Accepted Articles
Back to the articles list |
Back to browse issues page
1- Ferdowsi University of Mashhad
2- Ferdowsi University of Mashhad ,lashkaripour@um.ac.ir
2- Ferdowsi University of Mashhad ,
Abstract: (282 Views)
One of the crucial parameters in the design of structures, deep foundations, and underground excavations is the elastic modulus. Determining this parameter is costly and requires extensive validation, prompting researchers to continuously seek empirical relationships for its estimation. In this study, Pearson's correlation method was employed to assess the correlation coefficient between independent variables and the elastic modulus. Subsequently, a multivariate linear model, including a comprehensive model, a coarse-grained soil model, and a fine-grained soil model, was developed to predict the elastic modulus of the alluvial deposits in the Mashhad city. This model was formulated using multiple linear regression analysis based on data obtained from pressuremeter and laboratory tests conducted on 180 boreholes, totaling 5783 meters of drilling, within the Mashhad Metro Line 3 project.
The significance of this research lies in the fact that 160 relevant data points were selected from 489 pressuremeter tests, ensuring that basic soil parameters at the same depth were available. Additionally, cementation parameters of the soil were incorporated. A stepwise backward elimination method was used to determine the final comprehensive multivariate linear model, and statistical analyses were performed using Python software.
This study examined the influence of fundamental soil parameters, including gravel percentage, sand percentage, fine-grained percentage, passing diameters (D10, D30, D60), uniformity coefficient, coefficient of curvature, liquid limit, plastic limit, moisture content, natural density, dry density, specific gravity, and natural cementation (including gypsum, organic matter, and carbonates), along with the effects of depth and in-situ stress on the elastic modulus derived from pressuremeter tests. Finally, the multiple linear regression model for predicting the elastic modulus of soil (Ep) was presented as an equation. The scatter plot comparing actual and predicted elastic modulus values, along with the regression model fit, demonstrated a satisfactory level of accuracy.
The significance of this research lies in the fact that 160 relevant data points were selected from 489 pressuremeter tests, ensuring that basic soil parameters at the same depth were available. Additionally, cementation parameters of the soil were incorporated. A stepwise backward elimination method was used to determine the final comprehensive multivariate linear model, and statistical analyses were performed using Python software.
This study examined the influence of fundamental soil parameters, including gravel percentage, sand percentage, fine-grained percentage, passing diameters (D10, D30, D60), uniformity coefficient, coefficient of curvature, liquid limit, plastic limit, moisture content, natural density, dry density, specific gravity, and natural cementation (including gypsum, organic matter, and carbonates), along with the effects of depth and in-situ stress on the elastic modulus derived from pressuremeter tests. Finally, the multiple linear regression model for predicting the elastic modulus of soil (Ep) was presented as an equation. The scatter plot comparing actual and predicted elastic modulus values, along with the regression model fit, demonstrated a satisfactory level of accuracy.
Keywords: Elastic Modulus, Multivariate Regression, Pressuremeter, Mashhad Alluvial Deposits, Cementation
Type of Study: Original Research |
Subject:
En. Geology
Received: 2025/03/3 | Accepted: 2025/06/3 | Published: 2025/06/20
Received: 2025/03/3 | Accepted: 2025/06/3 | Published: 2025/06/20
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
