Optimization of intelligent compaction based on finite element simulation and nonlinear multiple regression

In intelligent compaction, a critical issue is determining the combination of construction parameters (e.g., the rolling speed and the number of passes) for achieving optimal compaction results. In this paper, a finite element model was developed based on the Mohr-Coulomb elasto-plastic model to simulate the field compaction process of subgrade, which was validated by field compaction tests. Nonlinear multiple regression was used to match the impacts of construction factors on compaction quality based on the model simulation. Then, the linear search approach was used to find the ideal combination of construction parameters that optimizes the compaction quality. The findings indicated that the ideal combination of construction parameters for reaching the ideal compaction degree is a rolling speed of 1.3 m/s with 4 roller passes.