Undrained Shear Strength Of Soil Research Articles

Modeling Undrained Shear Strength of Sensitive Alluvial Soft Clay Using Machine Learning Approach

Soft soils are commonly located in many regions near seas, oceans, and rivers all over the world. These regions are vital and attractive for population and governments development. Soft soil is classified as problematic soil owing to sustaining low shear strength and high settlement under structures. Constructing structures and/or infrastructures on soft soil is a considerable risk that needs great attention from structural engineers. The bearing capacity of structure foundations on soft soil depends mainly on their undrained shear strength. This soil feature strongly influences the selection of appropriate soil improvement methods. However, determining undrained shear strength is very difficult, costly, and time-consuming, especially for sensitive clay. Consequently, extracting undisturbed samples of sensitive clay faces several difficulties on construction sites. In this research, accurate field-tested data were fed to advanced machine learning models to predict the undrained shear strength of the sensitive clay to save hard effort, time, repeated laboratory testing, and costs. In this context, a dataset of 111 geotechnical testing points were collected based on laboratory and field examinations of the soil’s key features. These features included the water content, liquid limit, dry unit weight, plasticity index, consistency index, void ratio, specific gravity, and pocket penetration shear. Several machine learning algorithms were adopted to provide the soft clay modeling, including the linear, Gaussian process regression, ensemble and regression trees, and the support vector regression. The coefficient of determination was mainly used to assess the performance of each predictive model. The achieved results revealed that the support vector regression model attained the most accurate prediction for soil undrained shear strength. These outcomes lay the groundwork for evaluating soil shear strength characteristics in a practical, fast, and low-cost way.

Optimal maximum entropy quantile function for fractional probability weighted moments and its applications in reliability analysis

The maximum entropy principle (MEP) under the constraint of fractional probability weighted moments (FPWM) is a well-developed method for a direct estimation of the quantile function of a random variable. The accuracy, unbiasedness, and efficiency of maximum entropy quantile functions (MEQFs) have been demonstrated in the literature. However, the issue of how to select an optimal order of FPWMs given a sample of data is not fully solved, and the application of this approach to reliability analysis in civil engineering has not been fully investigated. This paper presents a FPWM-based MEP with a new nondimensional analysis and proposes the Akaike information criterion to determine the optimal order of FPWM in MEP analysis. To illustrate this approach, two examples of the estimation of optimal quantile functions for soil undrained shear strength and annual maximum daily discharge are presented. The paper presents a novel approach to use the quantile function for the First Order Reliability Method, a widely used method in civil engineering. As a case study of this approach, the reliability analysis of a rock slope is included. The FPWM-based MEQFs are compared with common empirical distributions and MEQFs based on integral probability weighted moments to demonstrate the advantages and disadvantages of the developed method.

Prediction of Undrained Shear Strength by the GMDH-Type Neural Network Using SPT-Value and Soil Physical Properties.

This study presents a novel method for predicting the undrained shear strength (cu) using artificial intelligence technology. The cu value is critical in geotechnical applications and difficult to directly determine without laboratory tests. The group method of data handling (GMDH)-type neural network (NN) was utilized for the prediction of cu. The GMDH-type NN models were designed with various combinations of input parameters. In the prediction, the effective stress (σv’), standard penetration test result (NSPT), liquid limit (LL), plastic limit (PL), and plasticity index (PI) were used as input parameters in the design of the prediction models. In addition, the GMDH-type NN models were compared with the most commonly used method (i.e., linear regression) and other regression models such as random forest (RF) and support vector regression (SVR) models as comparative methods. In order to evaluate each model, the correlation coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) were calculated for different input parameter combinations. The most effective model, the GMDH-type NN with input parameters (e.g., σv’, NSPT, LL, PL, PI), had a higher correlation coefficient (R2 = 0.83) and lower error rates (MAE = 14.64 and RMSE = 22.74) than other methods used in the prediction of cu value. Furthermore, the impact of input variables on the model output was investigated using the SHAP (SHApley Additive ExPlanations) technique based on the extreme gradient boosting (XGBoost) ensemble learning algorithm. The results demonstrated that using the GMDH-type NN is an efficient method in obtaining a new empirical mathematical model to provide a reliable prediction of the undrained shear strength of soils.

