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Collection of software modules can be configured to solve variety of mission analysis problems. GMAS includes modules for performing large selection of standard mission analyses. Graphics executive system is provided. Program is in FORTRAN IV and Assembler for and interactive execution on IBM 360-series.
The purpose of this presentation is to outline how the NASA Independent Verification and Validation (IVV) Program helps to build reliability into the Space Mission Software Systems (SMSSs) that its customers develop.
Model-Based System Engineering (MBSE) is an increasingly popular methodology for designing complex engineering systems. As the use of MBSE has grown, it has begun to be applied to systems that are less hardware-based and more people- and process-based. We describe our approach to incorporating MBSE as a way to streamline development, and how to build a model consisting of core resources, such as requirements and interfaces, that can be adapted and used by new and upcoming projects. By comparing traditional Mission Operations System (MOS) system engineering with an MOS designed via a model, we will demonstrate the benefits to be obtained by incorporating MBSE in system engineering design processes.
Surveyor Mission G flight operations from transit phase to second lunar day
Systems analysis and flight performance of Atlas Centaur launch vehicle with Surveyor 1 lunar probe
Viking Lander hardware performance during launch, interplanetary cruise, Mars orbit insertion, preseparation, separation through landing, and the primary landed mission, with primary emphasis on Lander engineering and science hardware operations, the as-flown mission are described with respect to Lander system performance and anomalies during the various mission phases. The extended mission and predicted Lander performance is discussed along with a summary of Viking goals, mission plans, and description of the Lander, and its subsystem definitions.
flexplan is a mission planning and scheduling (MPS) tool that uses soft algorithms to define mission scheduling rules and constraints. This allows the operator to configure the tool for any mission without the need to modify or recompile code. In addition, flexplan uses an ID system to track every output on the schedule to the input from which it was generated. This allows flexplan to receive feedback as the schedules are executed, and update the status of all activities in a Web-based client. flexplan outputs include various planning reports, stored command loads for the Lunar Reconnaissance Orbiter (LRO), ephemeris loads, and pass scripts for automation.
In situ resource utilization (ISRU) technologies are a key advancement required to make human habitation on the Moon and Mars viable. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission will provide crucial correlations between volatiles and lunar geology to understand the water content available for ISRU on the moon. The mission will require the coordination of multi-disciplinary teams across the country making real time decisions based on rover instrument data. The virtual reality Mission Simulation System (vMSS) is a virtual reality platform designed at MIT by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team to provide teams with a collaboration interface for planetary missions like VIPER. Herein we determine the integration pathway for analog based datasets that are examples of VIPER's two main instruments, the near-infrared volatile spectrometer subsystem (NIRVSS) and the neutron spectrometer subsystem (NSS), into vMSS to provide the most valuable visualization tools. Focusing on improving situational awareness, decision making, reducing task load and incorporating comments from scientists working previous analogs and on the current VIPER mission, we recommend critical elements to implement into vMSS and the best approaches for data visualization. We present a review of relevant analogs and state of the art mission software. We have developed a design concept and path to flight of analysed instrument data integrated with data maps that allow for virtual manipulation and annotation between non-co-located team members. We focus on pre-mission mapping of a priori data for improved situational awareness, layering of analysed instrument data, correlative mapping and interactive capabilities for in-mission decision making, as well as archiving and annotation tools for post-mission analysis. Finally, we lay out the roadmap for the future development of immersive sample site visualization capabilities and the use of integrated instrument data in vMSS with automated temporal and geospatial planning.
The goal of the Wide-field Infrared Survey Explorer (WISE) mission is to perform a highly sensitive all-sky survey in 4 wavebands from 3 to 25(mu)m. Launched on a Delta II rocket into a 500km Sun-synchronous orbit in June 2009, during its 7 months of operations, WISE will acquire about 50GBytes of raw science data every day, which will be down-linked via the TDRSS relay satellite system and processed into an astronomical catalogue and image atlas. The WISE mission operations system is being implemented in collaboration between UCLA, JPL and IPAC (Caltech). In this paper we describe the challenges to manage a high data rate, cryogenic, low earth-orbit mission; maintaining safe on-orbit operations, fast anomaly recoveries (mandated by the desire to provide complete sky coverage in a limited lifetime), production and dissemination of high quality science products, given the constraints imposed by funding profiles for small space missions.
This paper is a retrospective of the lessons learned during the almost 15-year history of the Compass concurrent mission and systems design team at NASA’s Glenn Research Center (GRC). It examines the key factors in the team’s evolution from a temporary group gathered to perform a single study to the successful, sustainable team it is today. Compass is a matrixed team of experts with various technical backgrounds and personalities. They collaborate over a two-week period either physically in a dedicated meeting space, or virtually to design a space system (Spacecraft, stage, science package, etc). Over the years, because of the rapid nature of the design studies, the team leadership has iterated on the optimal team member personality makeup, facility elements and tools as well as NASA GRC management support necessary to lead to sustained success.
Established at the NASA Glenn Research Center (GRC) in 2006 to meet the need for rapid mission analysis and multi-disciplinary systems design for in-space and human missions, the Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team is a multidisciplinary, concurrent engineering group whose primary purpose is to perform integrated systems analysis, but it is also capable of designing any system that involves one or more of the disciplines present in the team. The authors were involved in the development of the COMPASS team and its design process, and are continuously making refinements and enhancements. The team was unofficially started in the early 2000s as part of the distributed team known as Team JIMO (Jupiter Icy Moons Orbiter) in support of the multi-center collaborative JIMO spacecraft design during Project Prometheus. This paper documents the origins of a concurrent mission and systems design team at GRC and how it evolved into the COMPASS team, including defining the process, gathering the team and tools, building the facility, and performing studies.
The Advanced Technology Operations System (ATOS) is a program of studies into the integration of advanced applications (including knowledge based systems (KBS)) with ground systems for the support of spacecraft mission operations.
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The majority of today's CubeSat fleet consists of Earth-orbiting missions that mostly use existing ground systems developed by universities because of availability, simplicity, and low-cost. The Interplanetary NanoSpacecraft Pathfinder In Relevant Environment (INSPIRE) mission is a revolutionary CubeSat mission that will launch a pair of CubeSats into deep space to study the feasibility of CubeSats beyond low-Earth orbit. This uncovers a new set of systems and software engineering challenges to the development of a robust and reliable ground system in a low-cost environment. In this paper, we discuss the approach to these challenges by using the Jet Propulsion Laboratory's (JPL) Advanced Multimission Operation System (AMMOS) Ground Data System (GDS) as well as the methodologies used to engineer the flight system to work with an existing ground system developed for large-scale missions. Specifically we will focus on the command and telemetry subsystem of AMMOS, the Multimission Data Processing and Control System. We conclude with a retrospective on the challenges encountered and a brief discussion on our efforts to provide AMMOS to support future deep space CubeSat missions.
Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.
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Space exploration missions are evolving toward more complex architectures involving more capable robotic systems, new levels of human and robotic interaction, and increasingly autonomous systems. How this evolving mix of advanced capabilities will be utilized in the design of new missions is a subject of much current interest. Cost and risk constraints also play a key role in the development of new missions, resulting in a complex interplay of a broad range of factors in the mission development and planning of new missions. This paper will discuss how human, robotic, and autonomous systems could be used in advanced space exploration missions. In particular, a recently completed survey of the state of the art and the potential future of robotic systems, as well as new experiments utilizing human and robotic approaches will be described. Finally, there will be a discussion of how best to utilize these various approaches for meeting space exploration goals.