Abstract Offshore wind turbines have only been operated for about 30 years but they represent one of the most promising branches of renewable energy. The ever-increasing size of the turbines is beginning to pose both technological and logistical challenges, while the ambitious goals towards decarbonisation appear to be increasingly difficult to achieve. One way to take advantage of undeveloped offshore areas with high wind potential is the use of floating support structures. This kind of operation has not yet been carried out with tension leg platforms, so its feasibility requires detailed analysis. The main aim of this research is to evaluate the movements of a physical model of a 14 MW TLP floating wind turbine during towing to its installation site. For this purpose, a detailed design of a novel five-leg TLP support structure was established, its stability in a temporary floating state was assessed, and the results of model testing on towing the structure in regular waves were examined. The experimental findings were further compared with numerical simulations, providing additional insight into the hydrodynamic behaviour of the platform during towing.

Abstract The removal of subsea objects from the seabed is a crucial challenge for the offshore industry, necessitating the accurate prediction of pull-out resistance from an engineering perspective. To address this problem, a parametric analysis was undertaken to investigate how seabed properties influence the extrication force and the critical extrication time required to detach an axisymmetric object from a sandy sea bottom. The ranges for selected seabed parameters, including soil shear modulus, Poisson’s ratio, permeability coefficient, porosity, bulk modulus of pore water, and water viscosity, were established based on data from the existing soil and fluid mechanics literature. The results indicate that achieving robust and reliable estimates of the maximum extrication force and the critical extrication time in practical scenarios, such as underwater engineering and marine salvage, requires direct laboratory determination of the bulk modulus of water and the permeability coefficient and porosity, through tests on in-situ seabed and water samples. In contrast, appropriate values of the shear modulus, Poisson’s ratio, and water viscosity can be sourced from the existing literature, provided that the type and condition of the seabed soil are accurately characterised.

Abstract To address the issues of fault localisation and recovery in medium-voltage direct current power systems for ships, this paper proposes a hybrid reconstruction algorithm that combines the entropy weighting method with grey relational analysis, and embeds them within a framework based on chaotic particle swarm optimisation. During initialisation, the algorithm employs chaotic mapping to enhance the population diversity. The entropy weighting method is used for adaptive weighting of the objective functions, while grey relational analysis is integrated to evaluate the particle fitness and determine optimal reconstruction paths, thereby accomplishing fault diagnosis and system restoration. Simulations and case studies demonstrate that the proposed method has advantages such as rapid convergence and strong ability to escape local optima. Compared with traditional methods, it achieves a 41% increase in the reconstruction success rate and a 4.7% improvement in the system restoration capability, effectively enhancing post-fault power supply capacity and overall reliability.

Abstract The problem of an axisymmetric engineering object detachment from a poroelastic water-saturated seabed is investigated. This involves the determination of forces which are required to release a body from the seabed and the corresponding times at which this occurs. The solution of the problem involves: (1) calculation of the displacements of the seabed, performed by employing an analytical solution to the Boussinesq problem, known from the theory of elasticity; and (2) analytical description of the evolution of the gap thickness and water pressure between the object and the seabed via applying the boundary layer approximation by Foda (1982). The proposed model is used to analyse two scenarios, in which time-histories of either the pulling force magnitude or the object vertical uplift velocity are prescribed. For both scenarios, breakout times and associated breakout forces are calculated for a range of parameters defining the elastic and hydraulic properties of the seabed; the results of these calculations are presented. The limit case of a rigid porous seabed is also considered.

Abstract With the rapid development of maritime transportation, the issue of safe navigation for ships in complex and ever-changing marine environments has attracted increasing attention. Hull girder load is regarded as an important indicator of wave-induced loads during ship navigation and its prediction plays a crucial role in ensuring hull structural safety. To overcome the time-consuming nature of nonlinear load predictions in viscous flows caused by fluid-structure interaction, a data-driven load prediction model is proposed by combining Bayesian optimisation (Bo), a Long Short-Term Memory neural network (LSTM) and a Transformer algorithm. In our research, the navigational status of a S175 ship is simulated using the CFD-FMA method. These navigational data are then used to establish the Bo-Transformer-LSTM model to predict the load fluctuations along the ship’s length. The impacts of factors such as input sources, prediction ranges, and wave cases are investigated for this hybrid model. Its advantage is also illustrated by comparing it with the traditional data-driven algorithms, such as BP, RBF and LSTM. In addition, the wider practicality of the hybrid model is further verified by the application of the transfer learning strategy. This research can provide a reliable rapid prediction approach for wave load assessment and contribute to the optimal design of hull structures.