Numerical limit analyses on the uplift capacity of strip plate anchor in anisotropic spatially random cohesive soil

Plate anchors are used to resist uplift forces of both offshore and on-land structures. Numerous studies have been carried out to date to evaluate the ultimate uplift capacity of anchor plates. Most of them assumed the soil as homogeneous and isotropic. Naturally, the soil is heterogeneous and anisotropic. The undrained shear strength of soil may vary significantly within a seemingly homogeneous layer. This paper analyzes the impact of spatial shear strength variability of cohesive soil on the uplift capacity of strip anchors through numerical limit analyses. Repeated Monte Carlo simulations within a selected range of both isotropic and anisotropic spatial correlation length and coefficient of variation of undrained shear strength are conducted using the random field theory to evaluate the effect of probabilistic uplift capacity of shallow and deep strip anchors. The outcomes are then compared to those of a similar study in which the probabilistic uplift capacity was investigated using a displacement-based analysis employing the local averaging subdivision of the random finite element method (LAS-RFEM). The comparison depicts the requirement of a higher safety factor than the published results of RFEM. The findings suggest considering the spatial variation of soil strength for the safe design of plate anchors.

Characterization of Stationary and Nonstationary Random Fields with Different Copulas on Undrained Shear Strength of Soils: Probabilistic Analysis of Embankment Stability on Soft Ground

Soil properties are known to have high spatial variability and often fluctuate with depth. The objective of this study was to investigate the effects of using different models to simulate the spatial variability of undrained shear strength (su) to calculate the failure probability of an embankment on soft ground. Two-dimensional random fields of su were generated based on one Gaussian and two non-Gaussian copulas, with stationary and nonstationary assumptions. Statistical parameters of su variation—mean, coefficient of variance, and scale fluctuation (correlation length)—were estimated from simulated and field data. Monte Carlo probabilistic analyses were performed on embankment stability based on both stationary and nonstationary random fields and all copula approaches; results showed more frequent embankment failures at low water levels in the embankment ditch. In particular, the nonstationary random field (su increases with depth) simulations more closely reflected real observed data, with higher probabilities of slope failure and lower mean factor of safety than the stationary random field simulations. Additionally, the non-Gaussian copulas provided simulated data that more accurately reflected observed field data, highlighting the importance of copula selection when characterizing soil parameter random fields.

Uplift resistance of buried pipelines: The contribution of seepage forces

Pipelines are commonly buried, and can buckle upwards when heated if there is insufficient soil uplift capacity. Interface tension beneath the buried pipe significantly influences the uplift capacity at shallow embedments. Conventional design approaches, which consider either zero or unlimited interface tension, do not assess and quantify the effect of interface tension on uplift capacity. The present study bridges the gap between conventional “no tension” and “full tension” capacities. Mobilisation of interface tension is governed by seepage forces which in turn directly control the formation of a gap beneath the pipe. A large deformation finite element approach, which simulates this phenomenon of gap formation using a thin layer of gap elements below the pipe, is adopted to study the soil response for various cases of uplift velocity, embedment and soil weight. The enhancement in undrained shear strength of soil at higher uplift velocities due to strain rate effects has also been considered. The interface tension mobilised at these different velocities and embedments varies systematically in a way that is expressed by modifying Hvorslev's intake factors. The proposed expressions may be used with the existing methodologies to assess pipe stability during operation, demonstrated here through a design example.

Correlation between undrained shear strength and liquidity index of soils in Malaysia

Accuracy of soil undrained shear strength measurement is often governed by the quality of undisturbed soil sampling. Numerous previous attempts have been made to establish correlations between the undrained shear strength and various soil physical parameters. This paper aims to determine a correlation between the undrained shear strength (cu) and liquidity index (IL) based on 34 soil samples collected from selected sites in Peninsular Malaysia. Sieving, hydrometer analysis and Atterberg limit tests were performed to determine physical properties of the soils. The undrained shear strengths were determined using the Unconsolidated Undrained (UU) triaxial test. An attempt was made to correlate the undrained shear strength with liquidity index of all the soil specimens. However, the correlation was found to be considerably weak (r2 = 0.47). The correlation was improved significantly (r2 = 0.82) by limiting the data to soils with fines content of more than 65% only. The proposed equation was in the form cu = a exp(-bIL) where the values of constants a and b were determined empirically as 72.9 and 1.95, respectively.

Probabilistic characterization of soil properties based on the maximum entropy method from fractional moments: Model development, case study, and application

In probabilistic reliability analysis for geotechnical engineering applications, determining the underlying probability distributions of soil properties and corresponding parameters from observed data is a critical initial step because subsequent risk and reliability analyses depend upon these evaluations. Conventionally, the choice of probability distribution is dictated by subjective familiarity with a classical (e.g., normal or lognormal) distribution. This paper proposes an objective and unbiased method to estimate probability distributions of a soil property using the maximum entropy method from fractional moments of observed data. The probability distribution is based on the concept of maximum entropy and is free from the assumptions of classical distributions. A case study is presented for the undrained shear strength of soil in the Nipigon River landslide area, Ontario, Canada. The maximum entropy distributions of the soil property from fractional moments are compared to the frequency histogram, normal and lognormal distributions, and maximum entropy distributions from integral moments. The maximum entropy distribution with two-order fractional moments, almost equivalent to that with four-order integral moments, is verified with the chi-square goodness-of-fit test. Issues related to overfitting/underfitting, minimum sample size, fractional orders, negative moments, and limitations are discussed. Application of the method to geotechnical reliability analysis is illustrated.

