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为实现无人作战飞机(UCAV,Unmanned Combat Aerial Vehicle)认知导航的空间方位自主推算,提出了一种基于多尺度网格细胞的路径整合方法.该方法模拟背侧内嗅皮层(dMEC,dorsal Medial Entorhinal Cortex)的相同区域网格细胞放电特征相同、不同区域放电特征递增变化的特点,构建尺度递增的仿生多尺度网格图组,在各层中引入突触样式(synaptic pattern)计算各细胞权值,通过细胞的活跃度变化表征各网格层中位置的变化,并在各层分别实现路径整合,进而利用低尺度整合结果调整高尺度整合,提高空间位置的推算精度.实验结果表明,所提方法在一定的速度误差与方向误差范围内能够精确推算方位,具有较高的空间位置推算精度,并且方向误差值随运动方向变化呈锯齿状分布. 相似文献
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A method of determining effective elastic properties of honeycomb cores based on equal strain energy
A computational homogenization technique (CHT) based on the finite element method (FEM) is discussed to predict the effective elastic properties of honeycomb structures. The need of periodic boundary conditions (BCs) is revealed through the analysis for in-plane and out-of-plane shear moduli of models with different cell numbers. After applying periodic BCs on the represen-tative volume element (RVE), comparison between the volume-average stress method and the boundary stress method is performed, and a new method based on the equality of strain energy to obtain all non-zero components of the stiffness tensor is proposed. Results of finite element (FE) analysis show that the volume-average stress and the boundary stress keep a consistency over different cell geometries and forms. The strain energy method obtains values that differ from those of the volume-average method for non-diagonal terms in the stiffness matrix. Analysis has been done on numerical results for thin-wall honeycombs and different geometries of angles between oblique and vertical walls. The inaccuracy of the volume-average method in terms of the strain energy is shown by numerical benchmarks. 相似文献
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