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Due to its unique geotechnical properties, loess presents itself as a cost-effective and energy-efficient material for engineering construction, aiding in cost reduction and environmental sustainability. However, to meet engineering specifications, loess often requires enhancement. Evaluating its permeability properties holds significant importance for employing improved loess for construction materials in landfills and artificial water bodies. This study investigates the influence of dry densities, grain size characteristics, grain size distribution, and admixture contents and types on the permeability of improved loess, focusing on the Malan and Lishi loess. The falling head permeability test was conducted to analyze how each factor affects the permeability of the improved loess. The findings indicate that the permeability coefficient decreases with increased dry density and admixture content. Conversely, it demonstrates a linear increase with the average grain size (d50), restricted grain size (d60), and the product of the coefficient of uniformity and coefficient of curvature (Cu × Cc). The primary influencing factor is the type of admixture, followed by Cc and d60. Furthermore, this study developed a predictive model for permeability using a support vector machine (SVM), surpassing the predictive accuracy of linear regression and neural network models. The model provides a robust prediction for the permeability of superior loess material.

The permeability coefficient of landslide mass, a key parameter in the study of reservoir landslides, is commonly obtained through in situ and laboratory tests; however, the tests are costly and subject to high variability, leading to potential biases. In this paper, a new method was proposed to inversely estimate the permeability coefficient of landslide layers using monitoring data of groundwater level (GWL). First, the landslide transient seepage simulation was conducted to generate sample data for permeability coefficients and GWL during a reservoir operation cycle. Second, using GWL data as input and permeability coefficient data as output, the least-square support vector machine (LSSVM) was trained with two optimization algorithms, the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA), to construct the nonlinear mapping relationship between simulated GWL and permeability coefficients. Third, the accurate permeability coefficients for landslide seepage simulation were inverted or predicted based on the monitored GWL. Finally, using the inverted permeability coefficients for landslide seepage simulation, we compared simulation results with actual monitored GWL and achieved good consistency. In addition, this paper compared the inversion effects of three different algorithms: the standard LSSVM, PSO-LSSVM, and WOA-LSSVM. This study showed that these three algorithms had good nonlinear fitting effects in studying landslide seepage fields. Among them, using the inversion values from PSO-LSSVM for landslide seepage simulation resulted in the smallest relative error compared to actual monitoring data. Within a single reservoir operation cycle, the simulated water level changes were also largely consistent with the monitored water level changes. The results could provide a reference to determine landslide permeability coefficients and seepage.

Permeability characterized by permeability coefficient is one of the important engineering properties of clay, and its permeation mechanism depends on the permeation process of water in clay. To clarify the characteristics and influencing factors of the anisotropy of stress in red clay, indoor variable head permeability tests were conducted to obtain the permeability coefficients of undisturbed red clay in vertical and horizontal directions under different overlying loads. The research results indicate that under the same overburden load, the vertical permeability coefficient (kV) is greater than the horizontal permeability coefficient (kH), and on semi-logarithmic coordinates, both permeability coefficients exhibit a linear negative growth relationship with the overburden load. Moreover, with a gradual increase in the overburden load, the permeability coefficient ratio kV/kH shows a decreasing trend. When the overburden load does not exceed 150 kPa, the ratio of permeability coefficients (kV/kH) shows a linear decreasing trend, and when the overburden load exceeds 150 kPa, the rate of decrease gradually slows and eventually stabilizes. It is also found that the void ratio (e) is linearly related to lgkV and lgkH, and based on this, a prediction model for the anisotropy of stress in undisturbed red clay based on permeability coefficients is established. Under increasing osmotic pressure, the permeability coefficients in both directions exhibit linear growth. Essentially, it is the osmotic pressure that alters the stress pathways of red clay, and the smaller the overburden load, the greater the effect of osmotic pressure. With the increase in the overburden load, the anisotropy of stress gradually weakens.

Granite residual soil has distinctive engineering characteristics due to its unique properties, and the resulting slopes are less stable and less resistant to rain erosion. The granite residual soil was improved by the addition of 5%, 10%, 15% and 20% fly ash, and the effects of fly ash on the intensity index and penetration of granite residual soil were investigated by triaxial strength tests and permeability tests. In combination with scanning electron microscopy measurements, a study of the stability of fly ash-modified granite residual soil slopes by modeling rainfall using the finite element software ABAQUS revealed the following: (1) the permeability coefficients of the residual granitic soils decreased by one order of magnitude when fly ash was added; (2) the improvement in the triaxial strength index of the improved soil was most pronounced when the dosage of fly ash was 15%, so that a dosage of 15% was considered optimal; and (3) numerical simulations concluded that the stability of the slope formed by 15% fly ash-improved soil fill improved significantly relative to the original slope, with the coefficient of safety increasing from 1.06 to 1.42, and the resistance to water seepage also significantly improved.

