{"id":519865,"date":"2026-08-25T23:00:00","date_gmt":"2026-08-25T13:00:00","guid":{"rendered":"https:\/\/science.nasa.gov\/science-research\/science-enabling-technology\/technology-highlights\/integrating-model-based-systems-engineering-and-fault-management-to-enable-autonomous-space-missions\/"},"modified":"2026-08-25T23:00:00","modified_gmt":"2026-08-25T13:00:00","slug":"integrating-model-based-systems-engineering-and-fault-management-to-enable-autonomous-space-missions","status":"publish","type":"post","link":"https:\/\/www.vibewire.com.au\/?p=519865","title":{"rendered":"Integrating Model-Based Systems Engineering and Fault Management to Enable Autonomous Space Missions"},"content":{"rendered":"

Fully autonomous space mission operations require the ability to detect faults and compensate for them without human intervention. To address this challenge and provide model-based support for system design and operations, it is important to connect fault management (FM) and model-based systems engineering (MBSE). This approach was successfully demonstrated with the model-based generation of a failure modes and effects analysis and fault trees using NASA\u2019s HelioSwarm mission early design information.<\/strong><\/p>\n

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\"A<\/a><\/figure>
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Artist\u2019s conception of the future HelioSwarm mission in orbit.<\/div>\n
Credit: HelioSwarm Project Team<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n

As NASA strives to push the boundaries of space travel with the Artemis program and the agency\u2019s upcoming deep-space science missions, increased system autonomy and resiliency have inevitably become key technology needs. Autonomous operations require fault management (FM) software to detect issues that occur in space so they can be mitigated automatically without human intervention. <\/strong>Designing autonomous missions requires a multi-disciplinary approach that connects FM with the model-based systems engineering (MBSE) approach used in mission design to ensure that resilient, fault-tolerant systems are architected, modeled, and integrated during the design phase.<\/p>\n

To address this need, NASA awarded a Phase II Small Business Innovation Research (SBIR) contract to Qualtech Systems Inc. (QSI) for development of FM capabilities and enhancements to its commercially available toolset, TEAMS\u00ae (a product that resulted from commercialization of the company\u2019s earlier NASA-sponsored SBIR work), to support HelioSwarm<\/a> and other NASA heliophysics missions.<\/p>\n

The QSI Approach<\/strong><\/h3>\n

One of the most important tasks in this effort was to connect system health management (SHM) and FM to the systems engineering (SE) process. Together, SHM\/FM consists of a set of mechanisms that ensure that mission goals are achieved by preventing failures from occurring, or detecting and then mitigating them if they do occur. The SE process coordinates, cross-checks, and integrates system elements to achieve mission goals and is integral during the design, specification, and verification and validation (V&V) of systems. NASA often employs a model-based approach for its SE process, using Systems Modeling Language (SysML) as the framework.<\/p>\n

Despite their inherently close relationship to SE in practice, SHM\/FM practices have typically not been tightly integrated with SE. Often, SHM\/FM is incorporated only after a nominal system is designed, which essentially makes SHM\/FM a bandage fix for problems after they occur, without considering how issues might have been prevented. In addition, SE and SHM\/FM often involve separate sets of subject matter experts with stove-piped knowledge repositories. This situation can lead to use of modeling methodologies and analyses processes that yield inconsistent results, and can potentially result in inefficiencies throughout the mission life cycle.<\/p>\n

This NASA-funded QSI team\u2019s approach integrates SHM\/FM directly within the MBSE process from the beginning of a project. This method enables the FM design to be evaluated in an operational context by showing how the SHM\/FM schemes mitigate the effects of simulated component-level physical and functional failures. This technique also facilitates trade studies to evaluate the merits of various FM architectures during the design phase.<\/p>\n

Under this SBIR effort, QSI worked with the SysML v2 Submission Team (SST) \u2014 an assorted group of end users, vendors, academics, and government liaisons involved in the development of specifications for SysML v2, which is the latest iteration of SysML. The QSI team incorporated FM concepts and modeling standards into SysML v2, then they demonstrated how SysML v2 models could translate to the failure space models produced by the QSI toolset.<\/p>\n

