Consideration of spatial variability and environmental impacts in the probabilistic design of driven piles

This study presents a probabilistic framework for the axial design of driven pipe piles that incorporates subsurface spatial variability and quantifies the influence of soil heterogeneity on reliability and environmental performance. Traditional geotechnical designs often rely on conservative deterministic parameters that simplify natural variability, resulting in overdesign and increased environmental impact. The applied methodology combines Monte Carlo simulations, random field theory, and the Unified cone penetration testing-based design method to model pile capacity under varying degrees of spatial correlation in relative density ( D R ) profiles. Initial pile geometries were determined using conventional factor of safety (FS) criteria for a homogeneous soil profile. These were then evaluated under uncorrelated, correlated, and uniform subsurface vertical spatial variability scenarios by simulating D R as a lognormally distributed random field with varying mean, coefficient of variation, and correlation length ( θ). The resulting probability of failure ( p f ) for each design was computed and compared to the deterministic FS. The analysis revealed that p f varies by several orders of magnitude for the same FS depending on the assumed spatial structure. A streamlined life cycle assessment indicates that incorporating spatial correlation enables material reductions while maintaining acceptable p f levels, achieving up to 14% global warming potential savings compared to uniform soil profile assumptions.