Abstract

In this study, Al-Mg-Si alloy plates in 4 mm thickness that are particularly used for aerospace and automotive industries were welded using Tungsten Inert Gas (TIG) welding and Friction Stir Welding (FSW) methods as similar joints with one side pass with parameters of varying tool rotation, weld speed and 2.3 degree tool tilt angle. Tensile tests results showed high yield stress values for FSW joints. Micro Vickers hardness test gave the required result for FSW welded and TIG welded Al-Mg-Si alloy plates. While fatigue test results showed all similar welded joints have fatigue strength close to each other.

Abstract

During the design of a vessel or marine artefact, one of the main objectives is to ensure a long service life. The structure of these artefacts is essential to achieve this goal, as it is responsible for withstanding the extremely unfavourable stresses of the high seas. The aim of this paper is to present a method of detailed structural assessment by applying a dynamic hydroelastic model [1] that allows structural verification by greatly reducing the calculation time without losing accuracy. The current procedures used for this purpose require a detailed study of each loading condition, which implies many simulation hours and high computational cost. In this model, the high-fidelity structural solution is projected onto the modal basis to get the system modal matrix and extend the response amplitude operators (RAO) to the modal response amplitude operators (MRAO) of the structure. By retaining only those eigenmodes that preserve most of the structural elastic energy, the number of structural degrees of freedom can be significantly reduced. This reduced model has been implemented and coupled in the time domain with the seakeeping software SeaFEM, enabling quick analysis of a large number of load cases of the structure [2]. In this work, the first case study of a ship is presented.

Abstract

Digital twins (DTs) offer significant promise for condition-based maintenance of floating offshore wind turbines (FOWTs); however, existing solutions typically compromise either on physical rigor or real-time computational performance. This paper presents a real-time DT framework that resolves this trade-off by embedding a hydro-elastic reduced-order model (ROM) that accurately captures structural dynamics and fluid–structure interaction. Integrated in a cloud-ready Internet of Things architecture, the ROM reconstructs full-field displacements, von Mises stresses, and fatigue metrics with near real-time responsiveness. Validation on the 5 MW OC4-DeepCWind semi-submersible platform shows that the ROM reproduces finite-element (FEM) displacements and stresses with relative errors below 1%. A three-hour load case is solved in 0.69 min for displacements and 3.81 min for stresses on a consumer-grade NVIDIA RTX 4070 Ti GPU—over two orders of magnitude faster than the full FEM model—while one million fatigue stress histories (1000 hotspots×1000 operating scenarios) are processed in 37 min. This efficiency enables continuous structural monitoring, rapid *what-if* assessments and timely decision-making for targeted inspections and adaptive control. By effectively combining physics-based reduced-order modeling with high-throughput computation, the proposed framework overcomes key barriers to DT deployment: computational overhead, physical fidelity and scalability. Although demonstrated on a steel platform, the approach is readily extensible to composite structures and multi-turbine arrays, providing a robust foundation for cost-effective and reliable deep-water wind-energy operations.