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4The General Mission Analysis Tool (GMAT) is a space trajectory optimization and mission analysis system. This document is a draft of the users guide for the tool. Included in the guide is information about Configuring Objects/Resources, Object Fields: Quick Look-up Tables, and Commands and Events.
Several NASA centers have developed independent flight mechanics tools to meet the science needs of missions. This NASA Engineering and Safety Center (NESC) assessment sought to explore the ways to increase the interoperability of three specific tools: Copernicus from Johnson Space Center (JSC), the General Mission Analysis Tool (GMAT) from Goddard Spaceflight Flight Center (GSFC), and the Mission-Analysis Operations Navigation Toolkit Environment (MONTE) from the Jet Propulsion Laboratory (JPL). Before this assessment, these tools were not integrated and could not easily share data, models, or components. This report contains the outcome of the NESC assessment.
This paper presents a performance analysis of the instrument pointing control system for NASA's Space Interferometer Mission (SIM). SIM has a complex pointing system that uses a fast steering mirror in combination with a multirate control architecture to blend feed forward information with feedback information. A pointing covariance analysis tool (PCAT) is developed specifically to analyze systems with such complexity. The development of PCAT as a mathematical tool for covariance analysis is outlined in the paper. PCAT is then applied to studying performance of SIM's science pointing system. The analysis reveals and clearly delineates a fundamental limit that exists for SIM pointing performance. The limit is especially stringent for dim star targets. Discussion of the nature of the performance limit is provided, and methods are suggested to potentially improve pointing performance.
Giovanni, the NASA Goddard online visualization and analysis tool (http://giovanni.gsfc.nasa.gov) allows users explore various atmospheric phenomena without learning remote sensing data formats and downloading voluminous data. Using NASA MODIS (Terra and Aqua) and ESA MERIS (ENVISAT) aerosol data as an example, we demonstrate Giovanni usage for online multi-sensor remote sensing data comparison and analysis.
The Object Reentry Survival Analysis Tool (ORSAT) code is maintained and used by the NASA Orbital Debris Program Office (ODPO) and has been under continuous development and improvement since the mid-1990s. ORSAT is an object-oriented reentry simulation tool; it models a satellite as a collection of discrete components that follow independent trajectories upon the breakup of the parent object. Version 7.1 of the tool incorporates five years of new thermal and aerodynamic model development, multi-processor parametric study capability, codebase upgrades, and numerous bug-fixes. The thermal demise model was completely rewritten using a forward-time/central-space numerical stencil and incorporating a new pyrolysis model for fiber-reinforced plastic (FRP) materials. New aerodynamic and aeroheating models for hollow cylinders and hollow square prisms were developed using a combination of flow simulations in the direct simulation Monte Carlo (DSMC) Analysis Code (DAC) and Data Parallel Line Relaxation (DPLR) code and free-flight tests in the University of Texas at San Antonio’s Hypersonic Wind Tunnel. The latest version also incorporates a mechanical, strength-based demise model for FRP materials. Minor improvements include an update to the Fortran 2018 codebase; improved integration and speed with the Python-based, multi-core, parametric study tool, AutoORSAT; and fixes for many minor bugs. This new version of ORSAT will enable more accurate reentry risk assessments for modern satellites. This paper presents an overview of these changes and a summary of the verification and validation performed on the final code.
The Object Reentry Survival Analysis Tool (ORSAT) code is maintained and used by the NASA Orbital Debris Program Office (ODPO) and has been under continuous development and improvement since the mid-1990s. ORSAT is an object-oriented reentry simulation tool; it models a satellite as a collection of discrete components that follow independent trajectories upon the breakup of the parent object. Version 7.1 of the tool incorporates five years of new thermal and aerodynamic model development, multi-processor parametric study capability, codebase upgrades, and numerous bug-fixes. The thermal demise model was completely rewritten using a forward-time/central-space numerical stencil and incorporating a new pyrolysis model for fiber-reinforced plastic (FRP) materials. New aerodynamic and aeroheating models for hollow cylinders and hollow square prisms were developed using a combination of flow simulations in the direct simulation Monte Carlo (DSMC) Analysis Code (DAC) and Data Parallel Line Relaxation (DPLR) code and free-flight tests in the University of Texas at San Antonio’s Hypersonic Wind Tunnel. The latest version also incorporates a mechanical, strength-based demise model for FRP materials. Minor improvements include an update to the Fortran 2018 codebase; improved integration and speed with the Python-based, multi-core, parametric study tool, AutoORSAT; and fixes for many minor bugs. This new version of ORSAT will enable more accurate reentry risk assessments for modern satellites. This paper presents an overview of these changes and a summary of the verification and validation performed on the final code.
