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Correlations Between Dynamic Elastic Properties and P-Wave Velocity for Different Rock Types
https://orcid.org/http://orcid.org/0000-0002-2491-0012
The performance of the ground for any geotechnical and geological engineering project is of prime concern, which is evaluated with the strength and elastic behaviour characterization. The determination of static elastic constants is very difficult, expensive, and requires a lot of time for sample preparation and testing. Therefore, nowadays, engineers are using indirect and cost-effective methods to determine elastic constants. The method of determining the dynamic elastic properties using P-wave velocity (VP), S-wave velocity (VS), and density (ρ) of the rocks has become prevalent. However, sometimes, the determination of VS is difficult and vague due to small sample sizes or low ρ of materials. Therefore, the correlation between dynamic elastic properties and VP have been studied in this paper for seven different lithology groups from nine previous studies’ databases. The predictive models using simple regression (SR) and artificial neural network (ANN) have been applied to determine the dynamic elastic properties using the VP. It was observed from the SR model that the dynamic elastic modulus (ED), dynamic shear modulus (GD), dynamic bulk modulus (KD), VS, and ρ have a positive correlation with the VP, while no correlation could be established between µD and VP. An ANN model has also been trained to estimate the ED, GD, KD, VS, and ρ using VP as an input parameter. Finally, the performance was evaluated of the SR and ANN predictive models using different statistical indicators for strength and accuracy.
Correlations Between Dynamic Elastic Properties and P-Wave Velocity for Different Rock Types
https://orcid.org/http://orcid.org/0000-0002-2491-0012
The performance of the ground for any geotechnical and geological engineering project is of prime concern, which is evaluated with the strength and elastic behaviour characterization. The determination of static elastic constants is very difficult, expensive, and requires a lot of time for sample preparation and testing. Therefore, nowadays, engineers are using indirect and cost-effective methods to determine elastic constants. The method of determining the dynamic elastic properties using P-wave velocity (VP), S-wave velocity (VS), and density (ρ) of the rocks has become prevalent. However, sometimes, the determination of VS is difficult and vague due to small sample sizes or low ρ of materials. Therefore, the correlation between dynamic elastic properties and VP have been studied in this paper for seven different lithology groups from nine previous studies’ databases. The predictive models using simple regression (SR) and artificial neural network (ANN) have been applied to determine the dynamic elastic properties using the VP. It was observed from the SR model that the dynamic elastic modulus (ED), dynamic shear modulus (GD), dynamic bulk modulus (KD), VS, and ρ have a positive correlation with the VP, while no correlation could be established between µD and VP. An ANN model has also been trained to estimate the ED, GD, KD, VS, and ρ using VP as an input parameter. Finally, the performance was evaluated of the SR and ANN predictive models using different statistical indicators for strength and accuracy.
Correlations Between Dynamic Elastic Properties and P-Wave Velocity for Different Rock Types
https://orcid.org/http://orcid.org/0000-0002-2491-0012
The performance of the ground for any geotechnical and geological engineering project is of prime concern, which is evaluated with the strength and elastic behaviour characterization. The determination of static elastic constants is very difficult, expensive, and requires a lot of time for sample preparation and testing. Therefore, nowadays, engineers are using indirect and cost-effective methods to determine elastic constants. The method of determining the dynamic elastic properties using P-wave velocity (VP), S-wave velocity (VS), and density (ρ) of the rocks has become prevalent. However, sometimes, the determination of VS is difficult and vague due to small sample sizes or low ρ of materials. Therefore, the correlation between dynamic elastic properties and VP have been studied in this paper for seven different lithology groups from nine previous studies’ databases. The predictive models using simple regression (SR) and artificial neural network (ANN) have been applied to determine the dynamic elastic properties using the VP. It was observed from the SR model that the dynamic elastic modulus (ED), dynamic shear modulus (GD), dynamic bulk modulus (KD), VS, and ρ have a positive correlation with the VP, while no correlation could be established between µD and VP. An ANN model has also been trained to estimate the ED, GD, KD, VS, and ρ using VP as an input parameter. Finally, the performance was evaluated of the SR and ANN predictive models using different statistical indicators for strength and accuracy.
Correlations Between Dynamic Elastic Properties and P-Wave Velocity for Different Rock Types
Indian Geotech J
Rahman, Tabish (author) / Sarkar, Kripamoy (author) / Sahu, Sarthak (author)
Indian Geotechnical Journal ; 54 ; 699-706
2024-04-01
8 pages
Article (Journal)
Electronic Resource
English
Correlations Between Dynamic Elastic Properties and P-Wave Velocity for Different Rock Types
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