Research on conductive models of damaged soil that consider the effect of microcrack expansion (the degree of saturation and suction) is weak. By assuming an equivalent conductive path a unit series-parallel conductive model of damaged soil under environmental loads was proposed. This model shows the change in soil porosity and fractal dimension. To verify that, the soil was damaged by rainfall cycles (simulated natural drying and rainfall). Electrical measurements and X-ray microscopy tests were performed to obtain the damaged soil resistivity, porosity, and fractal dimension variation. The resistivity was calculated based on the conductive model, and the error was approximately 7.9% compared with that of the test. In addition, the soil damage variable related to soil porosity and fractal dimension was introduced, and it exhibited a logarithmic relationship with soil resistivity. Variations in soil damage during the rainfall cycles were observed. In the top layer, the soil porosity increased and the fractal dimension decreased owing to microcrack expansion, resulting in an increase in soil damage. In contrast, in the bottom layer, the soil porosity decreased and the fractal dimension increased, resulting in a decrease in soil damage due to particle migration from the top area and pore fill.

Characterisation of freezing conditions (i.e. temperature and unfrozen water content) and stress states (e.g. stress level and specific volume) is critical to evaluate the thermo-hydro-mechanical properties of frozen soils. This study aims to utilise frozen soils' electrical responses to characterise mechanical properties and interpret the associated frost heave phenomenon and compression characteristics. Frozen soils were prepared by freezing sand and bentonite at various temperatures (i.e. -5, -10, -20 degrees C), in which the electrical conductivity and frost heave were monitored. A modified oedometer was thereafter utilised to conduct compression tests on frozen soils. Results showed that electrical responses were highly sensitive to soil temperature variations during freezing: electrical conductivity decreasing by 2-5 orders of magnitude in response to the temperature drop of 15-40 degrees C. Soil freezing characteristic curves were associated with freezing point depression phenomena, as reflected in correlations between electrical conductivity and unfrozen water content. Frozen soils exhibited sensitive electrical responses to stress changes along the loading path (e.g. electrical conductivity increased by 2-4 orders of magnitude due to stress increase from 1 to 2500 kPa); while no significant stress-dependent electrical responses were observed during unloading, likely due to the loss of electric contacts. Moreover, the preconsolidation pressure of the frozen bentonite increased by 10-60 times compared to the unfrozen bentonite because of the ice invasion mechanism. This study investigates thermomechanical couplings in frozen soils and highlights the potential applicability of electrical conductivity for monitoring thermal and stress states of frozen soils in cold regions.

Monitoring groundwater levels and soil moisture content (SMC) is crucial for managing water resources and assessing risks, but can be challenging, especially over large acreages. Recent advances in geophysical methods provide new opportunities for accurate groundwater assessment. Seismic wave speed data, sensitive to changes in pore water pressure, can be used in a passive monitoring approach, while electrical conductivity data can be used for monitoring SMC. Combining seismic and electromagnetic induction (EMI)-based monitoring techniques enhances our understanding of groundwater dynamics. Seismic methods enable wide spatial coverage with moderate depth resolution, whereas EMI offers high-resolution, rapid data acquisition, particularly effective for shallow subsurface monitoring. Integrating these approaches can leverage the strengths of each, yielding comprehensive, high-resolution insights into dynamic subsurface hydrological processes. Integrating these approaches allows for improved groundwater monitoring, aiding in better understanding and managing droughts in regions like the Netherlands.

Fluid flow in fractures controls subsurface heat and mass transport, which is essential for developing enhanced geothermal systems and radioactive waste disposal. Fracture permeability is controlled by fracture microstructure (e.g. aperture, roughness, and tortuosity), but in situ values and their anisotropy have not yet been estimated. Recent advances in geophysical techniques allow the detection of changes in electrical conductivity due to changes in crustal stress and these techniques can be used to predict subsurface fluid flow. However, the paucity of data on fractured rocks hinders the quantitative interpretation of geophysical monitoring data in the field. Therefore, considering different shear displacements and chemical erosions, an investigation was conducted into the hydraulic-electric relationship as an elevated stress change in fractures. The simulation of fracture flows was achieved using the lattice Boltzmann method, while the electrical properties were calculated through the finite element method, based on synthetic faults incorporating elastic-plastic deformation. Numerical results show that the hydraulic and electrical properties depend on the rock's geometric properties (i.e. fracture length, roughness, and shear displacement). The permeability anisotropy in the direction parallel or perpendicular to the shear displacement is also notable in high stress conditions. Conversely, the permeability -conductivity (i.e., formation factor) relationship is unique under all conditions and follows a linear trend in logarithmic coordinates. However, both matrix porosity and fracture spacing alter this relationship. Both increase the slope of the linear trend, thereby changing the sensitivity of electrical observations to permeability changes. (c) 2024 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/).