Abstract The fault diagnosis of marine propulsion motors has been an important focus of attention in the marine industry. Various types and numbers of sensors have been used to monitor and diagnose faults in permanent magnet propulsion motors, and the comprehensive application of multi-sensor signals has played a key role in improving fault diagnosis performance, but the issue of how to efficiently exploit this multi-source information remains a difficult problem. In this paper, we propose a multi-sensor-signal feature-level fusion method based on a multi-input convolutional neural network and a CBAM attention mechanism, which fully utilises the end-to-end learning capability of deep learning and the interpretability and domain expert knowledge of traditional methods. A synchrosqueezing wavelet transform is used to extract the high-resolution feature information of the current and vibration signals; the multi-input neural network extracts the high-level abstract features in the current and vibration signals; the CBAM attention mechanism is introduced to make the network more targeted, to deal with the key feature information; and a Bayesian optimisation algorithm is used to automatically determine suitable combinations of hyperparameters for training of the network. A fault test of a permanent magnet synchronous motor shows that the diagnostic accuracy of the proposed method reaches 99.08%, a value 1.29% higher than a scheme without the CBAM attention mechanism, with an increase in the detection time for each sample of only 2.33 ms. Our approach also has better anti-noise interference ability and generalisation performance.

Abstract A novel dual-impact horizontal rotor wave energy converter (DHRWEC) system was designed to accommodate the short wave periods and low wave heights that are typical of China’s coastal regions, based on a combination of wave concentration and amplification technology with a four-point catenary mooring system. This study investigates the stability and survivability of the DHRWEC system under actual sea conditions. Numerical simulations and experimental validations are conducted to assess the performance of the system. The results indicate that if even one anchor chain fails under extreme conditions, the safety factor of the remaining chain’s maximum mooring force exceeds three, meaning that it meets international safety standards. The maximum surge and sway displacements are found to be 5.5 m and 3.0 m, respectively, values that align well with predictions from simulations and which confirm stable operation in the designated position. No risk of capsizing is detected, indicating that the system is robust in real sea environments. Sea trials also confirm reliable startup and give an energy conversion efficiency of about 21.33%. These findings offer valuable insights for the development of similar technologies, and provide a solid foundation for the practical application and sustained operation of the system.

Abstract Composite structures are widely used for marine applications such as yachts and wind turbine blades, due to their high mechanical strength, corrosion resistance, and favourable strength-to-weight ratio. In marine environments, however, they are exposed to numerous types of damage, resulting from mechanical, environmental, and fatigue-related factors. Effective repair methods for these structures, such as patch bonding, resin injection, and ply replacement, allow for partial restoration of their functionality without the need for costly replacement. A key aspect is the proper selection of the repair technology, which should take into account the type of damage, operating conditions, and material properties. The application of advanced diagnostic techniques, such as acoustic emission, enables early detection of defects and effective quality control of repairs; moreover, acoustic emission provides insights into the service parameters of such repairs. In this study, a damage scenario involving a composite structure was considered, and a stepped repair was designed and executed. Samples of composite material, both before and after repair, were prepared for static tensile testing to determine their strength parameters. Acoustic emission was also employed during the tensile tests to identify the values of stress at which damage initiation occurred, as well as to obtain the serviceability parameters. The results showed that the developed stepped repair scheme yielded strength parameters that were only slightly lower than those of the undamaged base composite. However, acoustic emission data revealed that the onset of damage in the repaired specimens occurred at significantly lower stress levels, indicating a considerable weakening of the composite structure as a result of the repair process.

Abstract This work presents a 3D numerical study of a steam-injected combustor for a gas turbine operating on an ammonia-hydrogen fuel blend, aimed at enabling carbon-free hybrid energy systems. The research focuses on the performance and emission characteristics of a 32 MW engine’s combustor. Using Computational Fluid Dynamics (CFD) with a detailed chemical kinetics mechanism (203 reactions, 31 species), the model solves the governing equations for turbulent reacting flow. The simulations provide new insights into ammonia-hydrogen flame propagation within intensely swirled flows under staged air and steam admission. Key energy and environmental parameters for the combustor are obtained. The results support the design of advanced combustors for decarbonised gas turbine systems.

Abstract The objective of this study is to ascertain the cavitation noise characteristics of an integrated motor pump-jet (IMP) propulsor. The far-field cavitation radiation noise of the propulsor is analysed using computational fluid dynamics and acoustic coupling methods. The results indicate that in comparison with non-cavitation noise, the IMP propulsor generates an increased level of noise as a consequence of cavitation. Strong correlation is observed between the variables of cavitation volume pulsation and radiation noise. The initial rise in the overall sound pressure level of the radiation noise inside the propulsor is followed by a gradual increase as the degree of cavitation deepens. Concurrently, the total noise increases, while the significance of the blade frequency weakens. Variations in the blade tip gap have a pronounced influence on the intensity of cavitation noise. Under identical conditions in terms of the axial gap, the cavitation noise attains its minimum level when the radial gap is set to 3 mm. Conversely, an increase in the axial gap results in a corresponding rise in cavitation noise when the radial gap remains constant. The findings of this study will provide valuable insights for the noise control of IMP propulsors.