Meso-structure image pre-selection method for two-dimensional finite element modeling in beam bending simulation of asphalt mixture

Abstract

Finite element (FE) simulation has been widely used in conjunction with the beam bending test (BBT) to analyze the cracking behavior of asphalt mixtures. Crack propagation is significantly affected by the internal structure of an asphalt mixture. Limitations on computational resources and the complex mesostructure of asphalt mixtures have resulted in two-dimensional (2D) FE simulations being more widely used than three-dimensional simulations. However, a single 2D FE model can only reflect the mesostructural characteristics of one specimen section, precluding comparison between the simulation and laboratory test results. In this paper, X-ray CT scanning technology was used to obtain a large number of internal mesostructure images of an asphalt mixture, and image-based modeling was used to construct 2D FE models for simulating beam bending tests. An analysis of the simulated crack morphologies and positions of the models was used to propose a prediction method for the crack position based on image processing technology, and a hypothesis that the crack positions were correlated with the simulation results was put forward. This hypothesis was verified by comparing the simulation and laboratory test results. Finally, the predicted crack position (CPRP) was used to propose an image preselection method from which 2D FE models were constructed to simulate of BBT for an asphalt mixture. This method considerably reduces the number of 2D FE models required and significantly improves the calculation efficiency while ensuring the accuracy of the BBT 2D simulations.