• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.268-273
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• 2019

The apparent soil resistivity is used for estimating multilayer soil parameters, such as, layer's depth and soil resistivity. The soil parameters are estimated by continuously revising those parameters until the error between the measured and calculated apparent soil resistivity reaches to allowable level. The equation for calculating the apparent soil resistivity is complicated and time consumed, because it is composed of an infinite integral which includes a zero order Bessel's function of the first kind. In this paper, a fast algorithm for calculating the apparent soil resistivity of horizontal multilayer earth structure is proposed using exponential sampling method.

• Journal of IKEEE
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• v.23 no.1
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• pp.318-321
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• 2019

The apparent soil resistivity is used for estimating multilayer soil parameters, such as, layer's depth and soil resistivity. The apparent soil resistivity can be measured, and also can be calculated if soil parameters are given, becacuse the apparent soil resistivity is a function of these parameters. Therefore, any optimization algorithms can be used to find these parameters which make the calculated apparent soil resistivity close to the measured one. The equation for calculating the apparent soil resistivity is complicated and time consumed, because it is composed of an infinite integral which includes a zero order Bessel's function of the first kind. In this paper, a fast algorithm for calculating the apparent soil resistivity of horizontal multilayer earth structure has been presented using complex image method.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.479-487
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• 2022

This study evaluates the performance of gravel impact compaction piers system (GICPs) in strengthening retrofitting a very loose silty sand layer with a very high liquefaction risk with a thickness of 3.5 meters in a multilayer coastal soil located in Bushehr, Iran. The liquefiable sandy soil layer was located on clay layers with moderate to very stiff relative consistency. Implementation of gravel impact compaction piers is a new generation of aggregate piers. After technical and economic evaluation of the site plan, out of 3 experimental distances of 1.8, 2 and 2.2 meters between compaction piers, the distance of 2.2 meters was selected as a winning option and the northern ring of the site was implemented with 1250 gravel impact compaction piers. Based on the results of the standard penetration test in the matrix soil around the piers showed that the amount of (N₁)₆₀ in compacted soils was in the range of 20-27 and on average 14 times the amount of (1-3) in the initial soil. Also, the relative density of the initial soil was increased from 25% to 63% after soil improvement. Also the safety factor of the improved soil is 1.5-1.7 times the minimum required according to the two risk levels in the design.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.171-175
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• 2007

In this paper a methodology has been proposed to compute the parameters of the multilayer earth model using a genetic algorithm(GA). The results provided by the GA constitute the indispensable data that can be used in circuital or field simulations of grounding systems. This methodology allows to proceed toward a very efficient simulation of the grounding system and an accurate calculation of potential on the ground's surface. The sets of soil resistivity used for GA are measured in Jeju area.

• Geomechanics and Engineering
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• v.39 no.2
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• pp.129-142
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• 2024

The most significant soil parameters that are utilized in geotechnical engineering projects' design and implementations are soil strength parameters including friction (ϕ), cohesion (c), and uniaxial compressive strength (UCS). Understanding soil shear strength parameters can be guaranteed the design success and stability of structures. In this regard, professionals always looking for ways to get more accurate estimations. The presented study attempted to investigate soil shear strength parameters by using multivariate regression and multilayer perceptron predictive models which were implemented on 100 specimens' data collected from the Tabriz region (NW of Iran). The uniaxial (UCS), liquid limit (LL), plasticity index (PI), density (γ), percentage of fine-grains (pass #200), and sand (pass #4) which are used as input parameters of analysis and shear strength parameters predictions. A confusion matrix was used to validate the testing and training data which is controlled by the coefficient of determination (R²), mean absolute (MAE), mean squared (MSE), and root mean square (RMSE) errors. The results of this study indicated that MLP is able to predict the soil shear strength parameters with an accuracy of about 93.00% and precision of about 93.5%. In the meantime, the estimated error rate is MAE = 2.0231, MSE = 2.0131, and RMSE = 2.2030. Additionally, R² is evaluated for predicted and measured values correlation for friction angle, cohesion, and UCS are 0.914, 0.975, and 0.964 in the training dataset which is considerable.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2007.10a
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• pp.450-452
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• 2007

