| dc.description.abstract | Roads, pavements, and highways are common civil engineering structures seen in daily life. It is often observed that road pavements suffer from damage, such as potholes and cracks. However, in engineering, there seems to be no convenient theoretical data that allows engineers to directly predict the failure behavior and deformation of such materials. Although experiments may reveal the behavioral data of these materials, the experimental process is often time-consuming. If a precise material theory can describe the properties of pavement, numerical analysis can be used to save significant time and effort in obtaining relatively reliable data for prediction.
Therefore, this study aims to understand and classify pavement materials theoretically, and describe material characteristics numerically. By updating the material properties in dynamic equations with these new characteristics, we can conduct analysis and simulations, comparing the results with different software packages to verify the reliability of the model.
This research uses the IDAP-ENSP (Implicit Dynamic Analysis Procedure based on Equivalent Nodal Secant Properties) dynamic time-history analysis procedure. This procedure uses the secant stiffness method for iteration, diagonalizing the matrix without the need to calculate the inverse matrix, resulting in relatively higher computational efficiency compared to traditional finite element analysis procedures. For comparison, the study uses ABAQUS 2017 software, a well-established and trusted tool in the engineering field, making it a valuable reference for comparison.
Finally, the analysis results are compared, summarized, and categorized based on various material properties. The theoretical material model and numerical analysis behaviors are cross-referenced and validated. The advantages and disadvantages of generating the material model and the comparison of analysis results are discussed, including differences, consistencies, and possible influencing factors. Conclusions and recommendations for future research updates are also presented. | en_US |