This study investigates the impact of biopolymer treatment on the filtration of small sand particles (base sand) through the soil medium with relatively high particle sizes (filter sand) through laboratory experiments. The filter sand treated with five types of biopolymers (xanthan gum, guar gum, agar gum, chitosan, and zein) and four biopolymer concentrations (0.1%, 0.3%, 0.5%, and 1%) was prepared to investigate the best-performing biopolymer and optimal treatment concentration in mitigating filtration of base sand particles. It was found that the filter sand without biopolymer treatment showed a fraction of filtration = 7.83% of the base sand during the injection. In contrast, substantial mitigation of filtration was observed after biopolymer treatment for all biopolymer types and treated concentrations (fraction of filtration < 3% for all experimental conditions). Among five biopolymer types, agar gum showed the highest treatment efficiency and the mitigation of base sand loss. In addition, the similar mass fraction of filtrated base sand particles at biopolymer concentration > 0.1% observed in this study demonstrated that low treated biopolymer concentration can provide substantial reduction of base-filter incompatibility. The results indicate the potential of biopolymer-treated filter sand to improve base-filter compatibility under the laboratory conditions

Suffusion is the loss of relatively small particles from the soil matrix due to high hydrodynamic forces acting on them. This study investigates critical hydraulic gradient and hydraulic-induced suffusion of sand–clay mixtures as a function of clay type, the size ratio between sand and clay, and ionic concentration using a two-dimensional flow cell in the laboratory. The breakthrough curves, particle size distribution (PSD) of filtrated clay, flow rate, and mass of filtrated clay at the top, middle, and bottom outlets of the flow cell were measured as the hydraulic gradient increased. It was found that the critical hydraulic gradient of sand–clay mixtures is a function of ionic concentration, clay type, and size ratio. In addition, the order of critical hydraulic gradient and the mass of filtrated clay during the injection implies that the earlier initiation of suffusion does not lead to more significant suffusion. Furthermore, the flow rate during the injection indicates that the flow rate can be a good indicator of assessing critical hydraulic gradient at low ionic concentrations. Overall, the results shown in this study suggest the need for coupling the interaction energy between sand and clay and hydrodynamic forces in assessing the susceptibility of suffusion for clay-containing soils.

The application of biopolymers as a soil binder has been investigated for many geotechnical applications. This study investigates the chance of mitigating the suffusion of clay particles through biopolymer treatment. Five biopolymers (Xanthan gum, Agar gum, Gellan gum, Guar gum, and Chitosan) were selected to treat the sand-clay mixtures to assess the mitigation of suffusion as a function of biopolymer type and concentration (0.005 - 0.1%) through laboratory flow cell experiments. In addition, the critical hydraulic gradient and viscosity of biopolymer solutions were also evaluated to assess the underlying mechanisms of clay transportation for biopolymer-treated sand-clay mixtures. It was found that guar gum is the most effective biopolymer type in mitigating suffusion of sand-clay mixtures among five biopolymers. In addition, biopolymer treatment was not beneficial in mitigating suffusion under relatively low flow rates because of the higher viscosity of the biopolymer solution than that of water. The underlying bonding mechanisms of five biopolymers with soils for explaining experimental observations were also discussed.

Permittivity can be one of the non-destructive methods to monitor many properties of soils. The objective of this study was to provide a comprehensive understanding of the permittivity of clay minerals through the measurement of permittivity and electrical conductivity as a function of water content, ionic concentration and clay mineralogy. It was found that swelling clay shows a wide variation in real and imaginary permittivity as a function of water content at low ionic concentration. In addition, the variation of permittivity was a strong function of swelling potential where Ca-montmorillonite showed a lower variation of permittivity than Na-montmorillonite. A linear relationship between the slope of real permittivity plotted against porosity and ionic concentration was found, which implies the need to incorporate ionic concentration when estimating porosity from the real permittivity of clay minerals. Overall, the findings and regression models shown in this study suggest that permittivity can be a non-destructive property to estimate the porosity and ionic concentration of clay minerals for monitoring contaminant transport through those clay minerals. The interaction between clay and water molecules at a wide range of water content and ionic concentration is also discussed.

