CPT soil profile interpretation represents a fundamental aspect for subsoil stratigraphic recon struction of complex geological contexts. In some situations, the soil profile may not exhibit evident boundary changes, making the interpretation more difficult. This crucial aspect plays a key role in the layers boundaries discontinuities identification and the construction of bi-dimensional and three-dimensional geotechnical models. In this paper, CPT and boreholes are used to calibrate and validate a massive and automated site characterization by combining statistical tools and artificial intelligence algorithms (AI). The procedure is applied in the complex stratigraphic context of Terre del Reno (Italy). The proposed data-driven analysis allows to combine the geological and geotechnical knowledge of the subsoil in an efficient and automatic way based on site-specific data, obtaining reliable and indispensable results for the construction of a robust and coherent geotechnical model of the subsoil.

Data-driven soil profile characterization using statistical methods and artificial intelligence algorithms

Spacagna, R. L.
Writing – Review & Editing
;
Baris, A.
Methodology
;
Paolella, L.
Validation
;
Modoni, G.
Conceptualization
2022

Abstract

CPT soil profile interpretation represents a fundamental aspect for subsoil stratigraphic recon struction of complex geological contexts. In some situations, the soil profile may not exhibit evident boundary changes, making the interpretation more difficult. This crucial aspect plays a key role in the layers boundaries discontinuities identification and the construction of bi-dimensional and three-dimensional geotechnical models. In this paper, CPT and boreholes are used to calibrate and validate a massive and automated site characterization by combining statistical tools and artificial intelligence algorithms (AI). The procedure is applied in the complex stratigraphic context of Terre del Reno (Italy). The proposed data-driven analysis allows to combine the geological and geotechnical knowledge of the subsoil in an efficient and automatic way based on site-specific data, obtaining reliable and indispensable results for the construction of a robust and coherent geotechnical model of the subsoil.
File in questo prodotto:
File Dimensione Formato  
9781003308829_webpdf.pdf

accesso aperto

Licenza: Dominio pubblico
Dimensione 673.45 kB
Formato Adobe PDF
673.45 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/91741
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
social impact