Probabilistic Soil Strata Delineation Using DPT Data and Bayesian Changepoint Detection

Soil strata delineation is a fundamental step for any geotechnical engineering design. The dynamic penetration test (DPT) is a fast, low cost in situ test that is commonly used to locate boundaries between strata of differing density and driving resistance. However, DPT data are often noisy and typically require time-consuming, manual interpretation. This paper investigates a probabilistic method that enables delineation of dissimilar soil strata (where each stratum is deemed to belong to different soil groups based on their particle size distribution) by processing DPT data with Bayesian changepoint detection methods. The accuracy of the proposed method is evaluated using DPT data from a real-world case study, which highlights the potential of the proposed method. This study provides a methodology for faster DPT-based soil strata delineation, which paves the way for more cost-effective geotechnical designs.

Automated summary

Soil strata delineation is a crucial step in geotechnical engineering design, and the dynamic penetration test (DPT) is commonly used for this purpose. However, DPT data is often noisy and requires manual interpretation. This paper proposes a probabilistic method that uses Bayesian changepoint detection to delineate different soil strata based on their particle size distribution. The proposed method is evaluated using real-world DPT data, demonstrating its potential for faster and more cost-effective geotechnical designs.