The electrical conductivity of soil is closely associated with various physical properties of the soil, and accurately establishing the interrelationship between them has long been a critical challenge limiting its widespread application. Traditional approaches in geotechnical engineering have relied on specific conduction mechanisms and simplifying assumptions to construct theoretical models for electrical conductivity. This paper adopts a different approach by using machine learning methods to predict the electrical conductivity of clay materials. A reliable dataset was generated using the quartet structure generation set to create random clay microstructures and calculate their electrical conductivity. Based on this dataset, machine learning methods such as least squares support vector machine and backpropagation neural networks outperform theoretical models in terms of prediction accuracy and resistance to interference, with a coefficient of determination (R2) exceeding 0.995 when unaffected by disturbances. The computation of Shapley values for input features aids in explicating the machine learning model. The results reveal that saturation is a key feature in predicting electrical conductivity, while porosity and constrained diameter are relatively less important. Finally, an already trained model is applied to the one-dimensional electroosmosis-surcharge preloading consolidation theory. The results of the calculations demonstrate that neglecting changes in soil electrical conductivity during electroosmosis can lead to an overestimation of the absolute values of anode excess pore water pressure and soil settlement.

Temperature and unfrozen water content are important affecting parameters in soil freezing process. This study aims to explore correlation between electrical conductivity, unfrozen water content, and temperature for silty clay under various salt content conditions and propose new theoretical relationships to predict the changes of related parameters in the freezing process. Frequency domain reflection(FDR)sensors were employed to conduct electrical performance tests on frozen soil, elucidating the response of frozen soil's electrical conductivity to unfrozen water content and temperature. The conduction mechanism of frozen soil was analyzed using SternGouy electrical double-layer theory. The analysis showed a negative correlation between soil salt content and freezing temperature. Before freezing, salt content significantly affected the crystallization pattern of salt and volumetric water content. There exists a threshold value below which no salt crystallization occurs in soil, and volumetric water content remains relatively constant, while electrical conductivity slightly decreases with decreasing temperature. When salt content exceeds the threshold value, the starting temperature of salt crystallization was influenced by the salt content, and both volumetric water content and electrical conductivity changes significantly after salt phase transition point. After freezing, both unfrozen water content and electrical conductivity significantly decrease. The remaining moisture content in soil slightly decreases with an increase in salt content. Different relevant parameter models have been proposed to describe variations in unfrozen water content and electrical conductivity with temperature after soil phase transition point. The effectiveness of different parameter-related models was validated by comparing experimental data with calculated and fitted results under various conditions. The electrical conductivity of soils with varying salt contents depends on both salt concentration of pore solution and migration pathways of ions. The primary conduction pathways include pore conduction and surface conduction, with latter gradually becoming predominant below its freezing temperature. This study provides a scientific basis for revealing the mechanism and prevention measures of freezethaw damage in the construction of subway tunnels using the artificial ground freezing (AGF) technique.

Green natural rubber (NR) composites reinforced with synthetic graphite platelets, using alginate as a thickening and dispersing agent, were successfully developed to improve mechanical properties, chemical resistance, and electrical conductivity. The fabrication was performed using a latex aqueous microdispersion process. The research demonstrated the effective incorporation of graphite platelets into the NR matrix up to 60 parts per hundred rubbers (phr) without causing agglomeration or phase separation. Graphite incorporation significantly improved the mechanical strength of the composite films. NR with 60 phr of graphite exhibited the highest Young's modulus of 12.3 MPa, roughly 100 times that of the neat NR film. The reinforcement also strongly improved the hydrophilicity of the composite films, resulting in a higher initial water absorption rate compared to the neat NR film. Moreover, the incorporation of graphite significantly improved the chemical resistance of the composite films against nonpolar solvents, such as toluene. The composite films exhibited biodegradability at about 21% to 30% after 90 days in soil. The electrical conductivity of the composite films was considerably enhanced up to 2.18 x 10-4 S/cm at a graphite loading of 60 phr. According to the improved properties, the developed composites have potential applications in electronic substrates.

Salt damage caused by the complex interaction between water and salt in the heritages is the main factor that deteriorates the materials and destroys the historical information of the relics. The influence of environmental conditions, especially humidity, on salt damage of heritages has been emphasized by many researches. In this study, the water-salt migration characteristics in soil columns under different humidity were studied by laboratory tests. First, water vapor adsorption test was carried out to investigate the soil samples adsorption capability in 6 relative humidity conditions (RH11%, RH23%, RH43%, RH60%, RH75%). There is a linear relation between relative humidity and water vapor absorbed by soil, and the water vapor adsorption curves of samples can be well described by first-order exponential attenuation equation. Second, the water content and conductivity distribution within samples (hygroscopic and non-hygroscopic samples respectively) were investigated after capillary migration tests using 4 types of saline solutions (0.2 mol/L NaCl, 0.2 mol/L Na2SO4, 0.2 mol/L NaCl Na2SO4 mixed solution and distilled water). Results show that high conductivity appears on the top of most samples, and the values have a correlation with type of capillary migration fluid: NaCl > Na2SO4 > NaCl-Na2SO4 > H2O. In addition, the distribution of water content and conductivity becomes complicated under different relative humidity conditions.