The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.
The NASA Orbital Debris Program Office (ODPO) Safety Group at the Johnson Space Center analyzes reentering spacecraft at the end of life. The program primarily used by ODPO in this effort is the Object Reentry Survival Analysis Tool (ORSAT). ORSAT utilizes shape primitives as well as a variety of other parameters (material, size, thickness, aerodynamic mass, orbit inclination, etc.) to simulate the reentry process and ultimately, to determine if a spacecraft could be hazardous to the population on the ground. The NASA ODPO plans to automate the ORSAT process to run multiple ORSAT input files either concurrently or consecutively. This type of automation program will provide several benefits. First, there is a need to run large parametric studies for ORSAT analysts to gain a greater understanding of reentering object’s sensitivity to certain input variables. Secondly, a database of pre-run ORSAT cases will be used to develop a survivability model, which could be made available to spacecraft developers as a design for demise (D4D) tool. The recently completed Automated Object Reentry Survival Analysis Tool (AutoORSAT) Wrapper is currently being used to build a survivability database, the first step in developing a survivability model. Already, the data that AutoORSAT has produced provides a greater understanding of the sensitivity of variables such as the initial temperature of the spacecraft, spacecraft breakup altitude, and the aerodynamic mass of spacecraft.
In the early formulation phase of a mission it is critically important to have fast, easy to use, easy to integrate space vehicle subsystem analysis tools so that engineers can rapidly perform trade studies not only by themselves but in coordination with other subsystem engineers as well. The Multi-Mission Telecom Analysis Tool (MMTAT) is designed for just this purpose.
Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.
Several space missions presently in the concept phase (e.g. Stellar Imager, Submillimeter Probe of Evolutionary Cosmic Structure, Terrestrial Planet Finder) plan to use multiple spacecraft flying in precise formation to synthesize unprecedently large aperture optical systems. These architectures present challenges to the attitude and position determination and control system; optical performance is directly coupled to spacecraft pointing with typical control requirements being on the scale of milliarcseconds and nanometers. To investigate control strategies, rejection of environmental disturbances, and sensor and actuator requirements, a capability is needed to model both the dynamical and optical behavior of such a distributed telescope system. This paper describes work ongoing at NASA Goddard Space Flight Center toward the integration of a set of optical analysis tools (Optical System Characterization and Analysis Research software, or OSCAR) with the Formation Flying Test Bed (FFTB). The resulting system is called the Precision Formation Flying Integrated Analysis Tool (PFFIAT), and it provides the capability to simulate closed-loop control of optical systems composed of elements mounted on multiple spacecraft. The attitude and translation spacecraft dynamics are simulated in the FFTB, including effects of the space environment (e.g. solar radiation pressure, differential orbital motion). The resulting optical configuration is then processed by OSCAR to determine an optical image. From this image, wavefront sensing (e.g. phase retrieval) techniques are being developed to derive attitude and position errors. These error signals will be fed back to the spacecraft control systems, completing the control loop. A simple case study is presented to demonstrate the present capabilities of the tool.
Several space missions presently in the concept phase (e.g. Stellar Imager, Sub- millimeter Probe of Evolutionary Cosmic Structure, Terrestrial Planet Finder) plan to use multiple spacecraft flying in precise formation to synthesize unprecedently large aperture optical systems. These architectures present challenges to the attitude and position determination and control system; optical performance is directly coupled to spacecraft pointing with typical control requirements being on the scale of milliarcseconds and nanometers. To investigate control strategies, rejection of environmental disturbances, and sensor and actuator requirements, a capability is needed to model both the dynamical and optical behavior of such a distributed telescope system. This paper describes work ongoing at NASA Goddard Space Flight Center toward the integration of a set of optical analysis tools (Optical System Characterization and Analysis Research software, or OSCAR) with the Formation J?lying Test Bed (FFTB). The resulting system is called the Precision Formation Flying Integrated Analysis Tool (PFFIAT), and it provides the capability to simulate closed-loop control of optical systems composed of elements mounted on multiple spacecraft. The attitude and translation spacecraft dynamics are simulated in the FFTB, including effects of the space environment (e.g. solar radiation pressure, differential orbital motion). The resulting optical configuration is then processed by OSCAR to determine an optical image. From this image, wavefront sensing (e.g. phase retrieval) techniques are being developed to derive attitude and position errors. These error signals will be fed back to the spacecraft control systems, completing the control loop. A simple case study is presented to demonstrate the present capabilities of the tool.
