Search Results (16)

To investigate the deformation characteristics of loess in the Yangling region of Shaanxi Province, China, under different wet-dense states, a fully automatic air pressure consolidation apparatus was used to conduct compression and collapsibility tests. The compression and collapsible deformation mechanisms were revealed from the evolution patterns of compression yield pressure, compression coefficient, and collapsible coefficient. The tests results indicate the following: (1) the greater the compaction degree and the smaller the initial water content, the smaller the amplitude of the compression curve change, the greater the compressive yield stress, and the smaller the compression coefficient; a compression curve model considering initial water content and compaction degree was constructed. (2) The collapsibility coefficient shows a trend of first increasing and then decreasing under low pressure compaction and high initial water content, while under high pressure compaction and low initial water content, it exhibits a continuous increase. The increase in compaction degree and initial water content will both lead to a decrease in the coefficient of collapse. The collapsibility coefficient exhibits a more pronounced response under high pressure compared to low pressure. Soil samples with low compaction and low initial water content demonstrate significantly greater collapsibility sensitivity. (3) A collapsible prediction model applicable to Yangling loess was established based on SPSS software, and the research findings can offer theoretical support for the rapid assessment of loess collapsibility in this region. Full article

Collapsibility is a fundamental geotechnical property of loess that critically affects its engineering behavior. In this study, a comprehensive dataset comprising 9041 experimental records on the physical properties and collapsibility of loess from the Xi’an region was compiled. Six parameters were selected as model inputs: sampling depth (H), water content (w), plastic limit (w_P), plasticity index (I_P), compression coefficient (a_1–2), and compression modulus (E_s). Based on these inputs, prediction models for the loess collapsibility coefficient (δ_s) were developed using Gaussian Process Regression (GPR), Gradient Boosting Machine (GBM), Support Vector Regression (SVR), Radial Basis Function Neural Network (RBFNN), Classification and Regression Tree (CART), and Feature Tokenizer Transformer (FT-Transformer). Among these, GPR demonstrated the best predictive performance, achieving the lowest error (RMSE = 9.88 × 10⁻³) and the highest accuracy (R² = 0.844). Additionally, the coverage proportion of the 95% confidence interval of the GPR predictions reached 0.949. SHapley Additive exPlanations (SHAP) analysis for GPR further revealed that the compression coefficient exerted the greatest influence on δ_s (0.0149), followed by compression modulus (0.0080), water content (0.0068), plasticity index (0.0061), sampling depth (0.0061), and plastic limit (0.0052). The GPR-based prediction model offers significantly higher predictive accuracy than empirical models. The developed models provide a robust technical framework for the rapid estimation of loess collapsibility in the Xi’an region. Full article

To overcome the limitations imposed by the anisotropy and heterogeneity of natural loess, this study establishes a novel quantitative macro–micro correlation framework for investigating the deformation mechanisms of artificial structural loess (ASL). ASL samples were prepared by mixing remolded loess with cement (0–4%) and NaCl (0–16%), followed by static compaction (95% degree) and 28-day curing (20 ± 2 °C, >90% RH) to replicate the structural properties of natural loess under controlled conditions. An integrated experimental methodology was employed, incorporating consolidation/collapsibility tests, particle size analysis, X-ray diffraction (XRD), and mercury intrusion porosimetry (MIP). A three-dimensional nonlinear model was proposed. The findings show that intergranular cementation, particle size distribution, and pore architecture are the main factors influencing loess’s compressibility and collapsibility. A critical transition from medium to low compressibility was observed at cement content ≥1% and moisture content ≤16%. A strong correlation (Pearson |r| > 0.96) was identified between the mesopore volume ratio and the collapsibility coefficient. The innovation of this study lies in the establishment of a three-dimensional nonlinear model that quantitatively correlates key microstructural parameters (fractal dimension value (D), clay mineral ratio (C), and large and medium porosity (n)) with macroscopic deformation indicators (porosity ratio (e) and collapsibility coefficient (δ_s)). The measured data and the model’s output agree quite well, with a determination coefficient (R²) of 0.893 for porosity and 0.746 for collapsibility, verifying the reliability of the model. This study provides a novel quantitative tool for loess deformation prediction, offering significant value for engineering settlement assessment in controlled cementation and moisture conditions, though its application to natural loess requires further validation. Full article

