Method for establishing two-dimensional stochastic pore model of fiber reinforced composite with large dispersion pore size
A pore size and fiber-reinforced technology, applied in the analysis of suspensions and porous materials, 2D image generation, image data processing, etc., can solve problems such as large deviations between experimental and theoretical analysis, and lack of information on large-sized pores
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[0022] (1) Dissect the tested sample along the direction perpendicular to the fiber, observe and count the section porosity and pore size with a metallographic microscope. Repeat the above steps more than 20 times to obtain the sample space of the volume porosity and pore size of the standard sample;
[0023] (2) Classify all pores according to the pore length, the pores with a length less than 50 μm are the primary pores, and the pores with a pore length greater than or equal to 50 μm are the secondary pores, and the porosity and pore size of the pores at all levels are counted;
[0024] (3) Select Gaussian autocorrelation function: Where a and b are the autocorrelation lengths: the preliminary value of the primary pore is: a=4.4μm, b=3.6μm; the preliminary value of the secondary pore is: a=22μm, b=10.1μm. Will Perform a two-dimensional fast Fourier transform to get Generate a two-dimensional random field θ∈[0, 2π]; construct a random power spectrum Perform inverse Fo...
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