The type of soil and its compactness significantly influence its permeability coefficient, which in turn affects the drainage difficulty of soil pore water and the distribution of the infiltration line. However, current tailings dam models typically consider only a single soil layer instead of taking into account the differences in soil types and compactness, resulting in a deviation between simulated results and actual conditions. To address this issue, this study proposes three models with a gradually increasing degree of layering refinement based on soil type and compactness. These models aim to simulate the variations in the infiltration line under three different strategies: constant head, rainfall, and drainage. The simulation results indicate that the average increase in the infiltration line of the three schemes after rainfall is 46.2%, 65.88%, 83.52%, respectively; the fitting percentages for each scheme of infiltration line after 720 days of drainage and the constant head stage are 72.38%, 88.27%, and 93.61%, respectively. It can be seen that the higher the refinement level of the layered model, the more sensitive it is to changes in the infiltration line. Furthermore, as the refinement level of the layered model increases, the simulation effect on the changes in the infiltration line improves, and the simulated results become more consistent with the actual situation. This finding provides a strategy and possibility for the study of the tailings dam’s infiltration lines, safety, and stability.

This study delves into the effects of sample height on consolidation behaviour, utilising the automatic air pressure consolidometer. Extensive tests were conducted on three varieties of dredged silt samples of varying heights from Qianwan, Shenzhen, China. The salient findings can be summarised as follows: (1) Compression curves for samples of different dimensions transitioned through three distinct phases: minimal load disturbance, elastic deformation, and plastic deformation. Notably, the void ratio during the latter two phases diminished as sample height increased. (2) A rising sample height corresponded to a reduced stable strain and compression index. Furthermore, the consolidation coefficient notably diminished with an escalation in the sample height, whereas the structural yield stress remained largely unaffected. (3) Given the disparate formation processes, stress histories, and material compositions between dredged and marine silts, the permeability coefficient of dredged silt was found to be superior to that of marine silt. Within the typical preloading pressure scope (50~300 kPa), the consolidation coefficient of dredged silt was lower compared to marine silt. However, as the consolidation pressure significantly surpassed this threshold, the coefficient disparity between the two silts narrowed.

In the construction of artificial islands in distant seas, calcareous sand has been widely used as a foundation filler due to its excellent mechanical properties and extensive availability in the marine environment. How to store more fresh water on the artificial islands by reducing its permeability is currently a great challenge. Microbial-induced carbonate precipitation (MICP) has always been considered as a great potential method to improve the cemented properties of calcareous sand, but the effect of grain gradation on the permeability of MICP-improved calcareous sand remains unclear. In this research, a self-made device was developed to conduct MICP grouting and permeability tests, where the permeability coefficient (k) under different grain gradations (curvature coefficient (Cc) and uniformity coefficient (Cu)) was measured. A CT scan was conducted to investigate the variation in the porosity (n) of sand samples before and after MICP treatment. The weighting method was adopted to measure the content of induced calcium carbonate (M). A scanning electron microscopy (SEM) technique was used to further study the micromechanism of the MICP treatment. Finally, the correlations between the k of MICP-treated sand and Cu, as well as Cc, were semiquantitively analyzed. The results show that the magnitude of M, k and n changes are closely related to Cc and Cu. The reduction amount of k and n increased with the rise in Cc and Cu, and the increased amount of M increased with the rise in Cc and Cu. The SEM results show that the particle surface became rough due to the coating effect of CaCO3 crystals, and the pore spaces were reduced because of the partially filling effect of the crystals, which was responsible for the decrease in permeability and porosity. Furthermore, k fitted well with Cu and Cc, respectively, and the fitting curve reveals that larger Cu (Cu ≥ 6.0) and smaller Cc (2.0 > Cc > 0.5) were more suitable for MICP treatments and lead to a large reduction in permeability. The above results indicate that the grain gradation of calcareous sand had a significant influence on its permeability improved by MICP.

The calcium leaching effect leads to a decrease in the impermeability of the impervious curtain. The inverse analysis strategy was introduced in this study because the calcium leaching parameters of the curtain are not easy to determine. An orthogonal design and the finite element method were used in the strategy. The time-series data of hydraulic head and leakage volume were applied to construct the objective function. The extreme learning machine (ELM) was proposed to build the reflection sets. Genetic algorithm (GA), simulated annealing (SA), sparrow search algorithm (SSA), and particle swarm optimization (PSO) were employed to accelerate the iterative search for the target parameters. The target parameters of the calcium leaching model were used for finite element verification by comparing the monitored and simulated values. The simulated values of hydraulic head and leakage by PSO show good agreement with measurements. The evolution of the curtain permeability coefficient in 100 years was analyzed. The results demonstrate the strategy’s feasibility in determining the curtain’s calcium leaching parameters and permeability coefficients.