The water retention and permeability characteristics of loess are core factors governing geological disaster prevention and engineering stability in the loess regions of northwest China. This study focuses on Yangling loess, systematically conducting soil water characteristic curve (SWCC) measurements and saturated permeability tests under different initial compaction degrees and water contents using a pressure plate apparatus and a TST-55 permeameter. By combining fitting analyses of the Gardner, Fredlund–Xing, and Van Genuchten SWCC models, the study reveals the influence mechanism of initial conditions on the water retention properties of Yangling loess. Furthermore, the unsaturated hydraulic conductivity of loess was predicted using the Van Genuchten–Mualem model. Finally, a quantitative relationship model between hydraulic conductivity and multiple factors (initial compaction degree, water content, and matric suction) was constructed using the response surface methodology. The results indicate the following: (1) A higher initial compaction degree and water content lead to a higher air entry value of loess, resulting in stronger water retention capacity. Among the three models, the Van Genuchten model exhibits the optimal fitting effect for the SWCC of Yangling loess. Its parameter a (related to the air entry value) decreases significantly with increasing compaction degree, while parameter n (pore size distribution index) increases linearly. The SWCC model, considering compaction degree, established based on these findings, can accurately predict the water retention characteristics in the high suction range (0~1200 kPa). This model’s precision in the high-suction segment is particularly valuable, as it addresses a critical range for engineering applications where soil behavior transitions from near-saturated to highly unsaturated states. (2) When loess transitions from a saturated to an unsaturated state, the hydraulic conductivity decreases up to 10⁴ times. Both increased initial compaction degree and water content lead to a significant reduction in hydraulic conductivity. This drastic reduction highlights the sensitivity of loess permeability to saturation changes, which is attributed to the rapid reduction in interconnected pore channels as soil suction increases and pore spaces are filled or compressed under higher compaction. (3) The response surface prediction model quantitatively reveals the influence weights of various factors on hydraulic conductivity in the order of matric suction > initial compaction degree > initial water content. The model exhibits a high coefficient of determination (R² = 0.9861), enabling rapid and accurate prediction of the hydraulic conductivity of Yangling loess. This high precision confirms that the model effectively captures the complex interactions between the factors, providing a reliable tool for practical engineering calculations. This study provides a new model and experimental basis for the accurate prediction of unsaturated loess hydraulic properties. The proposed SWCC model, considering compaction degree and the response surface model for hydraulic conductivity, offers practical tools for engineers and researchers, facilitating more precise design and risk assessment in collapsible loess areas. Full article

The collapsibility of loess in the northwest region poses a significant threat to infrastructure stability. Current research predominantly separates macroscopic mechanical behaviour from mesoscopic structural characteristics, lacking a systematic methodology to quantify their interdependence. This study integrates consolidation tests, laser particle size analysis, mercury intrusion porosimetry (MIP) tests, and fractal theory to propose a multi-scale evaluation framework for assessing the structural potential of collapsible loess in strength, with on-site verification conducted. This framework quantitatively links grain size, pore potential, and connection potential to the collapsibility of loess. The experimental results indicate that loess’s high compressibility and collapsibility are primarily governed by grain size and pore potential. In contrast, the connection potential of soluble salts mitigates structural instability through ionic bonding. Field verification demonstrates a strong correlation between the three structural potentials and the subsidence coefficient (R² = 0.92, p < 0.01), validating the framework’s effectiveness in evaluating structural stability. A ternary evaluation system has been established based on fractal dimension, void ratio, and soluble salt content. These research findings provide predictive tools for managing collapse risks in loess-related projects, enabling fixed-point design of loess foundations and early warning of collapse risks. Full article

Wetting-induced soil deformation significantly impacts land stability and management on the Chinese Loess Plateau. This study analyzed silt soils from the Late Pleistocene (1 m depth) and Middle Pleistocene (25 m depth) to investigate compression and collapsible deformation during wetting. The compression in both soils progressed through three stages: slow deformation under low pressure, accelerated deformation under moderate pressure, and decelerated deformation under high pressure. Wetting intensified the compression in the 1 m sample but reduced it in the 25 m sample, with the deformation becoming more sensitive to the initial water content under higher pressures. Collapse tests showed contrasting behaviors: the 1 m sample exhibited collapsibility, while the 25 m sample displayed expansiveness (a negative collapsibility coefficient). Microstructural analysis revealed that the 1 m sample with abundant macropores and overhead structures had a lower structural stability than the 25 sample with more stable, rounded micropores. The wetting-induced deformation was governed by the balance between clay mineral expansion and structural collapse, with collapsibility prevailing when collapse dominated and expansiveness prevailing when expansion was predominant. These findings provide valuable insights into soil–water interactions and support improved land use and management strategies in the loess region. Full article