Laboratory Evaluation of Undrained Shear Strength of a Soft Fine Grained Soils

The determination of undrained shear strength of soils is commonly achieved using triaxial testing in which specimen is carefully prepared before testing to maintain its original field condition. However, for soft soils preparing and handling specimens without causing any disturbance is a difficult job and may not always be successful. Other laboratory testing techniques can be adopted provided they can produce reliable results for such cases and can overcome the problem of pretest preparation process and hence avoiding any alteration of sample field condition. Extensive laboratory investigation on a soft marine soil recovered from sea bed offshore of Benghazi city, the testing program involves investigation of the basic geotechnical properties, focusing specifically on the determination of the undrained shear strength of such soils as determined by both the conventional unconsolidated undrained triaxial testing (UU) and the simple laboratory vane shear testing device (Miniature shear vane MV). The resulting shear strength obtained by UU-triaxial test, and resulting shear strength measured by Miniature shear vane MV were examined, compared and discussed on the light of other research works. Furthermore, the problems faced during testing soft samples in triaxial apparatus was also presented. The resulting undrained shear strength obtained by UU-triaxial test was found generally lower than that produced by Miniature shear vane MV which is attributed to sample disturbance before testing in triaxial. The study also demonstrates that despite of high scatter, the undrained shear strength obtained by MV can be reasonably comparable with the results of other investigations on soft soils.

Probabilistic basal heave stability analyses of supported circular shafts in non-homogeneous clayey soils

Circular shafts are commonly used to construct accesses to facilitate tunnel boring machine works and can be used as ventilation systems, subway stations or emergency exits. This study presents a probabilistic analysis of supported circular shafts in undrained and non-homogeneous clayey soils to reflect the uncertainty influences of the soil undrained shear strength at the ground surface, non-homogeneity coefficient, unit weight and soil-wall adhesion factor. The basal heave safety factor is evaluated by an axisymmetric lower bound Finite Element Limit Analysis and a probabilistic analysis is discussed using the adaptive Polynomial Chaos Kriging technique-based Monte-Carlo Simulation and a Global Sensitivity Analysis (GSA). After deterministic and probabilistic comparisons, academic cases are performed to get some insights for the following problems: (1) importance of the uncertainty’s consideration; (2) effect of the soil-wall interface; (3) influence of non-homogeneous soils on the circular shaft’s stability. Besides, some sensitivity analyses are conducted to discuss the input random variables importance. Obtained results show that the coefficient of variation, soil-wall adhesion factor and soil non-homogeneity coefficients have a remarkable influence on the circular shaft stability.

Artificial Neural Network (ANN) Model for Shear Strength of Soil Prediction

Geotechnical structures, design of embankment, earth and rock fill dam, tunnels, and slope stability require further attention in determining the shear strength of soil and other parameters that govern the result. The shear strength of soil commonly obtained by conducting laboratory testing such as Unconfined Compression Strength (UCS) Test and Unconsolidated Undrained (UU) Test. However, random errors and systematic errors can occur during experimental works and caused the findings imprecise. Besides, the laboratory test also consuming a lot of time and some of them are quite costly. Therefore, soft computational tools are developed to improve the accuracy of the results and time effectively when compared to conventional method. In this study, Artificial Neural Network (ANN) was employed to develop a predictive model to correlate the moisture content (MC), liquid limit (LL), plastic limit (PL), and liquidity index (LI) of cohesive soil with the undrained shear strength of soil. A total of 10 databases was developed by using MATLAB 7.0 - matrix laboratory with 318 of UCS tests and 451 of UU tests which are collected from the verified site investigation (SI) report, respectively. All the SI reports collected were conducted in Sarawak, Malaysia. The datasets were split into ratio of 3:1:1 which is 60:20:20 (training: validation: testing) with one hidden layer and eight hidden neurons. The input parameter of Liquidity index (LI) has shown the highest R-value (regression coefficient) which are 0.926 and 0.904 for UCS and UU model, respectively. In addition, the predictive models were tested and compare with the predicted and observed cohesion obtained from the collected experimental results. In summary, the ANN has the feasibility to be used as a predictive tool in estimating the shear strength of the soil.

