• Geomechanics and Engineering
• /
• 제32권1호
• /
• pp.1-20
• /
• 2023

To predict the consolidation behavior of dredged and reclaimed marine clays exhibiting consolidation settlement with large strains, the finite strain consolidation theory must be used. However, challenges in appropriately applying the theory and determining input parameters make design and analysis studies difficult. To address these challenges, design charts for predicting the consolidation settlement of reclaimed marine clays are developed by a numerical approach based on the finite strain consolidation theory. To prepare the design charts, a sensitivity analysis of parameters is performed, and influencing parameters, such as initial void ratio and initial height, as well as the non-linear constitutive void ratio-effective stresspermeability relation, are confirmed. Six representative Korean marine clays obtained from different locations with different liquid limits are used. The design charts for estimating the consolidation times corresponding to various degrees of consolidation are proposed for each of the six representative clays. The consolidation settlements predicted from the design charts are compared to those in previous studies and at an actual construction site and are found to agree well with them. The proposed design charts can therefore be used to solve problems related to the consolidation of reclaimed marine clays having large strains.

• Geomechanics and Engineering
• /
• 제29권4호
• /
• pp.435-449
• /
• 2022

In this paper, unreinforced and geogrid-reinforced soil foundations were modeled by discrete element method and this performed under surface strip footing loads. The effects of horizontal position of geogrid, vertical position, thickness, number, confining pressure have been investigated on the footing settlement and propagation of tensile force along the geogrids. Also, interaction between rectangular tunnel and strip footing with and without presence of geogrid layer has been analyzed. Experimental results of the literature were used to validation of relationships between the numerically achieved footing pressure-settlement for foundations of reinforced and unreinforced soil. Models and micro input parameters which used in the numerical modelling of reinforced and unreinforced soil tunnel were similar to parameters which were used in soil foundations. Model dimension was 1000 mm* 600 mm. Normal and shear stiffness of soils were 5*10⁵ and 2.5 *10⁵ N/m, respectively. Normal and shear stiffness of geogrid were 1*10⁹ and 1*10⁹ N/m, respectively. Loading rate was 0.001 mm/sec. Micro input parameters used in numerical simulation gain by try and error. In addition of the quantitative tensile force propagation along the geogrids, the footing settlements were visualized. Due to collaboration of three layers of geogrid reinforcements the bearing capacity of the reinforced soil tunnel was greatly improved. In such practical reinforced soil formations, the qualitative displacement propagations of soil particles in the soil tunnel and the quantitative vertical displacement propagations along the soil layers/geogrids represented the geogrid reinforcing impacts too.

• Geomechanics and Engineering
• /
• 제33권5호
• /
• pp.487-506
• /
• 2023

Looking from the past to the present, the earthquakes can be said to be type of disaster with most casualties among natural disasters. Soil liquefaction, which occurs under repeated loads such as earthquakes, plays a major role in these casualties. In this study, analytical equation models were developed to predict the probability of occurrence of soil liquefaction. In this context, the parameters effective in liquefaction were determined out of 170 data sets taken from the real field conditions of past earthquakes, using WEKA decision tree. Linear, Exponential, Power and Quadratic models have been developed based on the identified earthquake and ground parameters using Krill Herd algorithm. The Exponential model, among the models including the magnitude of the earthquake, fine grain ratio, effective stress, standard penetration test impact number and maximum ground acceleration parameters, gave the most successful results in predicting the fields with and without the occurrence of liquefaction. This proposed model enables the researchers to predict the liquefaction potential of the soil in advance according to different earthquake scenarios. In this context, measures can be realized in regions with the high potential of liquefaction and these measures can significantly reduce the casualties in the event of a new earthquake.

• Geomechanics and Engineering
• /
• 제37권3호
• /
• pp.197-211
• /
• 2024

This research studies the effect of geotechnical factors on EPB-TBM performance parameters. The modeling was performed using simple and multivariate linear regression methods, artificial neural networks (ANNs), and Sugeno fuzzy logic (SFL) algorithm. In ANN, 80% of the data were randomly allocated to training and 20% to network testing. Meanwhile, in the SFL algorithm, 75% of the data were used for training and 25% for testing. The coefficient of determination (R²) obtained between the observed and estimated values in this model for the thrust force and cutterhead torque was 0.19 and 0.52, respectively. The results showed that the SFL outperformed the other models in predicting the target parameters. In this method, the R² obtained between observed and predicted values for thrust force and cutterhead torque is 0.73 and 0.63, respectively. The sensitivity analysis results show that the internal friction angle (φ) and standard penetration number (SPT) have the greatest impact on thrust force. Also, earth pressure and overburden thickness have the highest effect on cutterhead torque.

