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

Inactive Publication Date: 2012-07-04
DALIAN UNIV OF TECH
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Problems solved by technology

However, for fiber-reinforced composites with large pore size dispersion, the use of the above random pore model will result in the loss of large-size pore info

Method used

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  • Method for establishing two-dimensional stochastic pore model of fiber reinforced composite with large dispersion pore size
  • Method for establishing two-dimensional stochastic pore model of fiber reinforced composite with large dispersion pore size
  • Method for establishing two-dimensional stochastic pore model of fiber reinforced composite with large dispersion pore size

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Experimental program
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specific Embodiment approach

[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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Abstract

A method for establishing a two-dimensional stochastic pore model of fiber reinforced composite with large dispersion pore sizes belongs to the field of composite nondestructive examination and evaluation. The method for establishing the model includes steps as follows: firstly dissecting a to-be-tested composite sample, counting the porosity and size characteristics of all pores through the metallographic method, grading the pores according to pore lengths, and establishing stochastic pore models of each grade; comparing the models with counting results, obtained through the metallographic analysis, of pore size characteristics of each grade, and obtaining the stochastic pore models of each grade as long as the difference between the models and the results are less than 2%; and finally, superimposing model images of the pores of each grade to obtain a stochastic pore model of the to-be-tested sample. The method can accurately establish the two-dimensional stochastic pore model of the fiber reinforced composite with the large dispersion pore sizes; and further, by utilizing the model, the base for the ultrasonically nondestructive examination of the composite porosity can be provided, and the model base for analyzing the performances of the composite can be provided.

Description

technical field [0001] The invention relates to a method for establishing a two-dimensional random pore model of a fiber-reinforced composite material with large pore size dispersion, which belongs to the technical field of non-destructive testing and evaluation of composite materials. Background technique [0002] So far, the 2D geometric models used to describe porous fiber-reinforced composites can be divided into two categories. The first class of models is based on similar assumptions: that all pores are of regular shape, such as spherical or disc-shaped, that the pores are of equal size and uniformly distributed in the medium, and so on. However, the pore size in actual fiber reinforced composites varies widely, the shape is different, and the distribution is not uniform. This kind of geometric model cannot fully and accurately reflect the pore morphology and its random characteristics, resulting in a large deviation between the porosity ultrasonic testing experiment ...

Claims

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Application Information

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IPC IPC(8): G06T11/00G01N15/08
Inventor 林莉梁向雨罗忠兵陈军李喜孟
Owner DALIAN UNIV OF TECH
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