The stabilization of the tunnel face in slurry shield tunnel boring machines (TBMs) is significantly influenced by the mechanisms of pressurized slurry penetration. This study employed infiltration column tests and modified fluid loss tests to investigate the characteristics of slurry penetration and filter cake formation under varying slurry concentrations and pressure levels. The transition point between two consecutive slurry penetration mechanisms was estimated by applying the blocking filtration laws and compared with predictions based on the Peclet number. The slurry permeability of sand and the infiltration distance during the slurry penetration stage were evaluated, both of which increased with higher pressure and lower slurry concentration. The hydraulic conductivities of the infiltration zone and the filter cake were estimated using the filtration equation and validated against experimental measurements. Additionally, the hydraulic conductivities of the filter cake obtained from the infiltration column tests were compared with those derived from the modified fluid loss tests. The results indicated that increased pressure and slurry concentration reduced the hydraulic conductivities of both the filter cake and the infiltration zone. Overall, the findings confirm that the blocking filtration laws provide a reliable framework, consistent with previously proposed methods for identifying transitions in pressurized slurry penetration mechanisms. Moreover, the filtration equation proved effective in evaluating the hydraulic conductivities of both the infiltration zone and the filter cake.

Suffusion refers to the loss of fine particles within the soil matrix without any associated volume change, induced by hydrodynamic forces. This study investigated the suffusion of sand-clay mixtures through one-dimensional soil column experiments under a stepwise increase in hydraulic gradient (i), aiming to evaluate the critical hydraulic gradient (icrit) as a function of the size ratio between sand and clay, clay type, and ionic concentration. It was found that icritwas less than 0.1 for all sand-clay mixtures examined in this study. In addition, the lower peak concentrations of filtrated clay observed in sand-illite mixtures, compared to those of sand-kaolinite mixtures at the same level of i, suggest that illite particles are more susceptible to suffusion. Overall, the observed breakthrough curves, mass fraction of filtrated clay, volume of outflow, and total injection time presented in this study highlight the importance of considering clay type, sand-to-clay size ratio, and ionic concentration when assessing the suffusion behavior of clay-containing soils under a stepwise increase in hydraulic gradient. (c) 2026 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This article proposes a real-time errorcompensated multisensor acquisition system for a self-weight multiphysics cone penetration apparatus that performs marine geotechnical investigation. Conventional methods such as standard penetration test (SPT) and cone penetration test (CPT) provide reliable, high-resolution data but require dedicated offshore vessels, which are expensive to operate. To address these limitations, the apparatus with the proposed acquisition system has been developed for a lightweight and cost-effective solution. The proposed acquisition system drives hydro-compensated dual pressure transducers, strain gauges with Wheatstone bridges, and an inertial measurement unit (IMU) to obtain accurate geotechnical parameters as well as determine soil strength and stiffness properties during dynamic penetration. Additionally, the acquisition system uses an RS-485 communication protocol to transmit data over long distances up to 1.2 km at a data rate up to 100 kb/s. A 10.7 V lithium-ion (Li-ion) battery powers the proposed system, generating supply voltages of 9, 5, and 2 V through onboard voltage regulators to drive analog and digital subsystems. The proposed apparatus was verified to acquire reliable geotechnical parameters through field tests, providing a viable solution for offshore wind power development and submarine cable installations.

This study explores the potential of integrating bender element signals with a convolutional neural network (CNN) to predict the particle size distribution of relatively uniform sand. A one-dimensional CNN analyzed time-series signals from bender elements across four sand types with particle sizes ranging from 0.5 to approximately 7 mm, under vertical stresses of 10, 50, and 150 kPa in three different cutoff frequencies (10, 50, and 100 kHz). The CNN architecture included convolutional layers augmented with batch normalization and ReLU activation functions, optimized through Bayesian techniques to enhance prediction accuracy. Experimental results demonstrated that higher stresses increased resonant frequencies and reduced arrival times of shear waves, with minor dependencies on soil type. Nevertheless, the developed CNN model well classified the four sand types at a given vertical stress and cutoff frequency, implying that the unique pattern of each sand type can be satisfactorily captured by the CNN algorithm. Overall, the framework shown in this study demonstrates that the bender element (or pattern of receiving shear wave signals) with the CNN model can be used in monitoring real-time variation of sand particle size.

