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Naval structures are subjected to damage that occurs on short-term (i.e. impact) and long-term (i.e. fatigue) time scales. Digital twins of ship structures can provide real-time condition assessments and be leveraged by a decision-making framework to enable informed response management that will increase ship survivability during engagements. A key challenge in the development of digital twins is the development of methodologies that can distinguish the various fault cases. Moreover, these methodologies must be able to operate on the resource-constrained computing environments of naval structures while meeting real-time latency constraints. This work reports on recent progress in the development of a multi-event model updating framework specially designed to meet stringent latency constraints while operating on a system with constrained computing resources. The proposed methodology tracks structural damage for both impact and fatigue damage through a swarm of particles that represent numerical models with varying input parameters with set latency and computational restraints. In this work, numerical validation is performed on a structural testbed subjected to representative wave loadings. Results demonstrate that continuous fatigue crack growth and plastic deformation caused by impact can be reliably distinguished. The effects of latency and resource constraints on the accuracy of the proposed system are quantified and discussed in this work.
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Jason Smith, Hung-Tien Huang, Austin Downey Jr., Alysson Mondoro, Benjamin Grisso, Sourav Banerjee, "Multi-event model updating for ship structures with resource-constrained computing," Proc. SPIE 12046, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2022, 120460E (18 April 2022); https://doi.org/10.1117/12.2628962