• Journal of the Korean Geotechnical Society
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• v.38 no.8
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• pp.39-52
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• 2022

Multilayer perceptron neural network was trained to determine the factor of safety and slip surface of the slope. Slope geometry is a simple slope based on Korean design standards, and the case of dry and existing groundwater levels are both considered, and the properties of the soil composing the slope are considered to be sandy soil including fine particles. When curating the data required for model training, slope stability analysis was performed in 42,000 cases using the limit equilibrium method. Steady-state seepage analysis of groundwater was also performed, and the results generated were applied to slope stability analysis. Results show that the multilayer perceptron model can predict the factor of safety and failure arc with high performance when the slope's physical properties data are input. A method for quantitative validation of the model performance is presented.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1042-1049
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• 2007

Recently, a theoretically-sound design approach, using an elastic multilayer model, is attempted in trackbed designs for the construction of high speed railways and new lines of conventional railways. In the elastic multilayer model, the stress-dependent resilient modulus($E_R$) is an important input parameter, that is, reflects substructure performance under repeated traffic loading. However, the evaluation method for resilient modulus using repeated loading triaxial test is not fully developed for practical purpose, because of costly equipment and the significantly fluctuated values depending on the testing equipment and laboratory personnel. In this study, the paper will present an indirect method to estimate the resilient modulus using dynamic properties. The resilient modulus of crushed stone, which is the typical material of sub-ballast, was calculated with the measured dynamic properties and the range of stress level of the sub-ballast, and approximated with the power model combined with bulk and deviatoric stresses. The resilient modulus of coarse grained material decreases with increasing deviatoric stress at a confining pressure, and increases with increasing bulk stress. Sandy soil(SM classified from Unified Soil Classification System) of subgrade was also evaluated and best fitted with the power model of deviatoric stress only.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1781-1782
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• 2006

In this paper, a methodology has been proposed according to which, after carrying out a set of soil's resistivity measurements using Wenner Four-probe data, one can compute the parameters of the multilayer earth structure using a genetic algorithm(GA). The results provided by the GA constitute the indispensable data that can be used in circuital or field simulations of grounding systems. The methodology allows to proceed toward a very efficient simulation of the grounding system and an accurate calculation of potential on the ground's surface.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.505-520
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• 2022

In recent years, geotextile-encased gravel columns (usually called stone columns) have become a popular method to increasing soil shear strength, decreasing the settlement, acceleration of the rate of consolidation, reducing the liquefaction potential and increasing the bearing capacity of foundations. The behavior of improved loose base-soil with gravel columns under shear loading and the shear stress-horizontal displacement curves got from large scale direct shear test are of great importance in understanding the performance of this method. In the present study, by performing 36 large-scale direct shear tests on sandy base-soil with different fine-content of zero to 30% in both not improved and improved with gravel columns, the effect of the presence of gravel columns in the loose soils were investigated. The results were used to predict the shear stress-horizontal displacement curve of these samples using support vector machines (SVM). Variables such as the non-plastic fine content of base-soil (FC), the area replacement ratio of the gravel column (Arr), the geotextile encasement and the normal stress on the sample were effective factors in the shear stress-horizontal displacement curve of the samples. The training and testing data of the model showed higher power of SVM compared to multilayer perceptron (MLP) neural network in predicting shear stress-horizontal displacement curve. After ensuring the accuracy of the model evaluation, by introducing different samples to the model, the effect of different variables on the maximum shear stress of the samples was investigated. The results showed that by adding a gravel column and increasing the Arr, the friction angle (ϕ) and cohesion (c) of the samples increase. This increase is less in base-soil with more FC, and in a proportion of the same Arr, with increasing FC, internal friction angle and cohesion decreases.