An individualised Finite Element framework for predicting footwear outsole wear: validation against a 250 km trekking field test

Premature wear of footwear outsoles degrades grip performance, significantly increasing slip and injury risks for the user during prolonged usage. Traditionally, evaluating outsole durability relies on resource-intensive field testing, which limits design optimisation to maintain safety and minimise material loss. This study develops and validates an individualised Finite Element Analysis (FEA) wear model to predict functional wear distribution across the outsole under trekking conditions. Mechanical simulations of the gait cycle were driven from the foot kinematic and kinetic walking laboratory data of seven participants. The resulting nodal contact pressures and sliding distances were then integrated into the Archard wear law to update the outsole geometry, representing the simulated cumulative wear. To validate these predictions, the same participants completed a 250 km trekking field test wearing shoes with two different outsole materials in a within-subject paired design. Experimental wear was quantified by comparing high-resolution 3D scans of the shoes before and after use. The model’s accuracy and its ability to differentiate material wear were assessed by comparing the simulated wear against the experimental wear throughout the whole outsole area. Results demonstrated a strong correlation at the functional zone scale (r = 0.72, p < 0.001). At a highly localised lug-by-lug scale, the correlation was lower (r = 0.29, p < 0.001), due to unpredictable interactions with the terrain and the level-ground biomechanical input limitations. Importantly, the simulation successfully differentiated the relative durability of the different outsole compounds. In conclusion, this field-validated computational framework offers a robust predictive tool to optimise outsole geometry for improved durability and user safety early in design, while supporting product eco-design.