Permeability Coefficient Of Soil Research Articles

A METHOD FOR PREDICTING UNSATURATED SOIL PERMEABILITY COEFFICIENT BASED ON CLAY CONTENT

The unsaturated permeability coefficient is of importance to study the behavior of the water seepage and contaminant transport in unsaturated soils. The direct measurement of the unsaturated permeability coefficient is time consuming and laborious. Therefore, indirect approaches are usually applied to obtain the unsaturated permeability coefficient. However, indirect methods still have some drawbacks. An indirect method is usually fitted through the soil–water characteristic curve of a special type of soil, which also requires a large workload and its application is limited. To overcome these drawbacks, a fractal model of the relative permeability coefficient of unsaturated soils has been deduced in this study based on the relation between clay contents and fractal dimensions in terms of mass. A new fractal simple prediction method of unsaturated soil absolute permeability coefficient associated with the new fractal model has also been proposed by combining the simple relation between saturated permeability coefficient and air-entry value. The method is validated with the experimental data of existing literature, and the result shows that the proposed model has a higher prediction accuracy.

A NEW FRACTAL MODEL FOR PREDICTING SATURATED SOIL PERMEABILITY UNDER DIFFERENT DEFORMATION

The permeability coefficient and air-entry value of saturated soil are important hydraulic properties, which play an important role in engineering applications. Subsoil supporting foundation is subjected to stress and undergoes deformation; the saturated permeability coefficient of such deformed soil is of practical importance. With the help of fractal theory, based on the different fractal forms of Tao–Kong model, CCG model, Mualem model, and soil–water characteristic curve, this paper derives the saturated permeability coefficient models under four deformation conditions, considering the saturation permeability coefficient is inversely proportional to the square of the air-entry value and directly proportional to the square of the maximum aperture of the soil. Combining the prediction method of air-entry value under deformation conditions, four prediction methods for the permeability coefficient of deformed saturated soil are established and the method proposed in this paper is validated by the measured value of the saturated permeability coefficient of the deformed soil. As observed, the predicted values of the four methods for clay, silt loam, sandy loam and sandy soil under deformed conditions are in acceptable agreement with the measured values, and the prediction results of the second prediction method are the closest to the measured values.

Influence of permeability on rainfall infiltration based on water gas two phase flow

The permeability function is one of the key properties in unsaturated soil mechanics and variation of parameters in soil water characteristic curve can easily affect matric suction as well as infiltration. The purpose of this research is to explore the significant effect of parameters in SWCC on rainfall infiltration. A water gas two phase flow analysis method was conducted to investigate the influence of parameters in SWCC on stable infiltration intensity. Result showed that when saturation was low, stable intensity of infiltration was greatly affected by matric suction because the modified parameters were related to pore size distribution such as air entry value ρ0 and parameter m. When saturation was close to 1, the influence of soil infiltration intensity was almost not affected by matric suction. The minimum value of stable infiltration of intensity was mainly determined by the intrinsic permeability, while saturation of this value was mainly affected by soil water characteristic curve, intrinsic permeability coefficient of soil as well as water relative permeability coefficient.

Permeability and Disintegration Characteristics of Composite Improved Phyllite Soil by Red Clay and Cement

The bearing capacity of the phyllite soil subgrade can be greatly improved by red clay, but the water stability of the modified soil is still poor. Hence, the blended soil has been found to be unsuitable for the construction of high-speed railways. This paper proposes an innovative scheme, by adding appropriate amounts of cement and red clay concurrently, to improve phyllite soil, which achieves a higher bearing capacity of the subgrade immediately after compaction, while also solving the problem of insufficient water stability. Laboratory tests of the permeability and disintegration characteristics of phyllite soils improved by cement, red clay, and both were carried out. The test results show that the permeability coefficient and maximum disintegration rate of soil can be improved effectively by using both red clay and cement. It was found that the optimal combination scheme is to add 3% cement and 40% red clay to phyllite soil by mass. Under the optimal scheme, the permeability coefficient, maximum disintegration rate, and disintegration rate of the improved soil decreased by 90.02%, 90.30%, and 99.02%, respectively, compared with the phyllite soil. The microscopic study shows that the mechanism of red clay blending with phyllite is that the finer particles of red clay infill the pores among the phyllite particles, thus reducing its permeability coefficient. The mechanism of adding cement to the blending soil mainly results from the production of hard-setting new materials and the formation of a cementation network among the soil particles, which not only increases the shear strength of the soil, but also reduces the permeability coefficient and the maximum disintegration ratio of the soil. This work makes full use of the complementary characteristics of red clay and phyllite soil and the advantages of hard-setting new materials, which will provide a new idea for soil improvement of the phyllite soil in the future.

