Abstract

FERNANDEZ, Wilmar D et al. ASPHALT MIXTURE DIGITAL RECONSTRUCTION BASED ON CT IMAGES. Cienc. Ing. Neogranad. [online]. 2015, vol.25, n.1, pp.17-25. ISSN 0124-8170.

More than 80% of pavements in Colombia and worldwide are made of asphalt mixtures. Those mixtures have usually been studied as a single material, but they are actually a three phase material, since they are composed of rocks, mastics and air voids. In addition, the behavior of the asphalt mixtures depends on the characteristics of each phase. The aim of this project is to make an asphalt mixture real sample reconstruction from X-Ray Computerized Axial Tomography (CAT). The reconstruction process has three stages: Scanning, Segmentation, and Data Scaling. All these stages were developed in Python under Object Oriented Programming (OOP) and were implemented through the use of several tools, such as Numpy, Scipy, Pydicom, Scikit-learn, Matplotlib and Mayavi. As a result, a tridimensional digital model called ToyModel was developed. This model is a 3D digital solid represented by a set of 1 mm³ voxels. The reconstructed ToyModel accurately represented the real sample, since the ToyModel air void volume was 3.98% and the real sample air void content volume was 4%. This Python implementation is a good tool to model any asphalt mixtures, not only to extract sample composition, but also to simulate different processes, e.g., Finite Element Method (FEM) analysis.

Keywords : Asphalt mixtures; X-Ray CT images; ToyModel; scanning; segmentation; scaling.

        · abstract in Spanish     · text in English     · English ( pdf )