Probabilistic Soil Strata Delineation Using DPT Data and Bayesian Changepoint Detection
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 149, Issue 4
Abstract
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.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to acknowledge Deutsche Bahn AG and Dr. Aloys Kisse for the use of the test data for research purposes. Oriol Ciurana (OSI) is gratefully acknowledged in the development of the 3D ground model referred to herein. The third author is funded by the Royal Academy of Engineering under the Research Fellowship scheme.
References
Adams, R. P., and D. J. MacKay. 2007. “Bayesian online changepoint detection.” Preprint, submitted 13 August 2019. https://arxiv.org/abs/0710.3742.
Aminikhanghahi, S., and D. J. Cook. 2017. “A survey of methods for time series change point detection.” Knowl. Inf. Syst. 51 (2): 339–367. https://doi.org/10.1007/s10115-016-0987-z.
Barry, D., and J. A. Hartigan. 1993. “A Bayesian analysis for change point problems.” J. Am. Stat. Assoc. 88 (421): 309–319.
BSI (British Standard Institution). 2005. Geotechnical investigation and testing–field testing–Part 2; Dynamic probing. BS EN ISO 22476-2. London: BSI.
Cao, Z. J., S. Zheng, D. Q. Li, and K. K. Phoon. 2019. “Bayesian identification of soil stratigraphy based on soil behaviour type index.” Can. Geotech. J. 56 (4): 570–586. https://doi.org/10.1139/cgj-2017-0714.
Ching, J., J.-S. Wang, C. H. Juang, and C.-S. Ku. 2015. “Cone penetration test (CPT)-based stratigraphic profiling using the wavelet transform modulus maxima method.” Can. Geotech. J. 52 (12): 1993–2007. https://doi.org/10.1139/cgj-2015-0027.
Depina, I., T. M. H. Le, G. Eiksund, and P. Strøm. 2016. “Cone penetration data classification with Bayesian mixture analysis.” Georisk 10 (1): 27–41.
Fearnhead, P. 2005. “Exact Bayesian curve fitting and signal segmentation.” IEEE Trans. Signal Process. 53 (6): 2160–2166. https://doi.org/10.1109/TSP.2005.847844.
Fearnhead, P. 2006. “Exact and efficient Bayesian inference for multiple changepoint problems.” Stat. Comput. 16 (2): 203–213. https://doi.org/10.1007/s11222-006-8450-8.
Fearnhead, P., and Z. Liu. 2007. “On-line inference for multiple changepoint problems.” J. R. Stat. Soc.: Ser. B (Stat. Methodol.) 69 (4): 589–605. https://doi.org/10.1111/j.1467-9868.2007.00601.x.
Freeman, M. F., and J. W. Tukey. 1950. “Transformations related to the angular and the square root.” In The annals of mathematical statistics, 607–611. Ann Arbor, MI: Institute of Mathematical Statistics.
Hegazy, Y. A., and P. W. Mayne. 2002. “Objective site characterization using clustering of piezocone data.” J. Geotech. Geoenviron. Eng. 128 (12): 986–996. https://doi.org/10.1061/(ASCE)1090-0241(2002)128:12(986).
Houlsby, N. M. T., and G. T. Houlsby. 2013. “Statistical fitting of undrained strength data.” Géotechnique 63 (14): 1253–1263. https://doi.org/10.1680/geot.13.P.007.
Jefferies, M. G., and M. P. Davies. 1993. “Use of CPTU to estimate equivalent SPT N60.” Geotech. Test. J. 16 (4): 458–468. https://doi.org/10.1520/GTJ10286J.
Li, J., M. J. Cassidy, J. Huang, L. Zhang, and R. Kelly. 2016. “Probabilistic identification of soil stratification.” Géotechnique 66 (1): 16–26. https://doi.org/10.1680/jgeot.14.P.242.
Lin, L., and C. Xu. 2020. “Arcsine-based transformations for meta-analysis of proportions: Pros, cons, and alternatives.” Health Sci. Rep. 3 (3): e178. https://doi.org/10.1002/hsr2.178.
Lunne, T., P. K. Robertson, and J. J. M. Powell. 1997. Cone penetration testing in geotechnical practice. London: Blackie Academic and Professional.
Mosteller, F., and C. Youtz. 2006. “Tables of the Freeman-Tukey transformations for the binomial and Poisson distributions.” In Selected papers of Frederick Mosteller, 337–347. New York: Springer.