Assessment of Runoff Control Effect with Improved Stepped Bioretention System (ISBS) under Various Rainwater Conditions

Stepped bioretention systems have been increasingly used for rainwater treatment in hillside areas. However, the depth of aquifer and soil permeability coefficient limit the treatment effect of runoff rainwater, resulting in a large amount of overflow water, particularly during extreme rainfall events. Here, in contrast to the ordinary stepped bioretention system (OSBS), an improved stepped bioretention system (ISBS) was developed by changing the overflow channel and the inflow and overflow were analyzed under various rainwater conditions. ISBS has high stability and the ability to control runoff rainwater. The runoff rainwater volume reduction rate reached 51.5–100% and the removal rate of suspended solid, chemical oxygen demand, total phosphorus and total nitrogen were 31.2–47.9%, 27.1–51.7%, 26.5–59.0% and 26.7–46.9%, respectively. According to the working principle of the continuous stirred tank reactor (CSTR), the permeable water concentration of other rainfall events can be predicted by using the parameters obtained from extreme rainfall events. In general, ISBS is a very promising runoff rainwater treatment technology, which can reduce the overflow quantity and recharge groundwater under various rainwater conditions.

One−Dimensional Seepage of Unsaturated Soil Based on Soil−Water Characteristic Curve

The uneven pore water distribution in unsaturated soil will cause water movement, change the hydraulic and mechanical characteristics of soil, and then cause soil damage. Therefore, it is important to study the hydraulic characteristics of unsaturated soil. In this paper, the law of conservation of mass and Darcy’s law were used to analyze the unit soil after seepage to obtain a continuous equation. Combined with the soil-water characteristic curve (SWCC), the effect of matric suction and permeability coefficient of unsaturated soil on infiltration rate is substituted into the equation. Through the analysis of pore water stress of the unit soil, the function of the unsaturated permeability coefficient with the effective saturation degree is obtained, and the theoretical formula of the one-dimensional infiltration rate of unsaturated soil is derived. Compared with other models, this formula has fewer parameters and is easy to use.

Coupling effect of roughness and normal pressure on mechanical characteristics and failure mode of deep-sea sediment interface

Revealing the failure mechanism at the soil–structure interface is an important prerequisite for foundations bearing capacity analysis. In deep-sea structures, due to the special sedimentary conditions and extremely low permeability coefficient of marine soil, obviously, the undrained behavior at the interface is becoming more complex and needs due attention. The objective of this study is to investigate the coupling effects of roughness and normal pressure on the interface mechanical characteristics and failure mode from the perspective of the pore pressure index through improved interface triaxial apparatus. The obtained results revealed that increased surface roughness makes it difficult for the soil particles in the grooves to climb along the structure surface and consequently the failure surface shifts from the interface to the soil. The confining pressure strongly influences the failure mode and critical roughness; Based on the response of two factors to the interface, a new piecewise Mohr-Coulomb failure criterion is established to reveal the real interface mechanical parameters, accordingly two new concepts are proposed and analyzed: transition roughness and critical normal stress; Furthermore, the relationship between the critical roughness and confining pressure is determined by the interface shear resistance equation considering the coupling effect; Finally, the interface failure mechanism and failure modes related to the confining pressure and surface roughness are revealed and distinguished. The dominant effect of effective interface friction parameters on the failure modes is evaluated for various surface roughness ranges.

Research on Leakage Mechanism of Underwater Shield Tunnels with Different Soil Layers during Operation Period

Different soil layer properties have great influence on tunnel leakage. In this paper, the finite element software is used to analyze the homogeneous leakage model of different soil layers and different degrees of lining deterioration. The working conditions of different soil layer properties and different degrees of lining deterioration are established by means of soil layer permeability coefficient and lining permeability coefficient, and the law of tunnel leakage under each working condition is analyzed. This paper innovatively explores the relationship between the severity of tunnel seepage caused by different lining deterioration and the soil layer properties of the tunnel. Finally, by comparing the field survey data of Dinghuaimen with the leakage law and mechanism summarized by the model, the reliability and feasibility of the model method to explore the leakage mechanism are verified. The model test results are consistent with the project survey data. In this paper, the seepage law and mechanism of underwater shield tunnel are explored and the result shows: (1) The leakage laws and stress distribution laws of a single homogeneous soil layer with different strata properties are similar. The flow velocity in the lower half of the tunnel lining is greater than the upper half, and the maximum velocity occurs at the arch foot; the velocity inside the lining is much smaller than that inside the soil layer. The maximum absolute value of the axial stress of the lining occurs at the arch waist on the left and right sides, and the minimum values of the axial stress of absolute values all occur at the dome. (2) The leakage of underwater tunnels is related to the properties of soil layers. The larger the soil permeability coefficient is, the more serious the deterioration of the tunnel lining will be, and the more serious the tunnel leakage will be. (3) The leakage of complex strata follows the law of leakage in a single homogeneous stratum. The leakage of the tunnel is the most serious in the fine sand layer with the largest permeability coefficient. Moreover, when the seepage phenomenon occurs, the water flow tends to seep along the fine sand layer to the tunnel.

