Interaction between sea ice/iceberg and ship structures: A review

For ship structural design and good maneuverability in an ice-covered sea, the local and global load of ice cover on ships should be well understood. This paper reviews the extensive work done on ice loads on ships, including： （a） Ice pressure and local load determination based on field and model tests; （b） Global ice loads on ships from full-scale field observations, model tests and numerical models under different ice conditions （level ice and pack ice） and ship operations （maneuvering and mooring）. Spe- cial attention is paid to the discrete element simulation of global ice loads on ships; and （c） Analytical solutions and numerical models of impact loads of icebergs on ships for polar navigation. Finally, research potential in these areas is discussed.

Preparation and Corrosion Resistance of Rare Earth Conversion Coatings on AZ91 Magnesium Alloy

The feasibility of forming pollution-free and environmentally benign Ce-based rare earth conversion coatings （short for RECCs） on AZ91 magnesium alloy to enhance corrosion resistance was studied. The effect of optimum processing parameters on corrosion resistance of RECCs, such as density of treating solution, temperature and time of coating formation were discussed. Protective performance of conversion coatings on magnesium alloy was evaluated by moisture/heating test, anodic polarization, etc. The results show that Ce-based RECCs under moisture/heating condition can remain intact, with high coverage and no obvious corrosion phenomenon. Corrosion potential increases and passive phenomenon occurs while current density decreases, therefore Ce-based RECCs can improve corrosion resistance of AZ91 magnesium alloy. The morphology of Ce-based RECCs prepared under optimum process through SEM observation is found to be a few particles coherent to the base coating, and the coating has no cracks and exhibits apparent corrosion resistance during corrosion courses of AZ91 magnesium alloy.

Cell Consistency Evaluation Method Based on Multiple Unsupervised Learning Algorithms

Unsupervised learning algorithms can effectively solve sample imbalance.To address battery consistency anomalies in new energy vehicles,we adopt a variety of unsupervised learning algorithms to evaluate and predict the battery consistency of three vehicles using charging fragment data from actual operating conditions.We extract battery-related features,such as the mean of maximum difference,standard deviation,and entropy of batteries and then apply principal component analysis to reduce the dimensionality and record the amount of preserved information.We then build models through a collection of unsupervised learning algorithms for the anomaly detection of cell consistency faults.We also determine whether unsupervised and supervised learning algorithms can address the battery consistency problem and document the parameter tuning process.In addition,we compare the prediction effectiveness of charging and discharging features modeled individually and in combination,determine the choice of charging and discharging features to be modeled in combination,and visualize the multidimensional data for fault detection.Experimental results show that the unsupervised learning algorithm is effective in visualizing and predicting vehicle core conformance faults,and can accurately predict faults in real time.The“distance+boxplot”algorithm shows the best performance with a prediction accuracy of 80%,a recall rate of 100%,and an F1 of 0.89.The proposed approach can be applied to monitor battery consistency faults in real time and reduce the possibility of disasters arising from consistency faults.

Research on fast solid state DC breaker based on a natural current zero-crossing point

The DC fault characteristics of voltage source converter based high voltage direct current(VSC-HVDC)systems are analyzed in this paper.The phenomenon whereby the capacitor on DC side discharges quickly during a DC fault contributes to a large short-circuit fault current.Neither traditional DC breakers nor DC switches can cut off the fault current under this condition.A fast solid state DC breaker design method is proposed in this paper.This method is based on the fault current characteristics of the inverter in multi-terminal HVDC systems(MTDC),where a fault current appears at the natural zerocrossing point near the inverter.At this point,by coordinating the AC breakers near the rectifier,the DC breaker could reliably cut off the DC fault current and protect the system.A detailed model for this fast solid state DC breaker and its operation sequence are studied,based on this design method.Simulations modeling a five-terminal meshed DC grid and a fast DC breaker were carried out with PSCAD/EMTDC using this design method.The results from the simulations confirmed the validity of the design method.

Formation of CMK-3/Co_3O_4 nanosheets on nickel foam with markedly enhanced pseudocapacitive properties

Composites of mesoporous carbon（CMK-3） and Co3 O4 nanosheets grown on nickel foam were successfully synthesized by a simple route. A bare Co3 O4 film was synthesized for comparison. With the addition of CMK-3, the Co3 O4 nanoparticles self-organize and agglomerate into nanosheets, showing a significant influence by CMK-3 on the morphology. The CMK-3/Co3 O4 exhibits an optimal specific capacitance of 1131.3 Fg^（-1） in 3 mol L-1 KOH aqueous electrolyte at 0.5 Ag-1, and a retention ratio of 91% over3000 cycles, both being much higher than that achieved from the bare Co3 O4 film（727 Fg^（-1） of specific capacitance, and 82% capacitance retention ratio）, indicating that the CMK-3/Co3 O4 nanosheets are very promising as electrode materials for supercapacitor applications.

Cloud-Data Envelopment Analysis Method Used for Assessment of Restoration Building Block Schemes

The selection of an optimized restoration building block(RBB)scheme among all available schemes is one of the most important factors impacting the power system restoration process after a complete or partial blackout.This paper presents a data envelopment analysis(DEA)model used as an empirical method to assess the RBB schemes.An N-level evaluation scale cloud system is built based on cloud theory to transform qualitative I/O indices of DEA model into quantitative values.Through joint utilization of the CCR(Charnes,Cooper and Rhodes)model and the LJK(Li,Jahanshahloo and Khodabakhshi)model,the established Joint-DEA model makes the newly proposed Cloud-DEA method a more feasible and robust method in assessment of RBB schemes.