Bearing Capacity in Reinforced Soil: A Systematic Review of Modern Assesment Methods

Abstract

This systematic literature review  aims to thoroughly analyze the probabilistic methods used to assess the bearing capacity of reinforced soil , with a focus on identifying research trends, gaps, and evaluating various techniques such as Monte Carlo simulation, reliability-based design, and the stochastic finite element method (SFEM). The review follows established SLR protocols, employing purposive sampling from scientific databases such as Scopus to select peer-reviewed articles and conference papers. The dataset includes 113 full-text articles, 9 books, and 420 non-full-text entries, totaling 542 sources. Data collection was guided by predetermined inclusion and exclusion criteria, and a coding framework was utilized to categorize and compare key variables, including probabilistic methods and research outcomes. Qualitative synthesis was used for theme extraction, while quantitative assessment evaluated the effectiveness of the methods. The main contribution of this study lies in highlighting the strengths, limitations, and practical applicability of various probabilistic approaches, while advocating for the further integration of probabilistic and deterministic methods to enhance the reliability of soil reinforcement design. This review provides valuable insights for geotechnical engineers and researchers, advancing the understanding of probabilistic methods in improving the performance of reinforced soil.