This capability enables systems engineers to use QSI\u2019s commercial modeling tool set andanalyze the FM aspects of a system design captured in SysML v2. By capturing the causes and impacts of failures, QSI\u2019s toolset enables mission designers to perform Fault Modes, Effects, and Criticality Analyses (FMECAs) and Fault Tree Analyses (FTAs) to analyze, quantify, and improve the diagnostics and availability of the system. Furthermore, the toolset recommends design improvements (e.g., optimal location of sensors onboard the spacecraft) based on the results from such analyses, and it provides these recommendations in industry-standard formats that can be easily understood and incorporated into the design.<\/p>\n

During this SBIR effort, theQSI toolset was also enhanced to interface with an MBSE framework and facilitate the creation, evaluation, and selection of FM concepts for a mission design. The toolset now enables FM concepts to be tested early in the design process so that adequate detection and diagnosis can be built into the system design, which could potentially lower the total cost of development<\/em><\/strong>, facilitate enhanced communication and coordination among mission team members, and reduce development risks (cost and schedule).<\/p>\n

The HelioSwarm Demonstration<\/strong><\/h3>\n

HelioSwarm\u00a0will transform our understanding of turbulence in the solar wind and the connected Sun\u2013Earth system. The mission uses a constellation, or \u201cswarm,\u201d of one hub and eight co-orbiting small satellites to make the first simultaneous, multiscale measurements of magnetic-field fluctuations and proton flows in the dynamic cislunar space environment. Because plasma turbulence transfers energy across many scales, from fluid-scale motions to kinetic-scale particle dynamics, it cannot be fully understood from a single measurement point, or from measurements at only a single scale.\u00a0HelioSwarm\u2019s\u00a0spacecraft will fly with separations ranging from tens to thousands of kilometers, allowing scientists to reconstruct the three-dimensional structure and dynamics of turbulent space plasma. These observations will reveal how energy moves through the solar wind, transforming our understanding of fundamental plasma processes that\u00a0operate\u00a0near Earth, around the Sun, and throughout the universe.<\/p>\n

Plasma turbulence is the process by which energy contained in fluctuating magnetic fields and plasma motion cascades from large to smaller spatial scales. When the cascade approaches small spatial scales associated with kinetic dissipation, the energy transfers into particle heat. Without turbulent cascades in space plasmas, most of the universe would be far colder than observed.\u00a0Because of the fundamental thermodynamic role it plays in fluids, including space plasmas, many contend that turbulent fluids are the most important unsolved problem in classical physics.<\/p>\n

The QSI team created a SysML v2 design model of HelioSwarm subsystems and top-level mission requirements, capturing the flowdown from mission goals to the design. The team then used its enhanced toolset to translate the HelioSwarm SysML v2 model into an FM model. The HelioSwarm models consist of key subsystems of the hub spacecraft and eight node satellites, including subsystems for command and data handling; electric power; attitude control; propulsion, thermal, and separation hardware payload sensors; and ground and space communications. Using the QSI toolset, mission designers then generated FMECAs and FTAs that were translated into a standardized SysML report. Furthermore, these FM analyses generated recommendations (e.g., for sensor placement) that were provided as proposed updates to the system design. This process will support the design of small spacecraft swarms with inherent redundancy to enhance science observations and other NASA goals, such as providing mission support for lunar surface operations.<\/p>\n

Relevance to future NASA missions and non-NASA applications<\/strong><\/h3>\n

The technology developed via this latest SBIR effort could be of high value for future NASA missions \u2014 especially those that require autonomous operation. The QSI TEAMS\u00ae toolset was baselined for Vehicle Systems Management functions on NASA\u2019s Gateway project and retains applicability to future human-rated spacecraft. System design engineers could use this technology to incorporate fault mitigation strategies to improve design with additional insight into the overall system resilience \u2014 right at the beginning of the design phase.<\/p>\n

This technology may also have applications outside of NASA. Comprehensive and efficient FM analyses and architecture trade studies are of critical importance to complex and high-value military systems such as aircraft, surface ships, submarines, and even modern ground-fighting vehicles. Additionally, this technology could be applicable to emerging commercial space systems, civilian aircraft and maritime systems, transportation, and power generation and distribution equipment.
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For additional details about this effort, see the relevant TechPort entries: here<\/a>, here<\/a>, and here<\/a>.<\/a>
Project Lead(s): <\/strong>Dr. Sudipto Ghoshal, Mr. Deepak Haste, Qualtech Systems, Inc.
Sponsoring Organization(s): <\/strong>NASA Ames Research Center<\/p>\n

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