during the execution of experiment sequences. A typical SAM experiment takes many hours to complete and involves hundreds of components. During the simulation, the electrical, mechanical, thermal, and gas dynamics states of each hardware component are accurately modeled and propagated within the simulation environment at faster than real time. This allows the simulation, in just a few minutes, of experiment sequences that takes many hours to execute on the real instrument. The SAMSIM model is divided into five distinct but interacting modules: software, mechanical, thermal, gas flow, and electrical modules. The software module simulates the instrument C&DH by executing a customized version of the instrument flight software in a Matlab environment. The inputs and outputs to this synthetic C&DH are mapped to virtual sensors and command lines that mimic in their structure and connectivity the layout of the instrument harnesses. This module executes, and thus validates, complex command scripts prior to their up-linking to the SAM instrument. As an output, this module generates synthetic data and message logs at a rate that is similar to the actual instrument.

Benna, Mehdi↗
NASA NTRS2010

Adaptive Numerical Algorithms in Space Weather Modeling

Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical schemes. Depending on the application, we find that different time stepping methods are optimal. Several of the time integration schemes exploit the block-based granularity of the grid structure. The framework and the adaptive algorithms enable physics based space weather modeling and even forecasting.

Toth, Gabor↗
NASA NTRSDate not supplied

Lunar Science Investigations and Exploration in Celestial Mapping System

Introduction: As NASA expands the mission portfolio on the lunar surface, there is a need for applications with a broad range of analytical and functional capabilities that can be simultaneously deployed onto multiple mobile and desktop platforms to perform in-situ operations and hence enabling extensive Lunar exploration. Celestial Mapping System (CMS) [1,2] is developed to address the need for tools for science investigations, mission planning, operations and support for planetary sciences. Built on top of NASA WorldWind libraries, CMS can be simultaneously deployed onto multiple platforms, has the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission and has the potential to enable traverse path planning suited for rovers, EVA and surface mobility units. It can provide critical functionalities such as equipment planning and optimized placement on Lunar surface, line of sight analysis to inform the coverage area for various equipment, powerful measurement tools based on 3D terrain, 3D COLLADA models to represent rovers, humans and equipment, visualization of derived mapping products (e.g. resource maps), and a data engine for hosting new observations that are not available in other contemporary lunar data tools [1]. Visualization of PSRs: The current presentation focuses on the work performed by the authors, to consume a unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [3]. This tool was developed in direct support of NASA's VIPER and Artemis programs to enhance the extremely low-light images of the interior of PSRs and provide the first-time ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the region near Nobili crater near Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Line of Sight Analysis and Traverse Planning in PSRs: We have developed an in-built line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. This tool was utilized to perform viewshed analysis to investigate the area inside the PSR, a remote observer such as a rover could see without actually crossing the region. Figure 1 shows the viewshed analysis on the PSR in Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. Figure 1: (left) PSR image on top of a high-resolution mosaic of sunlit images of a crater, in Nobile region (right) Viewshed Analysis of the same PSR with observer location shown by yellow pin. This analysis was extended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater. Future plans: Eventually, HORUS datasets will be integrated into CMS as a layer in selected lunar polar regions. Hazard Maps will then be created based on terrain analysis in those regions. This integration will enable multiple scientific and exploration applications, such as designing traverses within PSRs, analyzing potential landing and science mission targets, investigating the meter-scale geomorphology of PSRs, including craters, boulder, surface roughness, mass wasting features and other indications of the presence of water-ice and other volatiles. Acknowledgments: CMS developers team including Kaitlyn J. Dickinson, Tyler A. Lucarz, Tyler W. Choi from USRA, NASA WorldWind Advisory team including Mark Peterson and Guillermo Miguel Del Castillo, HORUS team member V.T. Bickel, Robinson, M., LRO MOON LROC 2 EDR V1.0, LRO-L-LROC-2-EDR-V1.0, NASA Planetary Data System (PDS), 2009. https://doi.org/10.17189/1520643 References: [1] https://celestial.arc.nasa.gov [2] Agrawal et. al. “Celestial Mapping System for Lunar Surface Mapping and Analytics”, Lunar Surface Innovation Consortium, 2021 [3] Bickel V. et al. (2021) Nat Commun 12, 5607

