. Incompressible SPH method based on Rankine source solution for violent water wave simulation. Journal of Computational Physics, 276, pp. 291-314. doi: 10.1016Physics, 276, pp. 291-314. doi: 10. /j.jcp.2014 This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent AbstractWith wide applications, the smoothed particle hydrodynamics method (abbreviated as SPH) has become an important numerical tool for solving complex flows, in particular those with a rapidly moving free surface. For such problems, the incompressible Smoothed Particle Hydrodynamics (ISPH) has been shown to yield better and more stable pressure time histories than the traditional SPH by many papers in literature. However, the existing ISPH method directly approximates the second order derivatives of the functions to be solved by using the Poisson equation. The order of accuracy of the method becomes low, especially when particles are distributed in a disorderly manner, which generally happens for modelling violent water waves. This paper introduces a new formulation using the Rankine source solution. In the new approach to the ISPH, the Poisson equation is first transformed into another form that does not include any derivative of the functions to be solved, and as a result, does not need to numerically approximate derivatives. The advantage of the new approach without need of numerical approximation of derivatives is obvious, potentially leading to a more robust numerical method. The newly formulated method is tested by simulating various water waves, and its convergent behaviours are numerically studied in this paper. Its results are compared with experimental data in some cases and reasonably good agreement is achieved. More importantly, numerical results clearly show that the newly developed method does need less number of particles and so less computational costs to achieve the similar level of accuracy, or to produce more accurate results with the same number of particles compared with the traditional SPH and existing ISPH when it is applied to modelling water waves.

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The water entry problem of a wedge through free fall in three degrees of freedom is studied through the velocity potential theory for the incompressible liquid. In particular, the effect of the body rotation is taken into account, which seems to have been neglected so far. The problem is solved in a stretched coordinate system through a boundary element method for the complex potential. The impact process is simulated based on the time stepping method. Auxiliary function method has been used to decouple the mutual dependence between the body motion and the fluid flow. The developed method is verified through results from other simulation and experimental data for some simplified cases. The method is then used to undertake extensive investigation for the free fall problems in three degrees of freedom.

The Smoothed Particle Hydrodynamics (SPH) method is a mesh-less numerical modeling technique. It has been applied in many different research fields in coastal engineering. Due to the drawback of its kernel approximation, however, the accuracy of SPH simulation results still needs to be improved in the prediction of violent wave impact. This paper compares several different forms of correction on the first-order derivative of ISPH formulation aiming to find one optimum kernel approximation. Based on four benchmark case analysis, we explored different kernel corrections and compared their accuracies. Furthermore, we applied them to one solitary wave and two dam-break flows with violent wave impact. The recommended method has been found to achieve much more promising results as compared with experimental data and other numerical approaches.

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Accurate and reliable short-term prediction of ship motions offers improvements in both safety and control quality in ship motion sensitive maritime operations. Inspired by the satisfactory nonlinear learning capability of a support vector regression (SVR) model and the strong non-stationary processing ability of empirical mode decomposition (EMD), this paper develops a hybrid autoregressive (AR)-EMD-SVR model for the short-term forecast of nonlinear and non-stationary ship motion. The proposed hybrid model is designed by coupling the SVR model with an AR-EMD technique, which employs an AR model in ends extension. In addition to the AR-EMD-SVR model, the linear AR model, non-linear SVR model, and hybrid EMD-AR model are also studied for comparison by using ship motion time series obtained from model testing in a towing tank. Prediction results suggest that the non-stationary difficulty in the SVR model is overcome by using the AR-EMD technique, and better predictions are obtained by the proposed AR-EMD-SVR model than other models.