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Multiple Regression Analysis of Geoelectric Imaging and Geotechnical Site Investigation Test Results


Affiliations
1 Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
2 Department of Civil Engineering, IIT Roorkee, Roorkee 247 667, India
 

Geotechnical site characterization through non-invasive and cost-effective electrical resistivity imaging (ERI) and induced polarization imaging (IPI) offers promise compared to conventional point-geotechnical site investigations (standard penetration test, SPT), for which a basic understanding of factors (grain size (sand, fines) and water content) influencing them is needed. Here we perform a multiple regression analysis of ERI, IPI and SPT results in a site investigation at Lucknow, India. The results show that grain size and water content influence both chargeability and SPT values in a similar manner, while resistivity values are affected differently with a low RMS prediction error for chargeability.

Keywords

Geoelectronic Imaging, Geotechnical Site Characterization, Multi-Regression Analysis, Grain Size, Water Content.
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  • Multiple Regression Analysis of Geoelectric Imaging and Geotechnical Site Investigation Test Results

Abstract Views: 320  |  PDF Views: 112

Authors

Rambhatla G. Sastry
Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
Sumedha Chahar
Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
Mahendra Singh
Department of Civil Engineering, IIT Roorkee, Roorkee 247 667, India

Abstract


Geotechnical site characterization through non-invasive and cost-effective electrical resistivity imaging (ERI) and induced polarization imaging (IPI) offers promise compared to conventional point-geotechnical site investigations (standard penetration test, SPT), for which a basic understanding of factors (grain size (sand, fines) and water content) influencing them is needed. Here we perform a multiple regression analysis of ERI, IPI and SPT results in a site investigation at Lucknow, India. The results show that grain size and water content influence both chargeability and SPT values in a similar manner, while resistivity values are affected differently with a low RMS prediction error for chargeability.

Keywords


Geoelectronic Imaging, Geotechnical Site Characterization, Multi-Regression Analysis, Grain Size, Water Content.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi09%2F1946-1952