Lunar Mapping↗
NASA NTRS2003

HEASARC Software Archive

(1) Chandra Archive: SAO has maintained the interfaces through which HEASARC gains access to the Chandra Data Archive. At HEASARC's request, we have implemented an anonymous ftp copy of a major part of the public archive and we keep that archive up-to- date. SAO has participated in the ADEC interoperability working group, establishing guidelines or interoperability standards and prototyping such interfaces. We have provided an NVO-based prototype interface, intending to serve the HEASARC-led NVO demo project. HEASARC's Astrobrowse interface was maintained and updated. In addition, we have participated in design discussions surrounding HEASARC's Caldb project. We have attended the HEASARC Users Group meeting and presented CDA status and developments. (2) Chandra CALDB: SA0 has maintained and expanded the Chandra CALDB by including four new data file types, defining the corresponding CALDB keyword/identification structures. We have provided CALDB upgrades for the public (CIAO) and for Standard Data Processing. Approximately 40 new files have been added to the CALDB in these version releases. There have been in the past year ten of these CALDB upgrades, each with unique index configurations. In addition, with the inputs from software, archive, and calibration scientists, as well as CIAO/SDP software developers, we have defined a generalized expansion of the existing CALDB interface and indexing structure. The purpose of this is to make the CALDB more generally applicable and useful in new and future missions that will be supported archivally by HEASARC. The generalized interface will identify additional configurational keywords and permit more extensive calibration parameter and boundary condition specifications for unique file selection. HEASARC scientists and developers from SAO and GSFC have become involved in this work, which is expected to produce a new interface for general use within the current year. (3) DS9: One of the decisions that came from last year's HEADCC meeting was to make the ds9 image display program the primary vehicle for displaying line graphics (as well as images). The first step required to make this possible was to enhance the line graphics capabilities of ds9. SAO therefore spent considerable effort upgrading ds9 to use Tcl 8.4 so that the BLT line graphics package could be built and imported into ds9 from source code, rather than from a pre-built (and generally outdated) shared library. This task, which is nearly complete, allows us to extend BLT as needed for the HEAD community. Following HEADCC discussion concerning archiving and the display of archived data, we extended ds9 to support full access to many astronomical Web-based archives sites, including HEASARC, MAST, CHANDRA, SKYVIEW, ADS, NED, SIMBAD, IRAS, NVRO, SAO TDC, and FIRST. Using ds9's new internal Web access capabilities, these archives can be accessed via their Web page. FITS images, plots, spectra, and journal abstracts can be referenced, down-loaded, and displayed directly and easily in ds9. For more information, see: http://hea-www.harvard.edu/saord/ds9. Also after the HEADCC discussion concerning region filtering, we extended the Funtools sample implementation of region filtering as described in: http://hea-www.harvard.edu/saord/funtools/regions.html. In particular, we added several new composite regions for event and image filtering, including elliptical and box annuli. We also extended the panda (Pie AND Annulus) region support to include box pandas and elliptical pandas. These new composite regions are especially useful in programs that need to count photons in each separate region using only a single pass through the data. Support for these new regions was added to ds9. In the same vein, we developed new region support for filtering images using simple FITS image masks, i.e. 8-bit or 16-bit FITS images where the value of a pixel is the region id number for that pixel. Other important enhancements to DS9 this year, include supporor multiple world coordinate systems, three dimensional event file binning, image smoothing, region groups and tags, the ability to save images in a number of image formats (such as JPEG, TIFF, PNG, FITS), improvements in support for integrating external analysis tools, and support for the virtual observatory. In particular, a full-featured web browser has been implemented within D S 9 . This provides support for full access to HEASARC archive sites such as SKYVIEW and W3BROWSE, in addition to other astronomical archives sites such as MAST, CHANDRA, ADS, NED, SIMBAD, IRAS, NVRO, SA0 TDC, and FIRST. From within DS9, the archives can be searched, and FITS images, plots, spectra, and journal abstracts can be referenced, downloaded and displayed The web browser provides the basis for the built-in help facility. All DS9 documentation, including the reference manual, FAQ, Know Features, and contact information is now available to the user without the need for external display applications. New versions of DS9 maybe downloaded and installed using this facility. Two important features used in the analysis of high energy astronomical data have been implemented in the past year. The first is support for binning photon event data in three dimensions. By binning the third dimension in time or energy, users are easily able to detect variable x-ray sources and identify other physical properties of their data. Second, a number of fast smoothing algorithms have been implemented in DS9, which allow users to smooth their data in real time. Algorithms for boxcar, tophat, and gaussian smoothing are supported.

