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Regeneration of surface roughness by the Langevin equation using stochastic analysis on AFM image of a carbon fiber

机译:基于碳纤维AFM图像随机分析的Langevin方程再生表面粗糙度

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A new method was developed using AFM images of a fiber surface to regenerate the surface roughness in 3D geometry, such as the cylindrical shape of a "model" fiber. The Langevin equation was used to derive the fluctuations of a carbon fiber surface image. The equation contains two quantities, D~((1)) (h) and D~((2)) (h) which in physics represent drift and diffusion coefficients. Knowing this coefficient and adding a proper noise function, a similar surface of larger dimension with the same statistical properties of the initial data was created. The generated surface was mapped into cylindrical coordinates, then a mesh generated. The resulting reconstructed surface, input over the geometry of a cylindrical shape, can be implemented for finite element analysis of a single fiber surrounded by matrix and generalized to a many fiber model.
机译:开发了一种使用纤维表面的AFM图像重新生成3D几何形状(例如“模型”纤维的圆柱形状)的表面粗糙度的新方法。 Langevin方程用于导出碳纤维表面图像的波动。该方程包含两个量,D〜((1))(h)和D〜((2))(h),在物理上代表漂移系数和扩散系数。知道该系数并添加适当的噪声函数,就可以创建具有较大尺寸的相似表面且具有与初始数据相同的统计属性。将生成的曲面映射到圆柱坐标中,然后生成网格。输入到圆柱形状的几何体上的最终重建表面可以用于对矩阵包围的单根光纤进行有限元分析,并推广到多光纤模型。

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