Parameter identification of unsaturated seepage model of core rockfill dams using principal component analysis and multi-objective optimization

The seepage behavior of core walls is an important aspect of safety monitoring of core rockfill dams. The permeability coefficient of unsaturated soil of the core wall is a nonlinear function not a constant. Since there are many seepage monitoring points in the core wall, parameter identification of unsaturated seepage model of soil core wall based on the data of these points is a high-dimensional multi-objective optimization problem. In this paper, a parameter identification method of unsaturated seepage in the core wall is proposed, in which an unsaturated seepage model, principal component analysis (PCA), and elitist non-dominated sorting genetic algorithm (NSGA-II) are combined. The seepage monitoring sequence of measuring points in saturated and unsaturated regions of the core wall is synthesized to a few comprehensive variables by PCA respectively. The NSGA- II is adopted to optimize the objective functions established by these comprehensive variables to obtain the Pareto-optimal solutions. The efficiency, accuracy, and robustness to the error of the proposed method have been confirmed in a fictitious dam and an actual dam. The predicted seepage pressure with the Brooks-Corey (BC) model is in best agreement with the measured data, and the simulated seepage field is more in line with the actual situation.

Parameter analysis of excavation face stability of shield tunnel under high water pressure seepage

When a river-crossing shield tunnel is excavated in saturated soft clay strata, the fluctuation of the water level, the tunnel buried depth, and the physical properties of soil have a significant influence on the tunnel face stability. In this study, based on the basic theory of fluid-solid coupling of the surrounding rock soil, the fluid-solid coupling calculation method and the stability criterion of the tunnel face were used. The failure modes, deformation characteristics, and fluid-solid coupling effect were systematically investigated under different water levels, buried depths, diameters, and soil permeability coefficients when the excavation face was unstable. The results show that with the changes of water level, buried depth, and tunnel diameter, the collapsed body presents a logarithmic spiral distribution as the underwater shield tunnel face is unstable. The limit support force of the excavation face increases linearly with the rise of the water level, and the seepage force greatly influences the limit support force. For the deep-buried shield tunnel, the limit support force and maximum horizontal displacement of the excavation face change slightly due to soil arch effect. The soil arch effect can be used as the deep- and shallow-buried boundary of an underwater shield tunnel. As for the underwater shield tunnels with different diameters, the instability of excavation face first occurs at the lower part of excavation face. The face stability of underwater small-diameter shield tunnel is better than that of large-diameter one. In addition, the soil permeability coefficient has a weak effect on the tunnel face stability.

A state parameter-based scaling law for centrifuge modelling

When centrifuge modelling is applied to a prototype with large geometries that the centrifugal acceleration (Ng) could not fully recover the overburden stress of the prototype in the model, the generalized scaling law proposed by Iai (i.e., Iai's GSL) is often a promising choice. However, the scaling factor of shear strain is always larger than unity in Iai's GSL, which leads to the fact that the strain of the model soil is always smaller than that of the prototype. To address such a problem in Iai's GSL, a state parameter-based centrifuge scaling law securing the same shear strain between the model and the prototype is proposed in this paper. The proposed scaling law controls the model and the prototype to have the same initial state parameter by adjusting the void ratio of the model. The corresponding depth variation of the initial void ratio of the model is derived theoretically. To simplify the procedure of controlling the continuous change of void ratio through the model depth, a simplified approach is adopted for model preparation. The resultant effects of the proposed scaling law on soil density and permeability coefficient for different types of soils are also discussed. Finally, three centrifuge model tests of a submerged gently sloping ground of Ottawa F-65 sand with the same target geometry, state parameter and input motion at prototype scale have been conducted to validate the proposed scaling law, where the dynamic response and liquefaction-induced deformations were carefully monitored and analyzed. The applicability of the proposed scaling law is well confirmed by the centrifuge model test results.

