Dynamic Compaction for Ground Improvement: Mechanisms, Governing Parameters, Environmental Impacts, and Multiscale Research Approaches

Dynamic compaction (DC) is a widely used ground-improvement technique due to its cost-effectiveness, low environmental impact, and high adaptability. Despite its simple implementation, compaction efficiency is governed by multiple interacting factors, including tamping energy and soil properties, which poses challenges to practical design. Although numerous investigations have been reported, a comprehensive review systematically linking the various aspects of the DC technique through multiple approaches remains lacking. This paper addresses this gap by integrating and critically evaluating findings from field studies, controlled laboratory experiments, analytical studies, and numerical modeling to establish an effective framework for dynamic compaction applications. In addition, the environmental performance of DC is critically assessed, demonstrating its relatively low environmental footprint compared to material-intensive ground-improvement techniques, as impacts are primarily governed by construction energy rather than material production, although vibration and noise remain key considerations. The findings indicate that DC performance is controlled by the combined effects of the tamper mass, drop height, and geometry, together with impact spacing, number of blows, and initial soil properties. Field studies show that densification depth and uniformity are influenced by the fines percentage, drainage conditions, and applied energy levels, often requiring appropriate tamping strategies to mitigate pore water effects. Laboratory investigations highlight the dominant role of tamper mass over drop height in stress transmission and penetration depth and demonstrate how the tamper shape and impact sequence govern crater formation and strain localization. Numerical models employing finite element, discrete element, smoothed particle hydrodynamics, and hybrid approaches provide insight into stress wave propagation, pore pressure evolution, and soil–structure interaction. However, limitations remain in simulating sequential tamping, boundary conditions, and coupled hydro-mechanical behavior. This review highlights the need for cross-validated modeling, advanced instrumentation, and machine learning integration to support predictive, site-responsive dynamic compaction design in complex geotechnical settings.