Analytical Solution to Ultimate Lateral Pressure on a Vertical Plate in Undrained Soil

For a vertical plate emerging on the surface of undrained cohesive soil, the adhesion between the plate and soil considerably impacts the lateral soil pressure on it. However, very few closed-form solutions have been published to address this seemingly simple problem; they either are restricted to certain conditions or overpredict the ultimate lateral pressure. This paper applies both the lower-bound and upper-bound methods of plasticity to develop a rigorous analytical solution to the ultimate lateral pressure, allowing for the undrained shear strength of soil to increase linearly with depth and a general adhesion on the interface. A method is presented to extend the static stress field throughout the soil mass to validate the lower-bound values. The developed solution is found to be an exact solution for homogeneous soil; the predicted results for nonhomogeneous soil fall within a narrow range bounded by the lower and upper limit values, with the range of errors mostly being within 1%. The solution reduces to the classic Bell’s relationship in the undrained condition if ignoring the adhesion on the interface. When the full active pressure behind the plate is mobilized, the upper-bound solution is rigorous but the lower-bound one is not unless examining a smooth surface. However, the predicted results are close enough to more rigorous ones to be used in engineering practice.

Analytical method for laterally loaded piles in soft clay considering the influence of soil outside the scour hole on the effective overburden pressure

Scour reduces the effective overburden pressure and the undrained shear strength of soil, thus affecting the lateral load-bearing capacity of pile foundations. Compared with general scour, local scour can decrease the reduction of the effective overburden pressure and the undrained shear strength around the pile due to the existence of soil outside the scour hole. To fully reflect the actual situation at a site, the behavior of laterally loaded piles in soft clay should consider both the scour-hole dimensions and the soil stress history. This paper proposes a closed-form analytical solution for laterally loaded piles in soft clay that can simultaneously account for the changes in effective overburden pressure and undrained shear strength caused by the scour-hole dimensions and the soil stress history based on the p–y curve proposed by Matlock. The average reduced stress is introduced according to Boussinesq’s point load solution. Case studies demonstrate that the analytical method is reliable with reasonable accuracy. According to the parameter study, the load eccentricity is the most sensitive factor compared with the changes in soil properties caused by the scour-hole dimensions and the soil stress history.

Improvement of Unconfined Compressive Strength of Soft Clay using Microbial Calcite Precipitates

The precipitation of calcite induced via microorganisms (MICP) is a technique that has been developed as an innovative sustainable ground improvement method utilizing ureolytic bacteria to soil strengthening and stabilization. Locally isolated Bacillus Sonorensis from Iraqi soil samples were found to have high abilities in producing urease. This study aims to use the MICP technique in improving the undrained shear strength of soft clay soil using two native urease producing bacteria that help in the precipitation of calcite to increase the cementation between soil particles. Three concentrations of each of the locally prepared Bacillus sonorensis are used in this study for cementation reagent (0.25M, 0.5M, and 1M) during the period of treatment. The results showed that the native isolated bacteria have high activity in bindings the soil particles together. The results of unconfined compressive strength tests showed that using MICP helps increase the undrained shear strength of soil by (3-5 times) for C11 types of native isolates, but the D11 was (1.5-2 times) because two types have different activity. This study's main finding is using the native urease-producing bacteria isolated from Iraqi soil in the MICP technique for the biocementation of soil, which is considered one of the sustainable techniques in the construction industry.

The Role of the Cement, Lime, and Natural Pozzolan Stabilizations on the Mechanical Response of a Collapsible Soil

This paper presents an extensive array of laboratory investigation on collapse behavior and shear strength characteristics of collapsible soils at different initial structures. This study also clarifies the crucial role of chemical stabilization on the mechanical behavior and the workability of the collapsible soils using different percentages of various stabilizer agents. The effect of the curing time and the amount of the agents on the collapsibility, the unconfined compressive strength, the undrained shear strength, and the consistency of the treated collapsible soils were studied. The findings demonstrated that cement outperformed lime and natural pozzolan in improving the strength and engineering properties of these collapsible clays. The results indicated that adding cement to soil minimized the degree of collapsibility significantly and increased the undrained shear strength of soil up to 5 times.

