Investigation of variations in performance properties of asphalt concrete using image-based finite element model

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2022-7-20
Karakaya, Yalçın
The objective of this study is to evaluate variations in performance properties of asphalt concrete using a two-dimensional image-based finite element model. Two different asphalt mixtures are used in both laboratory tests and in FEM analyses representing different conditions. A flatbed scanner is then used to capture cross-sectional images of the samples and various image processing techniques are applied to prepare the images for FEM. A unique image vectorization method has been developed to transform cross-sectional images into the finite element mesh to minimize computational time in FEM, where AC is modeled as a composite material consisting of individual components of aggregate and asphalt binder. In the experimental program, three different testing programs; resilient modulus, repeated creep and indirect tensile fatigue tests are conducted to obtain different performance indicators. The laboratory experiments are performed using ten replicates, to establish the variability in performance properties. Sample variability is also studied in the FEM for identical specimens by changing their microstructures using a previously developed redistribution algorithm. Finally, the performance indicators obtained from the laboratory tests and the FEM analyses are compared to evaluate the variability in the performance tests. Various results show that the two-dimensional finite element model created in this study works successfully for two completely different mix designs under different test conditions. Furthermore, with the particle redistribution method, the inherent variability of the asphalt concrete on the test results is identified and it was found to correspond to values as low as about one eighth.

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Citation Formats
Y. Karakaya, “Investigation of variations in performance properties of asphalt concrete using image-based finite element model,” Ph.D. - Doctoral Program, Middle East Technical University, 2022.