Data for a publication - A Numerical Study of Vehicle Security Barrier Effectiveness and Parameter Sensitivity Using the Generic Vehicle Model

This study introduces a novel numerical methodology for assessing the effectiveness of vehicle security barriers (VSBs) using a generic finite element vehicle model. Unlike previous studies that focus on specific vehicle types, this approach enables simulation across a wide range of configurations within the same vehicle groups—including variations in mass, dimensions, and cargo placement—allowing identification of critical impact scenarios that might otherwise remain undetected. A total of 129 vehicle configurations were simulated in one of the analyses, of which 74% were successfully stopped by the barrier, while 26% resulted in full barrier breach, highlighting the substantial influence of vehicle variability on barrier performance. The methodology incorporates a stochastic design of experiments and automated configuration generation to efficiently explore a broad parameter space. Sensitivity analysis was employed to identify the parameters strongly influencing barrier effectiveness, supporting both model simplification and design optimization. Using the Coefficient of Prognosis, vehicle velocity (CoP = 0.56), ground clearance (0.09), and cargo mass (0.07) as the dominant factors, with a prediction precision of 0.7; these findings were subsequently confirmed in additional analyses. Other parameters, including wheel diameter and cargo position, had a much lower impact. By identifying these key parameters, designers can prioritize critical factors, optimize barrier performance, and simplify simulations, ultimately enhancing safety and reliability under diverse impact scenarios. This framework demonstrates that combining a generic vehicle model with systematic sensitivity analysis provides a comprehensive, efficient, and practical tool for evaluating and improving VSB performance in public spaces, offering insights beyond conventional single vehicle testing.