Novel Approach to Predicting Soil Permeability Coefficient Using Gaussian Process Regression

In the design stage of construction projects, determining the soil permeability coefficient is one of the most important steps in assessing groundwater, infiltration, runoff, and drainage. In this study, various kernel-function-based Gaussian process regression models were developed to estimate the soil permeability coefficient, based on six input parameters such as liquid limit, plastic limit, clay content, void ratio, natural water content, and specific density. In this study, a total of 84 soil samples data reported in the literature from the detailed design-stage investigations of the Da Nang–Quang Ngai national road project in Vietnam were used for developing and validating the models. The models’ performance was evaluated and compared using statistical error indicators such as root mean square error and mean absolute error, as well as the determination coefficient and correlation coefficient. The analysis of performance measures demonstrates that the Gaussian process regression model based on Pearson universal kernel achieved comparatively better and reliable results and, thus, should be encouraged in further research.

Investigation on Calculation Method of Permeability Coefficient in the Consolidation Process of Cohesive Soil

In order to study the permeability characteristics of cohesive soil in the consolidation process more accurately, in this work, the pores occupied by the combined water were defined as invalid pores, and the effective pores and ineffective pores were decoupled to study the relationship between effective pores and permeability coefficient. The widely used empirical formulas of the permeability coefficient were modified, and the empirical formulas of the permeability coefficient suitable for the consolidation process of cohesive soil were obtained. Combined with the e − lg σ relationships of normally consolidated soil, underconsolidated soil, and overconsolidated soil, the formulas of permeability coefficient, which considering the influence of initial consolidation state and consolidation stress, in the consolidation process of cohesive soil, were proposed. Finally, the rationality of the new formulas proposed in this paper was analyzed by indoor consolidation-permeability test and existing research. The results showed that the permeability coefficient of cohesive soil in the consolidation process predicted by the new formulas were more consistent with the measured average value. This study possesses practical engineering significance to solve the problem of foundation consolidation settlement.

Influence of Unsaturated Hydraulic Properties on Transient Seepage and Stability Analysis of an Earthen Dam

Traditionally, the seepage through embankments and other geotechnical structures is estimated using the hydraulic properties of saturated soil. In most cases, the soil is not fully saturated, and the use of saturated soil properties can lead to erroneous results. A reliable assessment of slope stability needs comprehensive characterization of both unsaturated and hydraulic properties of saturated soil. The permeability coefficient of unsaturated soil is usually estimated using existing permeability models derived from the soil water characteristic curve (SWCC) of soil. The performance of these prediction models has not been consistent in the past. A proper determination of unsaturated soil permeability properties will be needed for better stability designs and checks of earth structures. In this study, an experimental program is designed to evaluate the influence of matric suction, net confining stress, and wetting and drying cycles on the hydraulic conductivity of a clayey soil over a wide range of suction values. Modified suction-controlled triaxial equipment was used to apply and maintain suction and hydraulic head in a soil specimen to measure the coefficient of permeability for drying and wetting cycles. Additionally, a series of fully coupled hydromechanic numerical analyses was performed to examine the effect of hydraulic properties of unsaturated soil on pore water pressure response and safety factors of slope for transient seepage conditions during drawdown. The effects of stress-dependent hydraulic properties and hydraulic hysteresis on transient seepage were also investigated. The findings from this study highlight the role of hydraulic properties of partially saturated soil in seepage and slope stability analysis of earthen dams.

Estimating the permeability coefficient of soil using CART and GMDH approaches

Abstract Permeability coefficient of soil (k) is one of the most important parameters in groundwater studies. This study, two robust explicit data-driven methods, Including classification and regression trees (CART) and the group method of data handling (GMDH) were developed using the characteristics of soil, i.e., clay content (CC), water content (ω), liquid limit (LL), plastic limit (PL), specific density (γ), void ratio (e) to generate predictive equations for prediction of k. When compared to CART; mean absolute error (MAE) = 0.0051, root mean square error (RMSE) = 0.0088, scatter index (SI) = 64.00%, correlation coefficient (R) = 0.7841, index of agreement (IA) = 0.8830; the GMDH equation produced the lowest error values; MAE = 0.0044, RMSE = 0.0072, SI = 52.17%, R = 0.8493, Ia = 0.9184; in testing stage. Although, GMDH had better performance, however, CART and GMDH could be considered effective approaches for the prediction of k.

