Version 1
: Received: 8 October 2023 / Approved: 9 October 2023 / Online: 9 October 2023 (11:42:43 CEST)
How to cite:
Ng'eno, F.K.; Omuto, C.T.; Biamah, E.K. Application of Machine Learning and 3D Modelling to Improve Geotechnical Site Characterization. Preprints2023, 2023100495. https://doi.org/10.20944/preprints202310.0495.v1
Ng'eno, F.K.; Omuto, C.T.; Biamah, E.K. Application of Machine Learning and 3D Modelling to Improve Geotechnical Site Characterization. Preprints 2023, 2023100495. https://doi.org/10.20944/preprints202310.0495.v1
Ng'eno, F.K.; Omuto, C.T.; Biamah, E.K. Application of Machine Learning and 3D Modelling to Improve Geotechnical Site Characterization. Preprints2023, 2023100495. https://doi.org/10.20944/preprints202310.0495.v1
APA Style
Ng'eno, F.K., Omuto, C.T., & Biamah, E.K. (2023). Application of Machine Learning and 3D Modelling to Improve Geotechnical Site Characterization. Preprints. https://doi.org/10.20944/preprints202310.0495.v1
Chicago/Turabian Style
Ng'eno, F.K., Christian Thine Omuto and Elijah Kipngetich Biamah. 2023 "Application of Machine Learning and 3D Modelling to Improve Geotechnical Site Characterization" Preprints. https://doi.org/10.20944/preprints202310.0495.v1
Abstract
Geotechnical investigation is an important site characterization process in engineering construction. Excavation pits and boreholes are popular geotechnical investigation methods for accessing subsurface soil and rock characteristics. Although they are accurate, they are limited to the discrete locations where tests are carried out. The demand for 3D representation has been increasing as an alternative for improved visualization of geotechnical investigations. This study developed a procedure for 3D modelling of geotechnical investigations using open-source software. It improves 3D visualization of geotechnical investigations and characterization of accuracy and uncertainty assessment. Presently, most geotechnical investigations do not regularly report uncertainty assessment despite its importance in risk analysis of the investigations. The procedure developed in this study was tested in a proposed site for construction of an Inland Container Depot where it depicted geotechnical soil properties with more than 80% accuracy on holdout samples. It was able to model both horizontal and vertical variations of the soil properties with quantification of uncertainty. More testing and wide applications are recommended.
Keywords
3D modelling, geotechnical properties, spatial modelling,
Subject
Engineering, Bioengineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
