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At least 289 records · Page 16

Jupiter Europa Orbiter Architecture Definition Process

The proposed Jupiter Europa Orbiter mission, planned for launch in 2020, is using a new architectural process and framework tool to drive its model-based systems engineering effort. The process focuses on getting the architecture right before writing requirements and developing a point design. A new architecture framework tool provides for the structured entry and retrieval of architecture artifacts based on an emerging architecture meta-model. This paper describes the relationships among these artifacts and how they are used in the systems engineering effort. Some early lessons learned are discussed.

requirements analysis↗

Captan+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗

CAPTAN+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗

Mars 2020 Site-Specific Mission Performance Analysis: 1. Science exploration and sol type modeling

We developed a scenario-based mission performance model for the Mars 2020 Rover to help identify project-wide productivity and operability challenges and opportunities. We have modeled science exploration combining high-fidelity resource modeling, science strategies, and modular science activity scenarios. This is proving to be an effective way of incorporating science activities into an engineering-based performance model.

Ono, Masahiro↗

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗

Towards a Decision Support System for Space Flight Operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Meshkat, Leila↗

Towards a decision support system for space flight operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The differences between the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the four increments of this vision. These increments include (1) the existing capabilities (2) hardware and software system components and interfaces with the NASA ground system, (3) uncertainty management and (4) re-planning and automated execution. Each of these increments provides value independently; but some may also enable building of a subsequent increment.

Ruszkowski, James↗

2023 Artemis Crew Health and Performance System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗

2023 Artemis Crew Health and Performance (CHP) System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗

Effort to Accelerate MBSE Adoption and Usage at JSC

This paper describes the authors' experience in adopting Model Based System Engineering (MBSE) at the NASA/Johnson Space Center (JSC). Since 2009, NASA/JSC has been applying MBSE using the Systems Modeling Language (SysML) to a number of advanced projects. Models integrate views of the system from multiple perspectives, capturing the system design information for multiple stakeholders. This method has allowed engineers to better control changes, improve traceability from requirements to design and manage the numerous interactions between components. As the project progresses, the models become the official source of information and used by multiple stakeholders. Three major types of challenges that hamper the adoption of the MBSE technology are described. These challenges are addressed by a multipronged approach that includes educating the main stakeholders, implementing an organizational infrastructure that supports the adoption effort, defining a set of modeling guidelines to help engineers in their modeling effort, providing a toolset that support the generation of valuable products, and providing a library of reusable models. JSC project case studies are presented to illustrate how the proposed approach has been successfully applied.

Wang, Lui↗

Model-Based Verification and Validation of Spacecraft Avionics

Our simulation was able to mimic the results of 30 tests on the actual hardware. This shows that simulations have the potential to enable early design validation - well before actual hardware exists. Although simulations focused around data processing procedures at subsystem and device level, they can also be applied to system level analysis to simulate mission scenarios and consumable tracking (e.g. power, propellant, etc.). Simulation engine plug-in developments are continually improving the product, but handling time for time-sensitive operations (like those of the remote engineering unit and bus controller) can be cumbersome.

Systems Modeling Language (SysML↗

A Model-based Approach to Developing the Concept of Operations for Potential Mars Sample Return

Mars Sample Return (MSR) is a proposed multi-agency effort that would return soil and rock samples from the surface of Mars to Earth. Both the complexity of the potential missions, as well as the involvement of multiple geographically distributed organizations, presents a challenge from an information management perspective. In this paper, a Model-based Systems Engineering (MBSE) approach to developing the Concept of Operations of a potential Mars Sample Return effort using the System Modeling Language(SysML) is presented.

Muirhead, Brian↗

Developing the Foundations of an Exploration Class Medical System: Bridging the Capability Gap between LEO and Mars

NASA's overarching mission is to drive advances in science, technology, aeronautics, and space exploration to enhance knowledge, education, innovation, economic vitality, and Earth stewardship. Its Artemis Program encompasses the next steps in human space exploration, critical elements of which include the Orion vehicle and Gateway outpost in lunar orbit. Artemis is the first "exploration class" space travel system with the stated mission to establish sustainable exploration of the lunar surface and serve as a bridge to future human exploration of Mars. Success requires understanding both the commonalities and the differences between our experience to date, predominantly in Low-Earth-Orbit, and the challenges expected in long-duration exploration missions. In addition, these missions will incur significant constraints on both vehicle and human systems. To that end, NASA Exploration Medical Capability (ExMC) element clinicians, engineers, and scientists are developing the "foundation" for a fully vehicle-integrated exploration-class medical system using model-based systems engineering to trace and leverage clinical and engineering content to expand and refine the fidelity and confidence in the medical system itself.

MEDICAL SYSTEMS↗

Studies and analyses of the space shuttle main engine. Failure information propagation model data base and software

The failure information propagation model (FIPM) data base was developed to store and manipulate the large amount of information anticipated for the various Space Shuttle Main Engine (SSME) FIPMs. The organization and structure of the FIPM data base is described, including a summary of the data fields and key attributes associated with each FIPM data file. The menu-driven software developed to facilitate and control the entry, modification, and listing of data base records is also discussed. The transfer of the FIPM data base and software to the NASA Marshall Space Flight Center is described. Complete listings of all of the data base definition commands and software procedures are included in the appendixes.

Tischer, A. E.↗

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

System-Level Model-Based Risk Determination for Lunar Mission Design

Recent work has shown that human activities on the lunar surface have the potential to impact not only surface infrastructure, but also have long-term repercussions to lunar orbit infrastructure that is directly proportional to the frequency and scale of landings and impacts. Those assets that are present within the lunar environment, whether on the surface or in orbit, are thus not entirely isolated from one another but contribute to the overall induced environment. With that in mind, this project endeavors to model that system using Model Based Systems Engineering (MBSE), employing previously developed mathematical methodology. The product from this work is a flexible tool with which a user may model any number of assets or events and determine how the dust and debris generated by those events effects mission operations and overall projected.

Matthew Wittal↗