Towards improved understanding of naval ship structural performance via virtual hull monitoring

Weight-optimised ships, such as High Speed Light Craft (HSLC), are operated by navies around the world. Naval ships must perform in harsh and contested ocean environments. Operations in high sea states result in large linear and nonlinear ship motions which in turn, induce significant loads on ship structures and accelerate structural fatigue. Monitoring and assessment of fatigue on ship structures is important for navies, to understand the performance, limitations, and life-cycle costs of their ships. An established method for monitoring structural responses is via long-term measurements, using Instrumented Hull Monitoring (IHM). However, this approach is generally too resource-intensive to be implemented on a broad scale. Virtual Hull Monitoring (VHM) is a technique to couple on-board ship data, such as Global Positioning System (GPS) data, with hindcast wave data. The resulting enriched dataset enables robust numerical fatigue analysis, because the structural responses are related to the encountered wave environment, rather than based on global wave statistics. Thus, the concept of VHM is receiving increased attention in both commercial and military sectors. This is due to its low cost and the relative ease of implementation compared to IHM. Using a Royal Australian Navy HSLC as the test bed, this study presents an investigation into the feasibility of VHM by comparing results with available IHM data. An efficient framework was developed in PythonTM to extract and couple hindcast wave data to ship speed and position, calculating the resultant stresses on the ship structure, and comparing with the measured stresses from IHM. The novel aspects of this work include the use of a semi-displacement hullform, and the utilisation of both sea-trials and long-term measurements. The study shows promising results for VHM. Finally, recommendations for further work are provided.