Automated Load–Settlement Prediction of Shallow Foundations from Pushed-in PENCEL Pressuremeter Data Based on Briaud (2007) Method: A Python-Based Framework

This study presents a fully automated, Python-based framework for predicting shallow foundation settlements from pushed-in PENCEL pressuremeter (PPMT) data, using an adapted implementation of Briaud’s (2007) method. The framework transforms raw in-situ test results into design-grade load–settlement curves by automating key analytical steps, including borehole wall-point detection, Lemée-type extrapolation for incomplete curves, strain-specific pressure extraction, and Schmertmann-based strain influence zoning. Unlike traditional approaches, which often rely on manual interpretation or pre-bored pressuremeter data, this method extends Briaud’s framework to pushed-in PPMT devices, which offer logistical advantages in sandy soils. Correction factors for footing shape, load eccentricity, inclination, and slope proximity are included to reflect real-world boundary conditions. The framework’s predictions were validated against advanced PLAXIS 3D simulations and full-scale field measurements across three Florida sites, demonstrating close agreement and confirming its reliability in cohesionless soils. By automating a traditionally complex procedure and supporting open-source reproducibility, this tool enables faster, more consistent deformation-based foundation design. The framework, implemented in Python, has been validated using field data and simulations and is publicly available for geotechnical practice and research.