Influence of the Spatial Variability of Soil Shear Strength on Deep Excavation: A Case Study of a Bangkok Underground MRT Station

This paper investigates the effects that the spatial variability of a soil's undrained shear strength has on lateral wall movements and ground surface settlements when performing a deep excavation stability analysis. A random finite-element method is employed to statistically assess a deep excavation. A case study based on an actual deep excavation project in Bangkok's subsoils was used to validate the methodology. The two-dimensional spatial variability of the undrained shear strength in the clay layers of Bangkok's subsoil is simulated using the random field theory and Monte Carlo simulation. The Mohr–Coulomb model is used to predict lateral wall movements and ground surface settlements, while the stability analysis of the deep excavation is evaluated by the factor of safety using the strength reduction approach. The results show that spatial variability highly affects the distribution of lateral wall movements and ground surface settlements, as well as the scatter of the factor of safety corresponding to progressing stages of excavation.

Probabilistic undrained bearing capacity of skirted foundations under HM combined loading in spatially variable soils

The behaviour of skirted foundations subjected to combined vertical (V), horizontal (H) and moment (M) loading is of particular interest to the geotechnical engineers. The bearing capacity of skirted foundations under combinations of VHM loading is represented by failure envelopes, which is commonly used in its stability assessment. In current studies, failure envelopes for skirted foundations were established deterministically, ignoring the spatial variability of natural soils. The paper aimed to investigate the probabilistic failure envelope of skirted foundations in the presence of soil undrained shear strength linearly increasing with depth. Random finite element method (RFEM) combining with random field theory, finite element method and Monte Carlo simulation was conducted to evaluate the uniaxial bearing capacities and define the HM failure envelopes. The influence of spatial variability on the stochastic response of bearing capacity in the HM space was discussed.

Simplified analysis of curvilinear penetration of free fall sphere projectile in soft soil

Free fall projectiles have been used in offshore engineering to determine in-situ undrained shear strength profiles of near-surface soft soils from accelerations recorded during penetrating. In doing so, however, only the equation of motion in the vertical direction has been formulated with the vertical acceleration by assuming vertical impact and penetration. In this study, the governing equations of curvilinear penetration of a sphere projectile are established with consideration of an angle of impact with soil surface. By treating the penetration process as an initial value problem, an algorithm is proposed for computing the trajectory, velocity and linear acceleration of penetration. The effects of impact angle, impact velocity and soil strength non-homogeneity on the penetration behavior are analyzed using a set of parameters reported in literature. The computed results of the final embedment depth and linear acceleration of sphere are shown to be in reasonably good agreement with published field data. Moreover, a new explicit equation is derived for determining the undrained shear strength of soil based on both vertical and horizontal linear accelerations. The accuracy of the undrained shear strength estimated by assuming vertical penetration is assessed. The impact angle is shown to have important influence on soil strength determination.

Correlation of Undrained Shear Strength and Liquidity Index of Fine-Grained Soils in West Java, Indonesia

The undrained shear strength of fine-grained soils is an important property in geotechnical engineering. However, the process of determining undrained shear strength can be challenging. Hence, the correlation of undrained shear strength with other soil properties needs to be established. Several studies have estimated undrained shear strength using the liquidity index. In the current study, we aim to find the best correlation of undrained shear strength and liquidity index of fine-grained soils in West Java, Indonesia at various water contents using the form of correlation of undrained shear strength and liquidity index and also factors influencing the undrained shear strength. The values of undrained shear strength and liquidity index are obtained by laboratory test and data collection from previous studies of soils in West Java. Results show a good linear relationship between the logarithmic value of undrained shear strength and liquidity index for 173 variations of soil samples. We also can conclude that the undrained shear strength of fine-grained soils is controlled by the proportion of finer grains presence and also the plasticity of the soils.

Probabilistic analysis of tunnel face stability considering spatially variable undrained shear strength with linearly increasing mean trend

The inherent spatial variability of soil properties has been considered as one of the main sources of uncertainties in geotechnical problems. The need for probabilistic analysis of the tunnel face stability that takes into account the variability of soil properties has been acknowledged. This article employed a probabilistic-based method, called random finite difference method, for evaluating the stability of tunnel face under the influence of the variability of undrained shear strength in clays. The two-dimensional spatial variation in soil undrained shear strength is modeled by random fields, which are discretized by the Covariance Matrix Decomposition method. The procedure for random finite difference method is presented. An illustrative example is employed to investigate the effect of soil variability. Particular attention has been paid to the situation that undrained shear strength increases with depth. The results demonstrate that ignoring the variability of undrained shear strength will result in overestimates of the tunnel face stability if the support pressure of the tunnel face exceeds the deterministic value, especially for higher coefficient of variation of soil undrained shear strength. Minor differences in the failure mechanism are observed in comparison to the deterministic case, considering only the global failure of the tunnel face is observed. In addition, ignoring the increase of undrained shear strength with depth will lead to conservative designs. The random finite difference method can provide a practical tool for evaluating the stability of a tunnel face in variable soils.