200 research outputs found

    SISO Space Reference FOM - Tools and Testing

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    The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE

    SISO Space Reference FOM 101

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    This is a tutorial that covers the basic concepts associated with the SISO Space Reference Federation Object Model. It will be given at the SISO 2020 SIW in Orlando, Florida

    Generic Kalman Filter Software

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    The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on the basis of the aforementioned templates. The GKF software can be used to develop many different types of unfactorized Kalman filters. A developer can choose to implement either a linearized or an extended Kalman filter algorithm, without having to modify the GKF software. Control dynamics can be taken into account or neglected in the filter-dynamics model. Filter programs developed by use of the GKF software can be made to propagate equations of motion for linear or nonlinear dynamical systems that are deterministic or stochastic. In addition, filter programs can be made to operate in user-selectable "covariance analysis" and "propagation-only" modes that are useful in design and development stages

    Systematic replications and statistical reproducibility of educational research

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    Science is at a critical juncture: the findings of many studies are unable to be replicated and reproduced, while scientific output is growing exponentially and becoming easily accessible. The inability of findings to replicate has been particularly prominent in the field of psychology, where it has been estimated that less than half of findings are able to be replicated. A similar conclusion has been drawn about educational research. At the same time, thousands of papers are published making it increasingly difficult for researchers to know whether or not findings have replicated. This thesis addresses the replicability and reproducibility of educational research and proposes tools that could help researchers sift through large amounts of scholarly output. The first paper of this thesis differentiates between the ideas of replicability and reproducibility, and describes how educational researchers can design systematic replications and report the details needed to reproduce statistical analyses. The second paper examines the use of different text classifiers to extract details about the findings and contextual factors of published articles, where this information can be used by researchers to determine whether two papers are systematic replications of one another. The third paper develops text classifiers to identify the details needed to reproduce the statistical analyses in published papers. These three papers demonstrate there are many components needed to replicate and reproduce educational studies, and these details are sometimes easily identified by text classifiers

    Distributed Simulation for Space Exploration

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    This viewgraph presentation reviews the use of simulation and modeling in preparation for the planned exploration initiatives. The Exploration Systems Mission Directorate (EMSD) Integrated Modeling and Simulation (IM&S) team strategy encompasses a wide spectrum of simulation and modeling policies and technologies. One prominent technology is distributed simulation. The DIstributed Simulation (DIS),a collaborative simulation project with international participation (US and Japan) is reviewed as an example of distributed simulation development. The Distributed Space Exploration Simulation (DSES) is another example of distributed simulation that is describe

    Phobos: Simulation-Driven Design for Exploration

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    Dr. Edwin "Zack" Crues presented an overview of the current use of modeling and simulation technologies by the NASA Exploration Systems Simulations (NExSyS) team in investigating the spacecraft and missions for the human exploration of Mars' moon Phobos

    A Coordinated Initialization Process for the Distributed Space Exploration Simulation (DSES)

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    This document describes the federate initialization process that was developed at the NASA Johnson Space Center with the HIIA Transfer Vehicle Flight Controller Trainer (HTV FCT) simulations and refined in the Distributed Space Exploration Simulation (DSES). These simulations use the High Level Architecture (HLA) IEEE 1516 to provide the communication and coordination between the distributed parts of the simulation. The purpose of the paper is to describe a generic initialization sequence that can be used to create a federate that can: 1. Properly initialize all HLA objects, object instances, interactions, and time management 2. Check for the presence of all federates 3. Coordinate startup with other federates 4. Robustly initialize and share initial object instance data with other federates

    Introduction to Modeling and Simulation

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    Lighting Condition Analysis for Mars Moon Phobos

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    A manned mission to Phobos may be an important precursor and catalyst for the human exploration of Mars, as it will fully demonstrate the technologies for a successful Mars mission. A comprehensive understanding of Phobos' environment such as lighting condition and gravitational acceleration are essential to the mission success. The lighting condition is one of many critical factors for landing zone selection, vehicle power subsystem design, and surface mobility vehicle path planning. Due to the orbital characteristic of Phobos, the lighting condition will change dramatically from one Martian season to another. This study uses high fidelity computer simulation to investigate the lighting conditions, specifically the solar radiation flux over the surface, on Phobos. Ephemeris data from the Jet Propulsion Laboratory (JPL) DE405 model was used to model the state of the Sun, the Earth, and Mars. An occultation model was developed to simulate Phobos' self-shadowing and its solar eclipses by Mars. The propagated Phobos' state was compared with data from JPL's Horizon system to ensure the accuracy of the result. Results for Phobos lighting condition over one Martian year are presented in this paper, which include length of solar eclipse, average solar radiation intensity, surface exposure time, total maximum solar energy, and total surface solar energy (constrained by incident angle). The results show that Phobos' solar eclipse time changes throughout the Martian year with the maximum eclipse time occurring during the Martian spring and fall equinox and no solar eclipse during the Martian summer and winter solstice. Solar radiation intensity is close to minimum at the summer solstice and close to maximum at the winter solstice. Total surface exposure time is longer near the north pole and around the anti- Mars point. Total maximum solar energy is larger around the anti-Mars point. Total surface solar energy is higher around the anti-Mars point near the equator. The results from this study and others like it will be important in determining landing site selection, vehicle system design and mission operations for the human exploration of Phobos and subsequently Mars
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