Online Structural Model Updating for Ship Structures Considering Impact and Fatigue Damage

Abstract

Naval ship structures (i.e., supports, hull, driving machinery, etc.) have various damage states that develop on short-term (i.e., impact) and long-term (i.e., fatigue) time scales. An up-to-date digital twin of ship structures that can deliver condition assessment in real time would empower a real-time decision-making framework to undertake informed response management. Together, the digital twin and decision-maker will increase ship engagement survivability during combat events and reduce the severity of long-term fatigue effects. A core challenge in digital twin development is the advancement of reliable methodologies that distinguish the short-term and long-term damage states. Furthermore, these methodologies must effectively assimilate large amounts of data into physics-based or data-driven prognostics models while operating on the naval structure’s resource-constrained computing environments and considering stringent real-time latency constraints. This work details the experimental validation of a specially designed multievent model updating framework that meets strict real-time latency constraints while operating on a system with limited computational resources. The proposed methodology tracks both impact and fatigue structural damage using a particle swarm that represents numerical models with varying input parameters, given set constraints for latency and computational resources. Experimental validation of the proposed methodology is undertaken using data collected from a structural testbed designed to provide responses representative of a ship subjected to fatigue and impact, considering a predetermined wave loading. Results demonstrate that a physics-based model of the structure can be updated in real time while distinguishing between plastic deformation caused by impact and continuous fatigue crack growth. Latency effects, resource-constrained accuracy, and parameter optimization of the proposed system are quantified and further discussed in this work.