We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.
A microcomputer based software for analysis of radio frequency interference is presented in this paper.
Launch vehicle programs require vertically complete atmospheric profiles. Many systems at the ER to make the necessary measurements, but all have different EVR, vertical coverage, and temporal coverage. MSFC Natural Environments Branch developed a tool to create a vertically complete profile from multiple inputs using Python. Forward work: Finish Formal Testing Acceptance Testing, End-to-End Testing. Formal Release
Tropospheric winds are an important driver of the design and operation of space launch vehicles. Multiple types of weather balloons and Doppler Radar Wind Profiler (DRWP) systems exist at NASA's Kennedy Space Center (KSC), co-located on the United States Air Force's (USAF) Eastern Range (ER) at the Cape Canaveral Air Force Station (CCAFS), that are capable of measuring atmospheric winds. Meteorological data gathered by these instruments are being used in the design of NASA's Space Launch System (SLS) and other space launch vehicles, and will be used during the day-of-launch (DOL) of SLS to aid in loads and trajectory analyses. For the purpose of SLS day-of-launch needs, the balloons have the altitude coverage needed, but take over an hour to reach the maximum altitude and can drift far from the vehicle's path. The DRWPs have the spatial and temporal resolutions needed, but do not provide complete altitude coverage. Therefore, the Natural Environments Branch (EV44) at Marshall Space Flight Center (MSFC) developed the Profile Envision and Splice Tool (PRESTO) to combine balloon profiles and profiles from multiple DRWPs, filter the spliced profile to a common wavelength, and allow the operator to generate output files as well as to visualize the inputs and the spliced profile for SLS DOL operations. PRESTO was developed in Python taking advantage of NumPy and SciPy for the splicing procedure, matplotlib for the visualization, and Tkinter for the execution of the graphical user interface (GUI). This paper describes in detail the Python coding implementation for the splicing, filtering, and visualization methodology used in PRESTO.
The Multi-Mission Power Analysis Tool (MMPAT) simulates a spacecraft power subsystem including the power source (solar array and/or radioisotope thermoelectric generator), bus-voltage control, secondary battery (lithium-ion or nickel-hydrogen), thermostatic heaters, and power-consuming equipment. It handles multiple mission types including heliocentric orbiters, planetary orbiters, and surface operations. Being parametrically driven along with its user-programmable features can reduce or even eliminate any need for software modifications when configuring it for a particular spacecraft. It provides multiple levels of fidelity, thereby fulfilling the vast majority of a project s power simulation needs throughout the lifecycle. It can operate in a stand-alone mode with a graphical user interface, in batch mode, or as a library linked with other tools. This software can simulate all major aspects of a spacecraft power subsystem. It is parametrically driven to reduce or eliminate the need for a programmer. Added flexibility is provided through user-designed state models and table-driven parameters. MMPAT is designed to be used by a variety of users, such as power subsystem engineers for sizing power subsystem components; mission planners for adjusting mission scenarios using power profiles generated by the model; system engineers for performing system- level trade studies using the results of the model during the early design phases of a spacecraft; and operations personnel for high-fidelity modeling of the essential power aspect of the planning picture.
The General Mission Analysis Tool (GMAT) is an open-source space mission design, analysis and trajectory optimization tool. GMAT is developed by a team of NASA, private industry, public and private contributors. GMAT is designed to model, optimize and estimate spacecraft trajectories in flight regimes ranging from low Earth orbit to lunar applications, interplanetary trajectories and other deep space missions. GMAT has also been flight qualified to support operational maneuver planning for the Advanced Composition Explorer (ACE) mission. ACE was launched in August, 1997 and is orbiting the Sun-Earth L1 libration point. The primary science objective of ACE is to study the composition of both the solar wind and the galactic cosmic rays. Operational orbit determination, maneuver operations and product generation for ACE are conducted by NASA Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF). This paper discusses the entire engineering lifecycle and major operational certification milestones that GMAT successfully completed to obtain operational certification for the ACE mission. Operational certification milestones such as gathering of the requirements for ACE operational maneuver planning, gap analysis, test plans and procedures development, system design, pre-shadow operations, training to FDF ACE maneuver planners, shadow operations, Test Readiness Review (TRR) and finally Operational Readiness Review (ORR) are discussed. These efforts have demonstrated that GMAT is flight quality software ready to support ACE mission operations in the FDF.