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One of sea ice core samples was taken from Arctic by the First Chinese National Arctic Research Expedition Team in 1999. 20 vertical and 2 horizontal ice sections were cut out of the ice core sample 2.22 m in length, which covered the ice sheet from surface to bottom except losses for during sampling and section cutting. From the observation and analysis of the fabrics and crystals along the depth of the ice core sample, followings were found. Whole ice sheet consists of columnar, refrozen clastic pieces, granular, columnar, refrozen clastic pieces, granular, columnar and refrozen clastic pieces. This indicates that the ice core sample was 3-year old, and the ice sheet surface thawed and the melt water flowed into ice sheet during summer. Hence, the annual energy balance in Arctic can be determined by the ice sheet surface thawing in summer, and bottom growth in winter. The thickness of the ice sheet is kept constantly at a certain position based on the corresponding climate and ocean conditions; A new 相似文献
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One of sea ice core samples was taken from Arctic by the First Chinese National Arctic Research Expedition Team in 1999. 20 vertical and 2 horizontal ice sections were cut out of the ice core sample 2.22 m in length, which covered the ice sheet from surface to bottom except losses for during sampling and section cutting. From the observation and analysis of the fabrics and crystals along the depth of the ice core sample, followings were found. Whole ice sheet consists of columnar, refrozen clastic pieces, granular, columnar, refrozen clastic pieces, granular, columnar and refrozen clastic pieces. This indicates that the ice core sample was 3-year old, and the ice sheet surface thawed and the melt water flowed into ice sheet during summer. Hence, the annual energy balance in Arctic can be determined by the ice sheet surface thawing in summer, and bottom growth in winter. The thickness of the ice sheet is kept constantly at a certain position based on the corresponding climate and ocean conditions; A new 相似文献
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神经网络在岩体力学参数和地应力场反演中的应用 总被引:13,自引:7,他引:13
BP神经网络已广泛地应用于岩体力学参数和初始应力场的反演分析,但在实际应用中,BP网络存在着网络训练易于过度、收敛速度慢、易陷入局部极小以及隐层节点数难于确定等缺点。采用RBF网络和改进的BP网络,利用基于有限差分格式的快速拉格朗日算法进行正分析计算,依据若干测点的正应力数据,反演了计算区域的岩体力学参数以及初始应力场。算例表明,RBF神经网络与快速拉格朗日算法相结合,在样本容量相同的情况下,反演分析的精度、网络的拓扑结构以及学习、收敛速度,均优于采用BP网络的反演算法。 相似文献
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The sea ice is idealized as an elastic-brittle material. When an ice sheet moves toward a structure, the dynamic in-teraction between ice and the structure is analyzed by the DDA (Discontinuous Deformation Analysis) approach, where the ice sheet and the structure are considered as assemblages of blocky masses. This has the advantages that the whole process of collision between the ice and structure can be shown visually vvith a series of pictures. Meanwhile, the dynamic response of the structure at each time step after the bumping of the ice against the structure is calculated. And with the aid of inverse analysis developed by the authors, the time history of the resultant ice force exerting on the structure is evaluated. A numerical example shows that the proposed approach is suitable to the simulation of the ice-breaking process and reasonable result of ice force acting on the structure can be obtained. 相似文献
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