In most previous ice–ship interaction studies involving fluid effects, ice was taken as unbreakable. Building breakable level ice on water domain is still a big challenge in numerical simulation. This paper overcomes this difficulty and presents a numerical modeling of a ship moving in level ice on the water by using a one-way CFD-DEM (computational fluid dynamics-discrete element method) coupling method. The detailed numerical processes and techniques are introduced. The ice crack propagation process including radial and circular cracks have been observed. Numerical results are compared with previous experimental data and good agreement has been achieved. The results show that water resistance is an order of magnitude smaller than ice resistance during the ice-breaking process. Ice resistance shows strong oscillation along with ice failure process, which are affected by ship speed and ice thickness significantly.

In railway electrification systems, the harmonic impedance of the traction network is of great value for avoiding harmonic resonance and electrical matching of impedance parameters between trains and traction networks. Therefore, harmonic impedance identification is beneficial to suppress harmonics and improve the power quality of the traction network. As a result of the coupling characteristics of the traction power supply system, the identification results of harmonic impedance may be inaccurate and controversial. In this context, an identification method based on a data evolution mechanism is proposed. At first, a harmonic impedance model is established and the equivalent circuit of the traction network is established. According to the harmonic impedance model, the proposed method eliminates the outliers of the measured data from trains by the Grubbs criterion and calculates the harmonic impedance by partial least squares regression. Then, the data evolution mechanism based on the sample coefficient of determination is introduced to estimate the reliability of the identification results and to divide results into several reliability levels. Furthermore, in the data evolution mechanism through adding new harmonic data, the low-reliability results can be replaced by the new results with high reliability and, finally, the high-reliability results can cover all frequencies. Moreover, the identification results based on the simulation data show the higher reliability results are more accurate than the lower reliability results. The measured data verify that the the data evolution mechanism can improve accuracy and reliability, and their results prove the feasibility and validation of the proposed method.

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