In this paper, an investigation was conducted to characterize the behavior of weakly cohesive soil subjected to vibratory compaction. Thus, the authors developed a model for weakly cohesive soils, defined by inter-parametric laws that consider their initial state and predict the evolution of state parameters resulting from static and vibratory compaction processes, depending on the number of equipment passes. Four types of soil were proposed for testing, with different initial characteristics such as dry density, longitudinal modulus, and moisture content. Some correlations between main parameters involved in the compaction process were established, considering soil mechanical properties, compaction equipment, and in situ technology applied. The results obtained in the computational environment were implemented to predict the performance compaction process for an overall assessment. This research contributes to database development by offering valuable insights for specialists aiming to apply Industry 4.0 digitalization practices, which stipulate the use of predictability laws in pre-assessing the degree of soil compaction (or settlement) to estimate and maximize the efficiency of road construction or foundation works. These insights help optimize design processes, enhance functional performance, improve resource utilization, and ensure long-term sustainability in large infrastructure projects built on these soils.

The rheological modeling of soil-drum interaction in the vibratory compaction process is a complex process. This paper aims to describe the behavior of soil-drum interaction through lumped parameter modeling. The amplitude of the vertical motion is evaluated for dynamic conditions using the rheological models (generalized and advanced Kelvin-Voigt-based models) and compared with the experimental results obtained from weakly cohesive soil compaction. Different modeling approaches are considered, and the results reveal that the properties of the soil as input play a vital role in the accuracy of the modeling.