Effect of biochar on permeability of compacted soil and its microscopic mechanism

Biochar has attracted much attention in the field of geo-environmental engineering as a carbon-neutral alternative for soil amendment. In this study, the effects of biochar dosage, type, and particle size on the permeability and physical properties of compacted silty clay were investigated. And the prediction model of permeability coefficient of biochar-amended soil (BAS) was established. Based on the microscopy test results, the influence mechanism of biochar on the permeability of compacted soil was analyzed. Results revealed that adding different biochar types affected the consistency limits, specific gravity, and compaction curves of soil obviously. As the biochar content increased, the permeability coefficient of compacted BAS initially decreased before increasing. The permeability coefficient of compacted BAS with peanut-shell biochar was much higher than with other biochar types. Additionally, reducing the particle size of biochar can effectively decrease the permeability coefficient of BAS due to the pore-filling effect. Microscopy test results show that the permeability coefficient of BAS is affected by both the most probable pore size and the main-peak area of the pore-size distribution curve. Results suggest that controlling the biochar content at 5% and reducing the particle size of biochar are more beneficial to improve the impermeability of compacted BAS.

Prediction of Permeability Coefficient k in Sandy Soils Using ANN

The paper presents a method of application of an ANN (Artificial Neural Network) to predict the permeability coefficient k in sandy soils: FSa, MSa, CSa. To develop an ANN the results of permeability coefficients from pumping and consolidation tests were applied. The proposed ANN with an architecture 6-8-1 predicts the value of permeability coefficient k based on the following parameters: soil type, relative density ID, void ratio e and effective soil diameter d10. The mean relative error and single maximum value of the relative error for the proposed ANN are following: Mean RE = ±4%, Max RE = 7.59%. The use of the ANN to predict the soil permeability coefficient allows the reduction of the costs and time needed to conduct laboratory or field tests to determine this parameter.

Hybrid Model: Teaching Learning-Based Optimization of Artificial Neural Network (TLBO-ANN) for the Prediction of Soil Permeability Coefficient

The permeability coefficient (k-value) of the soil is an important parameter used in the civil engineering design of roads, tunnels, dams, and other structures. However, the determination of k-value by experimental methods in the laboratory or the field is still costly and time-consuming. Moreover, it requires special equipment and special care in the collection of soil samples for laboratory study. Therefore, in this study, we have proposed machine learning (ML) hybrid model: teaching learning-based optimization of artificial neural network (TLBO-ANN) to predict the k-value of soil based on limited parameters (natural water content, void ratio, specific gravity, liquid limit, plastic limit, and clay content) which can be determined easily in the laboratory. Test results of 84 soil samples obtained from the Da Nang-Quang Ngai expressway project in Vietnam are used in the model development. Statistical indicators such as correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are used to validate and evaluate the accuracy of the model. The results show that the TLBO-ANN model is an effective tool in predicting correctly the k-value (R = 0.905) of soil for the consideration in the design of structures founded on the soil.

Prediction of soil permeability coefficient using GEP approach

Prediction of soil permeability coefficient using GEP approach

Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm

The permeability coefficient of soils is an essential measure for designing geotechnical construction. The aim of this paper was to select a highest performance and reliable machine learning (ML) model to predict the permeability coefficient of soil and quantify the feature importance on the predicted value of the soil permeability coefficient with aided machine learning‐based SHapley Additive exPlanations (SHAP) and Partial Dependence Plot 1D (PDP 1D). To acquire this purpose, five single ML algorithms including K‐nearest neighbors (KNN), support vector machine (SVM), light gradient boosting machine (LightGBM), random forest (RF), and gradient boosting (GB) are used to build ML models for predicting the permeability coefficient of soils. Performance criteria for ML models include the coefficient of correlation R2, root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE). The best performance and reliable single ML model for predicting the permeability coefficient of soil for the testing dataset is the gradient boosting (GB) model, which has R2 = 0.971, RMSE = 0.199 × 10−11 m/s, MAE = 0.161 × 10−11 m/s, and MAPE = 0.185%. To identify and quantify the feature importance on the permeability coefficient of soil, sensitivity studies using permutation importance, SHapley Additive exPlanations (SHAP), and Partial Dependence Plot 1D (PDP 1D) are performed with the aided best performance and reliable ML model GB. Plasticity index, density > water content, liquid limit, and plastic limit > clay content > void ratio are the order effects on the predicted value of the permeability coefficient. The plasticity index and density of soil are the first priority soil properties to measure when assessing the permeability coefficient of soil.