Predicting stress concentration in trapdoor problems for buried transportation infrastructure using dimensionless DEM-based model

Buried transportation assets (e.g., culverts, utility corridors, shallow tunnels) beneath highways and urban streets can experience differential ground movement, leading to pavement settlement, serviceability loss, and, in extreme cases, sudden collapse and traffic disruption. The trapdoor mechanism provides a controlled analogue for this load-redistribution problem. Soil arching develops due to a static, yielding zone that redistributes load towards stiffer adjacent zones, affecting overburden pressure and the deformation response relevant to roadway performance. This paper consolidates a comprehensive dataset of trapdoor simulations performed with the discrete element method, analyzing the problem using three dimensionless ratios: η = H/B, γ = B’/B, and λ = L/B. A concise predictive formula for the peak stress concentration factor α_peak is proposed, showing it increases with soil cover (H) and yielding width (B’), converges as the cover and H/B ratio grow, and incorporates a boundary multiplier to account for periodic versus wall boundaries. Using existing α values across various geometries and heights, model parameters are estimated via non-linear least squares and then validated using cross-validation, parity plots, and residual diagnostics. Results are presented in design charts that map α_peak within the dimensionless parameter space, indicating the necessary cover to reach 90–95% of the asymptotic response. The study links particle-scale mechanisms with practical, portable guidance for screening the design and maintenance of buried assets supporting transportation corridors.