• Geomechanics and Engineering
• /
• 제31권1호
• /
• pp.113-127
• /
• 2022

The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R² greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R² and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

• Geomechanics and Engineering
• /
• 제37권3호
• /
• pp.213-222
• /
• 2024

Determination of jointed rock mass properties plays a significant role in the design and construction of underground structures such as tunneling and mining. Rock mass classification systems such as Rock Mass Rating (RMR), Rock Mass Index (RMi), Rock Mass Quality (Q), and deformation modulus (Em) are determined from the jointed rock masses. However, parameters of jointed rock masses can be affected by the tunnel depth below the surface due to the effect of the in situ stresses. In addition, the geomechanical properties of rocks change due to the effect of metamorphism. Therefore, the main objective of this study is to apply correlation analysis to investigate the relationships between rock mass properties and some parameters related to the depth of the tunnel studied. For this purpose, the field work consisted of determining rock mass parameters in a tunnel alignment (~7.1 km) at varying depths from 21 m to 431 m below ground surface. At the same excavation depths, thirty-seven rock types were also sampled and tested in the laboratory. Correlations were made between vertical stress and depth, horizontal/vertical stress ratio (k) and depth, k and Em, k and RMi, k and point load index (PLI), k and Brazilian tensile strength (BTS), Em and uniaxial compressive strength (UCS), UCS and PLI, UCS and BTS. Relationships were significant (significance level=0.000) at the confidence interval of 95% (r = 0.77-0.88) between the data pairs for the rocks taken from depths greater than 166 m where the ratio of horizontal to vertical stress is between 0.6 and 1.2. The in-situ stress parameters affected rock mass properties as well as metamorphism which affected the geomechanical properties of rock materials by affecting the behavior of minerals and textures within rocks. This study revealed that in-situ stress parameters and metamorphism should be reviewed when tunnel studies are carried out.

• Geomechanics and Engineering
• /
• 제8권4호
• /
• pp.559-594
• /
• 2015

A nonlinear creep function incorporated into the elastic visco-plastic model may describe the long-term soil deformation more accurately. However, by applying the conventional procedure, there are challenges to determine the model parameters due to limitation of suitable data points. This paper presents a numerical solution to obtain several parameters simultaneously for a nonlinear elastic visco-plastic (EVP) model using the available consolidation data. The finite difference scheme using the Crank-Nicolson procedure is applied to solve a set of coupled partial differential equations of the time dependent strain and pore water pressure dissipation. The model parameters are determined by applying the algorithm of trust-region reflective optimisation in conjunction with the finite difference solution. The proposed method utilises all available consolidation data during dissipation of the excess pore water pressure to determine the required model parameters. Moreover, the reference time in the elastic visco-plastic model can readily be adopted as a unit of time; denoting creep is included in the numerical predictions explicitly from the very first time steps. In this paper, the settlement predictions of thick soft clay layers are presented and discussed to evaluate and compare the accuracy and reliability of the proposed method against the graphical procedure to obtain the model parameters. In addition, comparison of the available experimental results to the numerical predictions confirms the accuracy of the numerical procedure.

• Geomechanics and Engineering
• /
• 제23권5호
• /
• pp.419-429
• /
• 2020

To investigate the effect of spatial variability on hydraulic properties of unsaturated soils, a numerical model is set up which can simulate seepage process in an unsaturated heterogeneous soil. The unsaturated heterogeneous soil is composed of matrix sand embedded with a small proportion of clay for simulating the heterogeneity. Soil-water characteristic curve and unsaturated hydraulic conductivity curve of the unsaturated soil are expressed by Van Genuchten model. Hydraulic parameters of the matrix sand are considered as random fields. Different autocorrelation lengths (ACLs) of hydraulic parameter of the matrix sand and different proportions of clay are assumed to investigate the influence of spatial variability on the equivalent hydraulic properties of the heterogeneous soil. Four model sizes are used in the numerical experiments to investigate the influence of scale effects and to determine the sizes of representative volume element (RVE) in the numerical simulations. Through a number of Monte Carlo simulations of unsaturated seepage analysis, the means and the coefficients of variations (COVs) of the equivalent hydraulic parameters of the heterogeneous soil are calculated. Simulations show that the ACL and model size has little influence on the means of the equivalent hydraulic parameters, but they have a large influence on the COVs of the equivalent hydraulic parameters. The size of an RVE is mainly affected by the ACL and the proportion of heterogeneity. The influence of spatial variability on the hydraulic parameters of the heterogeneous unsaturated soil can be used as a guidance for geotechnical reliability analysis and design related to unsaturated soils.

• Geomechanics and Engineering
• /
• 제9권3호
• /
• pp.345-360
• /
• 2015

Wave equation analysis programs (WEAP) such as GRLWEAP and TNOWave were primarily developed for pre-driving analysis. They can also be used for post-driving measurement applications with some refinements. In the case of pre-driving analysis, the programs are used for the purpose of selecting the right equipment for a given ground condition and controlling stresses during pile driving processes. Recently, the program is increasingly used for the post-driving measurement application, where an assessment based on a variety of input parameters such as hammer, driving system and dynamic behaviour of soil is carried out. The process of this type of analysis is quite simple and it is performed by matching accurately known parameters, such as from CAPWAP analysis, to the parameters used in GRLWEAP analysis. The parameters that are refined in the typical analysis are pile stresses, hammer energy, capacity, damping and quakes. Matching of these known quantities by adjusting hammer, cushion and soil parameters in the wave equation program results in blow counts or sets and stresses for other hammer energies and capacities and cushion configuration. The result of this analysis is output on a Bearing Graph that establishes a relationship between ultimate capacity and net set per blow. A further application of this refinement method can be applied to the assessment of dynamic formulae, which are extensively used in pile capacity calculation during pile driving process. In this paper, WEAP analysis is carried out to establish the relationship between the ultimate capacities and sets using the various parameters and using this relationship to recalibrate the dynamic formula. The results of this analysis presented show that some of the shortcoming of the dynamic formula can be overcome and the results can be improved by the introduction of a correction factor.

• Geomechanics and Engineering
• /
• 제20권3호
• /
• pp.191-205
• /
• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.