Microbial-induced calcium carbonate precipitation (MICP) is a new soil remediation technology, which can improve the physical and mechanical properties of soil by transporting bacterial solution and cementation solution to loose soil and precipitating calcium carbonate precipitation between soil particles through microbial mineralization. Based on this technique, the effects of different fine particle content and pore ratio on the physical and chemical properties of silt after reinforcement were studied. The content of calcium carbonate, the ability of silt to fixed bacteria, unconfined compressive strength (UCS), permeability coefficient and microstructure of the samples were determined. The results showed the following: In the process of calcium carbonate precipitation induced by microorganisms, more than 50% bacterial suspension remained on the surface of silt particles and their pores. The higher the bacterial fixation rate of silt, the more CaCO3 was generated during the solidification process. The bacterial fixation rate and CaCO3 content both decreased with the increase in the pore ratio and increased with the increase in the fine particle content. XRD and SEM images show that the calcium carbonate is mainly composed of spherical vaterite and acicular cluster aragonite. There is an obvious correlation between unconfined compressive strength and CaCO3 content of silt. When CaCO3 content accumulates to a certain extent, its strength will be significantly improved. The unconfined compressive strength of silt A with pore ratio of 0.75 and fine particle content of 75% is 2.22 MPa when the single injection amount of cementing fluid is 300 mL. The permeability coefficient of cured silt can be reduced by 1 to 4 orders of magnitude compared with that of untreated silt. In particular, the permeability of MICP-treated silt A is almost impermeable.

Affected by the coupling of excavation disturbance and ground stress, the heterogeneity of surrounding rock is very common. Presently, treating the permeability coefficient as a fixed value will reduce the prediction accuracy of the water inflow and the external water pressure of the structure, leading to distortion of the prediction results. Aiming at this problem, this paper calculates and analyzes tunnel water inflow when considering the heterogeneity of permeability coefficient of surrounding rock using a theoretical analysis method, and compares with field data, and verifies the rationality of the formula. The research shows that, when the influence of excavation disturbance and ground stress on the permeability coefficient of surrounding rock is ignored, the calculated value of the external water force of the tunnel structure is too small, and the durability and stability of the tunnel are reduced, which is detrimental to the safety of the structure. Considering the heterogeneity of surrounding rock, the calculation error of water inflow can be reduced from 27.3% to 13.2%, which improves the accuracy of water inflow prediction to a certain extent.

Landslides, which often occur on natural slopes of mountainous areas and artificial slopes around urban areas during summer in South Korea, are mostly caused by localized heavy rainfalls and typhoons. A survey was conducted, and the characteristics of landslide occurrences in different geological conditions—in this case, granite soils in Sangju area and gneiss soils in Yangu area—were analyzed. Soil characteristics in the landslide and non-landslide areas and the surroundings of each geological condition were also evaluated. Triggering factors, namely permeability coefficients (k), shear strength with cohesion (c), and internal friction angle (φ) of soils that are closely linked to landslides around weathered soil layers were extracted based on the examined characteristics and a statistics method. The study used regression analysis to formulate equations to estimate the permeability coefficients and shear strength. Ultimately, the permeability coefficients showed significant results in terms of void ratio (e), the effective size of grains (D10), and uniformity coefficient (cu), while shear strength correlated with the proportion of fine-grained soil (Fines), uniformity coefficient (cu), degree of saturation (S), dry weight density (rd), and void ratio (e).

Aggregates are a significant component of pervious concrete. Pervious concrete using iron tailings as coarse aggregates was prepared to study the feasibility of this approach. A mix design procedure was also used to design pervious concrete based on different target porosities. The effective porosity, measured porosity, dry density, compressive strength, and permeability coefficient of pervious concrete were studied. The results show that the mix design procedure based on a target porosity is relatively reasonable for designing iron tailing-based pervious concrete. The 28 d compressive strength of the pervious concrete decreased from 42 to 11 MPa as the effective porosity increased from 5.2% to 27.2%. The effective porosity of the equilibrium point of the compressive strength and permeability coefficient of pervious concrete was approximately 16%, where the compressive strength was 21.5 MPa, and the water permeability was 3.2 mm/s. The permeability coefficient of pervious concrete can be predicted as an exponential function of the effective porosity, and the compressive strength of pervious concrete can be predicted as a logarithmic function of the effective porosity.

Nuclear magnetic resonance (NMR) technology has been widely used for predicting permeability coefficients of porous medium, such as shales, sandstones, and coals. However, there have been limited studies on the prediction model of clay-quartz mixtures based on NMR technology. In this study, evaporation tests at 40 °C and NMR tests were simultaneously performed on eight clay-quartz mixtures with different mineral compositions. The results show that during the evaporation process, the decay rate of T2 total signal amplitudes was constant at first, and then decreased to 0 after a period of time. Based on the decay rate, the evaporation process was divided into two stages: the constant rate stage and the falling rate stage. Based on the two stages, the T2 cut-offs of eight mixtures were determined. The water in the mixture was divided into two parts by the T2 cut-off: the free water and the bound water. The prediction model of permeability coefficients of clay-quartz mixtures was established based on the Timur-Coates model. In order to simplify the process of predicting the permeability coefficient, fractal analysis was used to develop the relationship between the T2 cut-off and fractal dimension of the T2 spectrum of saturated mixture. A simplified method for predicting permeability coefficients of clay-quartz mixtures based on NMR technology without centrifugal and evaporation experiments was also proposed.