White, Nicholas↗
NASA NTRS2016

Next Generation Flight Displays Using HTML5

The Human Integrated Vehicles and Environments (HIVE) lab at Johnson Space Center (JSC) is focused on bringing together inter-disciplinary talent to design and integrate innovative human interface technologies for next generation manned spacecraft. As part of this objective, my summer internship project centered on an ongoing investigation in to building flight displays using the HTML5 standard. Specifically, the goals of my project were to build and demo "flight-like" crew and wearable displays as well as create a webserver for live systems being developed by the Advanced Exploration Systems (AES) program. In parallel to my project, a LabVIEW application, called a display server, was created by the HIVE that uses an XTCE (XML (Extensible Markup Language) Telemetry and Command Exchange) parser and CCSDS (Consultative Committee for Space Data System) space packet decoder to translate telemetry items sent by the CFS (Core Flight Software) over User Datagram Protocol (UDP). It was the webserver's job to receive these UDP messages and send them to the displays. To accomplish this functionality, I utilized Node.js and the accompanying Express framework. On the display side, I was responsible for creating the power system (AMPS) displays. I did this by using HTML5, CSS and JavaScript to create web pages that could update and change dynamically based on the data they received from the webserver. At this point, I have not started on the commanding, being able to send back to the CFS, portion of the displays but hope to have this functionality working by the completion of my internship. I also created a way to test the webserver's functionality without the display server by making a JavaScript application that read in a comma-separate values (CSV) file and converted it to XML which was then sent over UDP. One of the major requirements of my project was to build everything using as little preexisting code as possible, which I accomplished by only using a handful of JavaScript libraries. As a side project, I created a model of the HIVE lab and Building 29 using SketchUp. I obtained the floorplans of the building from the JSC Geographic Information Systems (GIS), which were computer-aided design (CAD) files, and imported them into SketchUp. I then took those floorplans and created a 3D model of the building from them. Working in conjunction with the Hybrid Reality lab in Building 32, the SketchUp model was imported into Unreal Engine for use with the HTC Vive. Using the Vive, I was able to interact with the model I created in virtual reality (VR). The purpose of this side project was to be able to visualize potential lab layouts and mockup designs as they are in development in order to finalize design decisions. Pending approval, the model that I created will be used in the Build-As-You-Test: Can Hybrid Reality Improve the SE/HSI Design Process project in the fall. Getting the opportunity to work at NASA has been one of the most memorable experiences of my life. Over the course of my internship, I improved my programming and web development abilities substantially. I will take all the skills and experiences I have had while at NASA back to school with me in the fall and hope to pursue a career in the aerospace industry after graduating in the spring.

Greenwood, Brian↗
NASA NTRS1997

Towards High-Assurance High-Performance Program Synthesis

Domain-specific automatic program synthesis tools, also called application generators, are playing an ever-increasing role in software development. However, high-performance application generators require difficult manual construction, and are very difficult to verify correct. This paper describes research and an implemented system that transforms program synthesis tools based on deductive synthesis into high-performance application generators. Deductive synthesis uses theorem-proving to construct solutions when given problem specifications. The verification condition for a deductive synthesis tool is essentially the soundness of the implemented inference rules. Theory Operationalization for Program Synthesis (TOPS) synergistically combines reformulation, automated mathematical classification, and compilation through partial deduction to decision procedures. It transforms general-purpose deductive synthesis, with exponential performance, into efficient special-purpose deductive synthesis, with near-linear performance. This paper describes our experience with and empirical results of PD(TH) theory-based partial deduction - in which partial deduction of a set of first-order formulae is performed within the context of a background theory. The implemented TOPS system currently performs a special variant of PD(TH) in which the compilation process results in the transformation of a set of first order formulae into the theory of an instantiated library decision procedure augmented by a compiled unit theory.

Lowry, Michael↗
NASA NTRS2009

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗
NASA NTRS2016

Utilizing Commercial Hardware and Open Source Computer Vision Software to Perform Motion Capture for Reduced Gravity Flight

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited. Therefore, compact resistance exercise device prototypes are being developed. The NASA Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) project and the National Space Biomedical Research Institute (NSBRI) funded researchers by developing computational models of exercising with these new advanced exercise device concepts. To perform validation of these models and to support the Advanced Exercise Concepts Project, several candidate devices have been flown onboard NASAs Reduced Gravity Aircraft. In terrestrial laboratories, researchers typically have available to them motion capture systems for the measurement of subject kinematics. Onboard the parabolic flight aircraft it is not practical to utilize the traditional motion capture systems due to the large working volume they require and their relatively high replacement cost if damaged. To support measuring kinematics on board parabolic aircraft, a motion capture system is being developed utilizing open source computer vision code with commercial off the shelf (COTS) video camera hardware. While the systems accuracy is lower than lab setups, it provides a means to produce quantitative comparison motion capture kinematic data. Additionally, data such as required exercise volume for small spaces such as the Orion capsule can be determined. METHODS: OpenCV is an open source computer vision library that provides the ability to perform multi-camera 3 dimensional reconstruction. Utilizing OpenCV, via the Python programming language, a set of tools has been developed to perform motion capture in confined spaces using commercial cameras. Four Sony Video Cameras were intrinsically calibrated prior to flight. Intrinsic calibration provides a set of camera specific parameters to remove geometric distortion of the lens and sensor (specific to each individual camera). A set of high contrast markers were placed on the exercising subject (safety also necessitated that they be soft in case they become detached during parabolic flight); small yarn balls were used. Extrinsic calibration, the determination of camera location and orientation parameters, is performed using fixed landmark markers shared by the camera scenes. Additionally a wand calibration, the sweeping of the camera scenes simultaneously, was also performed. Techniques have been developed to perform intrinsic calibration, extrinsic calibration, isolation of the markers in the scene, calculation of marker 2D centroids, and 3D reconstruction from multiple cameras. These methods have been tested in the laboratory side-by-side comparison to a traditional motion capture system and also on a parabolic flight.

