Reconstruction of granular railway ballast based on inverse discrete Fourier transform method

TLDR: It can be found that a large number of virtual particles with similar geometrical features can be reconstructed using the proposed Fourier descriptors in a rapid and convenient manner, which is beneficial for providing a virtual test sample for the numerical modeling of realistic granular materials.

Abstract: This paper presents a particle shape characterization and reconstruction method to describe the geometrical information of granular railway ballast. The outline of a real granular particle is segmented and transformed as discrete time domain signals based on Fourier transform method. Then, the discrete Fourier transform algorithm is developed and applied to convert discrete time domain signals into a discrete Fourier spectrum. Meanwhile, the normalized amplitudes are defined as Fourier descriptors, which is found to be applicable to characterize and reconstruct particle contour. Further, the proposed method is validated by comparing the contours of the real particle with that of reconstructed particle. Moreover, the shape indexes of particles Fourier descriptors and reconstruction of ballasted gravel are illustrated and the the results show that the geometrical parameters can be classified as three levels which can represent the geometrical characteristics in terms of macroscopical and microscopic structure. The inverse discrete Fourier transform can quantitatively control the shape of reconstructed particles by controlling the value and distribution of Fourier descriptors, which matchs the three levels of shape indexes. Furthermore, it can be found that a large number of virtual particles with similar geometrical features can be reconstructed using the proposed Fourier descriptors in a rapid and convenient manner, which is beneficial for providing a virtual test sample for the numerical modeling of realistic granular materials.