Suffusion is the process defined as the migration of relatively small soil particles through the pores of a soil matrix composed of relatively large particles, driven by substantial hydrodynamic forces and weak attraction energies. This study investigates the influence of flow direction (upward and downward) on suffusion induced by interaction energies in sand-clay mixtures under both saturated and unsaturated conditions. The impact of clay mineralogy (kaolinite, illite, and montmorillonite), sand-grain size, and ionic concentration (IC) gradient were discussed based on the observed breakthrough curves (BTCs) and relative saturation rate (Sr) during injection (particularly for unsaturated conditions). Under saturated conditions, higher susceptibility to suffusion was observed in sand-kaolinite and sand-illite mixtures under downward flow compared to upward flow, whereas the suffusion of montmorillonite was more significant under upward flow than under downward flow. In contrast, for unsaturated conditions, more substantial suffusion of kaolinite and illite particles occurred under upward flow compared to downward flow, whereas the opposite trend was observed in sand-montmorillonite mixtures. In addition, the impact of sand-grain size (or the size ratio between sand and clay) on the suffusion of kaolinite and illite under unsaturated conditions suggests a reduced size ratio that leads to relatively significant suffusion under downward flow compared to upward flow. The findings presented in this study contribute to a comprehensive understanding of the influence of flow direction on suffusion in sand-clay mixtures under both saturated and unsaturated conditions.

The presence of microplastics in aquatic environments threatens the ecological system and human health. This study investigates the transport and retention of polystyrene microplastics (PSMPs) in clean sand, and hematite-, goethite-, and magnetite-coated iron oxide - sands as a function of size ratio and ionic strength. The breakthrough curves (BTCs), retention profiles, and hydraulic pressure were measured through soil-column experiments, and the retention of PSMPs was assessed from the observed BTCs, RPs and first-order attachment coefficients. In addition, the maximum attachment capacity was evaluated to assess the long-term retention of PSMPs. Experimental data showed that the retention of PSMPs increased in the order of goethite-, hematite-, and magnetite-coated sands in all size ratios, which is consistent with the order of attraction energy calculated by extended Derjaguin-Landau-Verwey-Overbeek theory. The findings demonstrated the feasibility of mitigating the transport of microplastic particles using naturally abundant iron-rich soils.

Predicting the properties of deep-sea sediments offers critical insights into past oceanic conditions, including sediment composition, stratigraphy, and geochemical signals. However, accurate prediction is hindered by the high spatial variability of these sediments. This study presents a data-driven machine learning framework to predict five key sediment properties. Five prediction scenarios were developed with tailored preprocessing and hyperparameter tuning, and Shapley additive explanations were employed to assess feature importance and the relationships between depth and sediment properties. Among the five tested algorithms, the extreme gradient boosting (XGBoost) model achieved the highest predictive performance. Depth and compressional wave velocity emerged as the most and second most influential features for estimating porosity, grain density, calcite content, and thermal conductivity. The depth-dependent predictions with quantified uncertainties generated by the XGBoost model demonstrate that the proposed framework provides a robust approach for predicting deep-sea sediment properties.

The estimation of the cementation exponent (m) in Archie's equation, which is pivotal for interpreting the electrical resistivity of soils and rocks, could be significantly enhanced by correlating it with particle shape characteristics. This study proposes a novel approach in which Archie’s m-exponent for sand is estimated based on quantifiable particle shape parameters, including sphericity, convexity, elongation, slenderness, and roundness. The horizontal and vertical electrical resistivities of eight granular materials with varying particle shapes were measured. Correlation matrix scatter plot and multiple linear regression analyses were conducted to establish a quantitative relationship between Archie's m-exponents, electrical anisotropy, and particle shape parameters. The results indicate that all the investigated shape parameters exhibited strong correlations with m-exponents and electrical anisotropy. However, multiple linear regression analysis revealed that roundness (RD) is the most influential shape parameter, likely due to multicollinearity among the other shape parameters. Notably, m-exponents in both the vertical and horizontal directions were found to decrease linearly with increasing RD, as RD effectively captured the tortuosity of the electrical flow paths at a given porosity. These findings are supported by data from previous studies, further validating the observed relationship between RD and electrical properties.