Biodynamics↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗
NASA NTRS1995

DITDOS: A set of design specifications for distributed data inventories

The analysis of space science data often requires researchers to work with many different types of data. For instance, correlative analysis can require data from multiple instruments on a single spacecraft, multiple spacecraft, and ground-based data. Typically, data from each source are available in a different format and have been written on a different type of computer, and so much effort must be spent to read the data and convert it to the computer and format that the researchers use in their analysis. The large and ever-growing amount of data and the large investment by the scientific community in software that require a specific data format make using standard data formats impractical. A format-independent approach to accessing and analyzing disparate data is key to being able to deliver data to a diverse community in a timely fashion. The system in use at the Planetary Plasma Interactions (PPI) node of the NASA Planetary Data System (PDS) is based on the object-oriented Distributed Inventory Tracking and Data Ordering Specification (DITDOS), which describes data inventories in a storage independent way. The specifications have been designed to make it possible to build DITDOS compliant inventories that can exist on portable media such as CD-ROM's. The portable media can be moved within a system, or from system to system, and still be used without modification. Several applications have been developed to work with DITDOS compliant data holdings. One is a windows-based client/server application, which helps guide the user in the selection of data. A user can select a data base, then a data set, then a specific data file, and then either order the data and receive it immediately if it is online or request that it be brought online if it is not. A user can also view data by any of the supported methods. DITDOS makes it possible to use already existing applications for data-specific actions, and this is done whenever possible. Another application is a stand-alone tool to assist in the extraction of data from portable media, such as CD-ROM's. In addition to the applications, there is a set of libraries that can facilitate building new DITDOS compliant applications.

King, T. A.↗
NASA NTRS2005

Development Approach of the Advanced Life Support On-line Project Information System

The Advanced Life Support (ALS) Program has recently accelerated an effort to develop an On-line Project Information System (OPIS) for research project and technology development data centralization and sharing. There has been significant advancement in the On-line Project Information System (OPIS) over the past year (Hogan et al, 2004). This paper presents the resultant OPIS development approach. OPIS is being built as an application framework consisting of an uderlying Linux/Apache/MySQL/PHP (LAMP) stack, and supporting class libraries that provides database abstraction and automatic code generation, simplifying the ongoing development and maintenance process. Such a development approach allows for quick adaptation to serve multiple Programs, although initial deployment is for an ALS module. OPIS core functionality will involve a Web-based annual solicitation of project and technology data directly from ALS Principal Investigators (PIs) through customized data collection forms. Data provided by PIs will be reviewed by a Technical Task Monitor (TTM) before posting the information to OPIS for ALS Community viewing via the Web. Such Annual Reports will be permanent, citable references within OPIS. OPlS core functionality will also include Project Home Sites, which will allow PIS to provide updated technology information to the Community in between Annual Report updates. All data will be stored in an object-oriented relational database, created in MySQL(Reistered Trademark) and located on a secure server at NASA Ames Research Center (ARC). Upon launch, OPlS can be utilized by Managers to identify research and technology development (R&TD) gaps and to assess task performance. Analysts can employ OPlS to obtain the current, comprehensive, accurate information about advanced technologies that is required to perform trade studies of various life support system options. ALS researchers and technology developers can use OPlS to achieve an improved understanding of the NASA and ALS Program needs and to understand how other researchers and technology developers are addressing those needs. OPlS core functionality will launch for 'Ihe ALS Program in October, 2005. However, the system has been developed with the ability to evolve with Program needs. Because of open-source construction, software costs are minimized. Any functionality that is technologically feasible can be built into OPIS, and OPlS can expand through module cloning and adaptation, to any level deemed useful to the Agency.

Levri, Julie A.↗