# Predictive Models for Correlation of Compaction Characteristics of Weakly Cohesive Soils
## 1 Introduction  
The digitalization of the construction industry, particularly through Industry 4.0 technologies, is transforming large-scale infrastructure projects, including the compaction process for soils. Industry 4.0 refers to the integration of automation, data exchange, and smart technologies to enhance efficiency, productivity, and sustainability in various sectors. In the case of soil compaction, a main phase in infrastructure projects such as roads, the application of Industry 4.0 technologies can significantly enhance outcomes if it involves smart compaction equipment, real-time monitoring and data collection, prediction models for simulation, automation, and robotics, artificial intelligence and machine learning, remote control and cloud-based operations, sustainability and energy efficiency, etc. [1, 2, 3]. In Romania, approximately 70-80% of the technological processes involved in preparing construction materials and managing tasks on construction sites are automated, while around 10-20% are computerized. Field experiments are the usual approach to investigate the dynamic response of weakly cohesive soils during vibratory roller compaction. For example, our literature survey showed [4, 5, 6, 7, 8] that many field experiments have been conducted to study soil improvement characteristics in terms of strength, settlement, void ratio, permeability, etc. Thus, soil type has significant influence on compaction characteristics achievement. Non- or less cohesive soils, such as sand, gravel, or a combination, are characterized by larger particles with small cohesive forces between them. These soils are easier to compact,as the particles can be rearranged and fit more tightly together with less resistance. In addition, the absence of strong linkages between particles allows them to settle into a denser formation under the compaction forces of the roller drum. The moisture content of the soil is another factor with a great influence, as it can increase or decrease compaction efficiency depending on the type of soil and the applied technology. The energy developed during the compaction process represents a crucially important role in determining the final density, strength, or settlement of the compacted material (e.g., soil, aggregates, and asphaltic mixture). This energy depends on both the type of technological equipment used and the operational parameters of the working regime applied during compaction. A series of these factors will be enumerated below: type of technological equipment (static or vibratory rollers, smooth-wheeled rollers, sheepsfoot rollers, pneumatic-tired rollers), parameters of the working regime (frequency and amplitude of vibration, roller speed, number of passes, moisture content), and impact on compaction quality (in terms of density, stability, strength, and durability). Thus, the proper equipment choice and working regime settings lead to achieving efficient, cost-effective, and high-quality compaction. The moisture content of the soil also has a significant impact on the compaction process, and specialists know that there is an optimal moisture content at which a soil can achieve maximum density when compacted. In a case in which the soil is too dry, the particles will not move easily into a denser arrangement, but if the soil is too wet, water fills the spaces between particles, reducing the achievable density. Achieving the optimal relationship between moisture and compaction energy is key to improving soil strength and stability, making these factors fundamental in construction and related activities. Moreover, optimum water content (OWC), wopt, and maximum dry density (MDD), \(\varrho_{\text{dmax}}\), need to be known before starting the compaction process. These two parameters are essential, because they help to determine the maximum dry density, i.e., where soils have a larger bearing capacity due to the maximum soil densification, throughout the optimum water content [9; 10; 11].