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Abstract : Asphalt mixture is the most widely used pavement engineering material. Because the laboratory tests of asphalt mixture are costly, researchers keep searching for a practical numerical simulation approach to facilitate their study on mixture design, compaction process, and service performance. Although the discrete element method (DEM) had been introduced into those research areas for more than three decades and has been proved to be an effective tool, its utilizing is still limited by lacking coarse aggregate morphologies, efficient modeling approaches, and complete mechanical theories. This study aims to extend the application of DEM in asphalt mixture research by 1) establishing a coarse aggregate morphology database. Coarse aggregates were categorized according to shape information and then scanned through a three-dimensional scanner. The essential morphology factors, including grain size, dimensions, surface area, volume, and specific surface area, were collected and analyzed; 2) building the gyratory compaction process. Loose material assembly was precisely generated through the developed algorithm according to the mixture design. The loose material was then compacted through the programed gyration moment. The impacts of contact parameters on compaction were investigated. Speed-up techniques were proposed and verified by analyzing the internal structure of the compacted mixtures; 3) developing a set of modeling procedures with high efficiency, low cost, reliable accuracy, and wide application. The new modeling procedures use coarse aggregate temples from the database to improve simulation accuracy and use geometry information from the gyratory compacted mixtures or random generation method to save laboratory specimens. Hexagonal close-packed (HCP) structure, which has advantages in simulating shear failure and Poisson's ratio, was employed instead of the simple cubic-centered (SCC) structure. The corresponding mechanical calculation for contact micro-parameters was then derived and verify through simple stiffness/bond tests and complete indirect tensile (IDT) tests; 4) applying DEM models to research practice. Based on those improvements, this study involved DEM in the research of the mechanical performance of asphalt mixtures with high contents of ground tire rubber (GTR). Incorporate with laboratory tests, although asphalt mixtures with high contents of GTR have lower IDT strength of was than a conventional mixture, its cracking resistance and fatigue resistance were proved to be higher. By analyzing the contact force distribution in the DEM models, rubber particles with low moduli were found to be the endogenous reason for better performance. By further investigation, the rubber particles functioned as buffers that disperse the loadings. With the above four parts of research, the application of the DEM in asphalt mixture has significant improvement in modeling techniques, mechanical theories, simulation efficiency, and scope of application.
For several decades, rutting in asphalt pavements has not been fully addressed or prevented. Study on the microstructure of asphalt concrete may provide a good alternative way to approach a solution. Conventional microstructure modeling based on computed tomography (CT), however, is expensive, time consuming, and specimen destructive. In this paper we present a study on discrete element modeling of asphalt concrete in which the microstructure is described based on the compositional phases. This approach is less expensive, more rapid, nondestructive, and easier to use relative to the CT approach. First, a new algorithm for generating coarse aggregate elements with irregular shapes is developed. It considers the shape and orientation distribution of particles in the microstructure of asphalt concrete. The irregular shapes are created based on the mechanism of sieving analysis. The random distribution of orientations is modeled with a rotation algorithm. Some particular problems such as the issue of "floaters" are solved with an iteration method in the proposed algorithm. Second, the air void phase, which is treated as the second microstructure component of asphalt concrete, is established with a regression model based on data measured from specimens fabricated with a Superpave gyratory compactor. Finally, the developed microstructural model of asphalt concrete is validated with volume fractions of phases in actual asphalt mixture specimens. The results are quite satisfactory.
The six-volume set LNCS 10404-10409 constitutes the refereed proceedings of the 17th International Conference on Computational Science and Its Applications, ICCSA 2017, held in Trieste, Italy, in July 2017. The 313 full papers and 12 short papers included in the 6-volume proceedings set were carefully reviewed and selected from 1052 submissions. Apart from the general tracks, ICCSA 2017 included 43 international workshops in various areas of computational sciences, ranging from computational science technologies to specific areas of computational sciences, such as computer graphics and virtual reality. Furthermore, this year ICCSA 2017 hosted the XIV International Workshop On Quantum Reactive Scattering. The program also featured 3 keynote speeches and 4 tutorials.
Asphalt mixture compaction is an important procedure of asphalt mixture construction and can significantly affect the performance of asphalt pavement. Many laboratory compaction methods (or devices), have been developed to study the asphalt mixture compaction. Nevertheless, the whole process from the selection of aggregate to laboratory compaction is still time-consuming and requires significant human and material resources. In order to better understand asphalt mixture compaction, some researchers began to use finite element method (FEM) to study and analyze mixture compaction. However, FEM is a continuum approach and lacks the ability to take into account the slippage and interlocking of aggregates during compaction. Discrete Element Method (DEM) is a discontinuum analysis method, which can simulate the deformation process of joint systems or discrete particle assembly under quasi-static and dynamic condition. Therefore, it can overcome the shortcomings of FEM and is a more effective tool than FEM to simulate asphalt mixture compaction. In this study, an open source 3D DEM code implemented with the C++ programming language was modified and applied to simulate the compaction of hot-mix asphalt (HMA). A viscoelastic contact model was developed in the DEM code and was verified through comparison with well established analytical solutions. The input parameters of the newly developed contact model were obtained through nonlinear regression analysis of dynamic modulus test results. Two commonly used compaction methods (Superpave gyratory compaction and asphalt vibratory compaction) and one linear kneading compaction based on APA machine were simulated using the DEM code, and the DEM compaction models were verified through the comparison between the DEM predicted results and the laboratory measured test results. The air voids distribution within the asphalt specimens was also analyzed by post processing virtual DEM compaction digital specimens and the level of heterogeneity of the air void distribution within the specimens in the vertical and lateral directions was studied. The DEM simulation results in this study were in a relatively good agreement with the experimental data and previous research results, which demonstrates that the DEM is a feasible method to simulate asphalt mixture compaction under different loading conditions and, with further research, it could be a potentially helpful tool for asphalt mix design by reducing the number of physical compactions in the laboratory.
This book (including a 969 pages full paper USB device) deals with the geotechnics of roads, railways and airfields. Providing economic and sustainable transportation infrastructures for societies is highly dependent on progress made in this field, and the contributions are of interest to professionals and academics involved in geotechnical and pavement engineering of roads, railways and airfields.
The discrete element method is now increasingly used in the micro-mechanical analysis of asphalt mixtures. The digital image-based method is usually used to prepare the 2D discrete element sample. However, this method is costly and time-consuming. In this study, a series of algorithms were developed to generate the 2D discrete element sample of asphalt mixtures based on the probability analysis. Firstly, the shapes and sizes of the 2D aggregates cut from 3D aggregates were analyzed and their probabilities were computed. Based on this, an algorithm was proposed to generate the 2D aggregates. Secondly, a method was developed to calculate the number of 2D aggregates in the 2D asphalt mixture sample. Lastly, the algorithms for generating the 2D discrete element sample were summarized and discussed. With these algorithms, the 2D discrete element sample of asphalt mixtures can be generated directly and rapidly.