SBIR/STTR Research Award

TEAMS Fault Management Extension for State-based Design and Simulation

Award identifier 1c5c0e21cb645729e0244973a9410155387fb24b315d79eb841c0dec37fda5e6Awarding agency National Aeronautics and Space Administration

Award amount

$156,476

Program and phase

SBIR · Phase I

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
QUALTECH SYSTEMS, INC.
Proposal award date
2023-07-20
Contract end date
2024-02-02
UEI
T2RXVVH2H735
Solicitation number
SBIR_23_P1
Topic code
S17

Research abstract

Reliable Vamp;V and testing of fault management (FM) during design, implementation and operations is an essential part of systems engineering design and development of critical space programs such as the SLS, Gateway and Artemis.nbsp;NASArsquo;s Mission and Fault Management group currently utilizes SAM to assess nominal andnbsp;FM algorithms prior to full-scale real-time testing, to proactively check potential algorithm changes before finalizing algorithm design and to search for integration issues across multiple subsystems, vehicles, and systems. However, exploring large set of state transitions driven bynbsp;multiple component failure modes and their impactsnbsp;is challengingnbsp;for large interconnected systems such as the Gateway.The key innovation in this proposal is to bridge the gap between state machine modeling which seeks a top-level system view for FM and the more bottom-up physical and functional failure models by connecting state machine modeling tools such as MathWorksreg; Stateflow andnbsp;the newest revision 2 of vendor-neutral Systems Modeling Language (SysML v2),nbsp;tonbsp;industry-adopted and commercial FM design, analysis, and verification methods, via use of the commercial-off-the-shelf TEAMSreg; tool. Connecting component failure modes to their failure functions, functional failure propagation and their manifestations in various effects are suitably poised to drive a complex sequence of state transitions as modelednbsp;in SAM for various subsystems and subsystems and allows for a significantly improved coverage (e.g., through a rich set of what-if failure scenarios) for the off-nominal behavioral models as captured in SAM by incorporating the functional failure models such as in TEAMSreg; as their driver. Doing this combines the best qualities of each model and itsnbsp;associated analytical and operational capabilities to take advantages of what each tool and methodology does best. In essence, the State Machine Model and TEAMSreg; models will provide single sources of truth for modeling and analysis.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

113 SBIR/STTR records share this UEI (1995–2025). Reported award amounts total $44,387,946. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: National Aeronautics and Space Administration, Department of Defense, Department of Energy

Agency intelligence

National Aeronautics and Space Administration

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.