NASA SBIR 2018-II Solicitation

Proposal Summary

 18-2- S5.05-6243
 Fault Management Technologies
 Integrated Model-Based Fault-management System Design (IMFSD)
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
ASCA, Inc.
1720 South Catalina Avenue, Suite 220
Redondo Beach, CA 90277
(310) 316-6249

PRINCIPAL INVESTIGATOR (Name, E-mail, Mail Address, City/State/Zip, Phone)
Dr. Michael Yau
1720 S Catalina Ave, Suite 220
Redondo Beach, CA 90277 - 5504
(310) 316-6249

BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Sergio Guarro
1720 S Catalina Ave, Suite 220
Redondo Beach, CA 90277 - 5504
(310) 569-9673

Estimated Technology Readiness Level (TRL) :
Begin: 3
End: 5
Technical Abstract (Limit 2000 characters, approximately 200 words)

ASCA is developing an Integrated Model-based Fault-management System Design (IMFSD) workstation for current-generation and future high-autonomy space systems. The resulting product will integrate and document in one framework Fault Management (FM) design processes, models and products. The IMFSD covers FM requirements definition, design specification, analysis, validation-and-verification (V&V), and documentation. This provides the connection of the associated processes and models to the corresponding elements of the host space system model-based design. 

The integration of FM development life-cycle processes is achieved by means of a “design development, documentation, and assurance case” (D3AC) logic structure hosted within the IMFSD software platform, which provides active connectivity among all elements of the FM design, and with the evidences produced to demonstrate compliance with FM design and operations goals, and with the derived requirements.

In view of expected spacecraft-autonomy evolutions for which expanded FM operational capability and analytics will be needed, the IMFSD, in addition to established FM models like Fault Tree Analysis and Failure Modes and Effects Analysis, includes, or links to, logic-dynamic models and AI decision / action selection models – e.g., Dynamic Flowgraph Methodology, Markov Cell-to-Cell Mapping Technique – that can extend FM analysis into the time-dependent-logic domain. Other potentially applicable state-of-the-art models from the field of machine-learning, like Bayesian Belief Networks, Neural Networks, Fuzzy Logic, and Influence Diagrams, are also evaluated and demonstrated for evolutionary inclusion in the IMFSD.

Once demonstrated for NASA applications, the IMFSD will be transferable to the design of FM for the high-autonomy commercial systems that are presently being developed in the aeronautical and road transportation fields. This provides a path for commercialization efforts that will be initiated during Phase II.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

The IMFSD workstation, hosted on a commercial MBSE platform, integrates in one environment the Fault Management (FM) design of NASA space systems, and is also applicable to aeronautical systems, manned and unmanned. Its ability to support the convergence of FM and AI functionality makes the IMFSD especially well suited to support the design of autonomy in space systems.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

The IMFSD can support risk-scenario management, fault management, and safety analysis of autonomous vehicles of many kinds, i.e.: driver-less automotive road vehicles; Unmanned Aerial Vehicles (UAVs); commercial space vehicles; commercial aircraft; marine vessels and probes. Its implementation on a commercial MBSE platform will facilitate access for these potential uses.

Duration: 24

Form Generated on 05/13/2019 13:33:46