Nonionic polyacrylamide (NPAM) is a water-soluble flocculant frequently used to immobilize toxic contaminants and for contaminant treatment. This study examines the influence of NPAM concentration (0-10 mg/L), cationic valence (NaCl or CaCl2 solution), and clay mineralogy (kaolinitic and illitic clay) on the flocculation and postsettling behavior under water content (w) = 500-4000 %, using sedimentation and rheology experiments. The significant increase in settling velocity by NPAM treatment was observed, with a maximum of 92 % reduction in settling velocity. In addition, kaolinitic clay formed larger and faster-settling flocs than illitic clay, and CaCl2 solution showed a stronger shear-thinning response than NaCl solution. The zero shear viscosity of NPAM-treated kaolinitic clay increased approximately 3-fold compared to untreated conditions, indicating strong intra-floc bonding of NPAM-treated kaolinitic clay. The high separation distance (up to 2.2 mu m for kaolinitic clay) of stacked clay flocs at high NPAM concentration suggests that NPAM concentrations below 5 mg/L can be recommended for obtaining mechanical stability of settled clay after settling. Overall, these findings provide a comprehensive understanding of NPAM-clay interactions at varied cationic valence, clay type, and NPAM concentration under saline conditions.

Dispersion plays a critical role in predicting solute transport through unsaturated soils. Therefore, this study comprehensively investigated the unsaturated longitudinal dispersivity of sand-clay mixtures using laboratory soil-column experiments. The effects of clay content, average degree of saturation, flow path length, and swelling potential on the unsaturated longitudinal dispersivity were examined. The longitudinal dispersivity was evaluated based on the observed breakthrough curves using the advection-dispersion equation. It was found that an increase in illite content, initial degree of saturation, flow path length, and swelling potential led to an increase in longitudinal dispersivity. In addition, the longitudinal dispersivity under saturated conditions was lower than when the initial average degree of saturation was 80 % whereas an increase in unsaturated longitudinal dispersivity as the initial degree of saturation increased from 20 to 80 % was observed. This observation led to a bilinear trend of longitudinal dispersivity as a function of the initial degree of saturation in sand-clay mixtures. The trend in the longitudinal dispersivity of sand-clay mixtures observed in this study differs from that reported in the literature for sand, suggesting the need for incorporating clay content, swelling potential, and initial degree of saturation when predicting the unsaturated longitudinal dispersivity of clay-containing soils.

The unsaturated behavior of permeable reactive barriers (PRB) is a critical component in predicting the removal efficiency through the adsorption of contaminants. This study investigates the framework to estimate the soil water characteristic curve (SWCC) and hydraulic conductivity function (HCF) for iron oxide-coated sand (IOCS) and zeolite, which are common materials used in PRBs. A multistep outflow (MSO) experiment was performed and the results of the MSO experiment were used to optimize associated parameters in Kosugi's SWCC and HCF. In addition, three scenarios of optimization analysis were investigated to evaluate the best-fitting model for estimating SWCC and HCF. The low root mean square error (RMSE) of fitted parameters indicates the Kosugi model well described the observed suction profiles in MSO experiments. In addition, the lowest RMSE and coefficient of variation suggested the inclusion of the additional parameter β provided the best estimation of the three materials (clean sand, IOCS, and zeolite). The physically reasonable estimation of SWCC and HCF of the three materials from the optimized parameters suggests the proposed framework is a reasonable model for the unsaturated behavior of PRBs.

Investigating the sedimentation of clay in saline water was extensively studied because of its wide applications in engineering. This study investigated the impact of cation valence, ionic concentration, and water content on sedimentation behavior of kaolinitic and illitic clays through batch sedimentation tests for the comprehensive understanding of clay particle association and elapsed time for the transition of settling regimes from initial hindered settling to zone settling. The quantitative representation of observed settling curves was achieved using four fitted parameters in batch sedimentation model, which represented the shape of settling curves and the boundary of the initial hindered, zone, and consolidation settling regimes. In addition, the obtained settling velocity from the settling curves provided the fraction of clay particles and the size of clay flocs. The observed settling curves, trends of fitted parameters, and the estimated size of clay flocs shown in this study implied that the type of clay particle association (face-to-face aggregation or edge-to-face flocculation), settling velocity, final interface height, and boundary between initial hindered and zone settling are function of clay mineralogy, water content, cation valence, and ionic concentration.

In addressing the critical role of sand particle size in hydraulic property prediction and applications like groundwater management, this study introduces a novel method combining ultrasonic acoustic sensing and convolutional neural network (CNN) for sand particle size distribution (PSD) classification. Recognizing the limitations of traditional particle size measurements in capturing temporal and spatial changes, our framework proposes a continuous, non-destructive monitoring solution. Laboratory experiments to construct a diverse echo signal dataset reflecting median sand sizes yielded a CNN model with high accuracy for four sand types. This approach promises low-cost, efficient monitoring of sand deposits, showcasing potential for broader geotechnical applications.