Parry, S., F. J. Baynes, M. G. Culshaw, M. Eggers, J. F. Keaton, K. Lentfer, J. Novotny, and D. Paul. 2014. “Engineering geological models—An introduction: IAEG commission 25.” Bull. Eng. Geol. Environ. 73 (Feb): 689–706.
Phoon, K.-K., S.-T. Quek, and P. An. 2003. “Identification of statistically homogeneous soil layers using modified Bartlett statistics.” J. Geotech. Geoenviron. Eng. 129 (7): 649–659. https://doi.org/10.1061/(ASCE)1090-0241(2003)129:7(649).
Prinz, I. 2019. “Digitale baugrundmodelle: BIM in der geotechnik erfahrungen und ableitungen aus dem projekt ausbaustrecke Emmerich-Oberhausen (ABS 46/2), einem BIM-piloten der Deutschen Bahn.” Geotechnik 22: 22–27.
Punskaya, E., C. Andrieu, A. Doucet, and W. J. Fitzgerald. 2002. “Bayesian curve fitting using MCMC with applications to signal segmentation.” IEEE Trans. Signal Process. 50 (3): 747–758. https://doi.org/10.1109/78.984776.
Reeves, J., J. Chen, X. L. Wang, R. Lund, and Q. Q. Lu. 2007. “A review and comparison of changepoint detection techniques for climate data.” J. Appl. Meteorol. Climatol. 46 (6): 900–915. https://doi.org/10.1175/JAM2493.1.
Robertson, P. K. 1990. “Soil classification using the cone penetration test.” Can. Geotech. J. 27 (1): 151–158. https://doi.org/10.1139/t90-014.
Schneider, J. A., M. F. Randolph, P. W. Mayne, and N. R. Ramsey. 2008. “Analysis of factors influencing soil classification using normalized piezocone tip resistance and pore pressure parameters.” J. Geotech. Geoenviron. Eng. 134 (11): 1569–1586. https://doi.org/10.1061/(ASCE)1090-0241(2008)134:11(1569).
Shapiro, S. S., and M. B. Wilk. 1965. “An analysis of variance test for normality (complete samples).” Biometrika 52 (3–4): 591–611. https://doi.org/10.1093/biomet/52.3-4.591.
Stephens, D. A. 1994. “Bayesian retrospective multiple-changepoint identification.” J. R. Stat. Soc.: Ser. C (Appl. Stat.) 43 (1): 159–178.
Truong, C., L. Oudre, and N. Vayatis. 2020. “Selective review of offline change point detection methods.” Signal Process. 167 (Jun): 107299. https://doi.org/10.1016/j.sigpro.2019.107299.
Wang, H., X. Wang, J. F. Wellmann, and R. Y. Liang. 2019. “A Bayesian unsupervised learning approach for identifying soil stratification using cone penetration data.” Can. Geotech. J. 56 (8): 1184–1205. https://doi.org/10.1139/cgj-2017-0709.
Wang, Y., Y. Hu, and T. Zhao. 2020. “Cone penetration test (CPT)-based subsurface soil classification and zonation in two-dimensional vertical cross section using Bayesian compressive sampling.” Can. Geotech. J. 57 (7): 947–958. https://doi.org/10.1139/cgj-2019-0131.
Wang, Y., K. Huang, and Z. Cao. 2013. “Probabilistic identification of underground soil stratification using cone penetration tests.” Can. Geotech. J. 50 (7): 766–776. https://doi.org/10.1139/cgj-2013-0004.
Wickremesinghe, D., and R. Campanella. 1991. “Statistical methods for soil layer boundary location using the cone penetration test.” In Vol. 2 of Proc. ICASP6, 636–643. Mexico City, Mexico: International Civil Engineering Risk and Reliability Association.
Zhang, Z., and M. T. Tumay. 1999. “Statistical to fuzzy approach toward CPT soil classification.” J. Geotech. Geoenviron. Eng. 125 (3): 179–186. https://doi.org/10.1061/(ASCE)1090-0241(1999)125:3(179).
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© 2023 American Society of Civil Engineers.
History
Received: Mar 1, 2022
Accepted: Dec 15, 2022
Published online: Feb 8, 2023
Published in print: Apr 1, 2023
Discussion open until: Jul 8, 2023
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