Collapsible loess is characterized by its unique soil-forming environment, mineral composition, and microstructure, resulting in poor engineering properties such as high water sensitivity, high collapsibility, high compressibility, and low strength. To improve the poor engineering properties of collapsible loess, we selected a suitable eco-friendly material—guar gum (GG)—for its improvement and reinforcement, and investigated the improvement effect of different GG dosages (0.5~1.5%) and curing ages (0~28 days) on collapsible loess. The mechanical properties of soil samples were determined by direct shear tests, unconfined compressive strength tests, and splitting tests. The water stability of soil samples was evaluated by both cube and sphere crumb tests. SEM and EDS analyses were also conducted to determine the microstructural and mineral changes in soil. The results indicate that the incorporation of GG is beneficial to inhibit the collapsibility of the soil and improves the water stability and strength of the soil. The collapsibility coefficient of loess is reduced to below 0.015 when 0.75% and above of GG is admixed, which is considered a complete loss of its collapsibility. When the GG dosage increases from 0% to 1.25%, the compressive strength and tensile strength of the soil samples increase by 43.5% and 34.9%, respectively. However, by further increasing the GG dosage to 1.5%, the compressive strength and tensile strength decrease by 3.8% and 6% compared to those with 1.25% GG. This indicates that the strength of the specimens shows an increasing trend and then a decreasing trend with the increase in GG dosage, and 1.25% GG was found to be the best modified dosage. Microstructural and mineral analyses indicate that the addition of GG does not change the mineral composition of loess, but, rather, it significantly promotes the agglomeration and bonding of soil particles through cross-linking with Ca²⁺ ions in the soil to form a biopolymer network, thus achieving a reliable reinforcement effect. Compared with the existing traditional stabilizers, GG is a sustainable and eco-friendly modified material with a higher low-carbon value. Therefore, it is very necessary to mix GG into collapsible loess to eliminate some of the poor engineering properties of loess to meet engineering needs. This study can provide test support for the application and promotion of GG-modified loess in water agriculture and road engineering. Full article

The collapsible loess will rapidly soften and lose its bearing capacity when soaked in water. Under a mild condition (20 °C), the biomimetic inorganic agent, diammonium phosphate (DAP), reacts with calcite in the collapsible loess, producing a stronger bonding material, hydroxyapatite (HAP), to modify and stabilize the soil. Uniaxial compression, permeability tests, and morphological analysis using X-ray diffraction and scanning electron microscopy equipped with an energy X-ray dispersive system were used to assess the effectiveness of DAP stabilization on the collapsible loess. The results indicated that HAP improved the inter-particle bonding within the loess, filled the pores within particles, reduced the permeability, and consequently mitigated the collapsibility of the loess. The compressive strength of the DAP-treated loess increased as DAP concentration increased. Following 28 days of curing, the compressive strength of the loess treated with a 3.0 mol/L DAP solution was six times greater than that of the untreated group. DAP’s reinforcement effect on the loess was superior to that of cement. The compressive strength of the DAP-treated loess was about double that of the cement-treated loess and the permeability coefficient was reduced by more than 50% at equivalent solid content. Furthermore, DAP generated 82% fewer carbon emissions compared to Portland cement. Considering eco-friendly and sustainable development, DAP offers a more competitive alternative for modification and stabilization of loess. Full article

Bored piles comprise an advanced pile foundation technology that has the advantages of high bearing capacity, fast construction speed, stable construction technology, and no noise or mud pollution. To study the applicability of bored piles to collapsible loess sites, the compaction effect and load-bearing characteristics of bored piles before and after immersion were studied via a full-scale field test combined with the theory of hole expansion. The results indicate that when the pile spacing is 1.0, 1.25, and 1.5 m, the average dry density of the soil between piles increases by 23.8%, 18.5%, and 3.1%, respectively, compared with that of untreated foundation soil. When bored piles are used to treat deep collapsible loess foundations, the reasonable pile spacing to eliminate the collapsibility of the loess foundation is 2.5 times the pile diameter. It is feasible to estimate the effective compaction range using the pore expansion theory, and the effective compaction coefficients of similar sites are given. The positive friction of bored piles in the collapsible loess area is more than 95.5 kPa, which increases by more than 48.5% compared with that of non-extruded piles. Therefore, the bearing capacity of a single pile is significantly improved, and it is an effective treatment method for collapsible loess areas. Under immersion, the pile side negative friction did not change significantly with a pile diameter of approximately 27 kPa, and the increase was approximately 14% compared with that of non-extruded piles. Consequently, to avoid the adverse effects of negative friction resistance on the bearing capacity of pile foundations and to fully utilize the technical advantages of bored piles, it is necessary to eliminate or partially eliminate site collapsibility before applying bored piles. The results can provide experimental support and theoretical guidance for the popularization and application of screw–squeeze piles in deep, collapsible loess areas. Full article

Collapsibility is a unique engineering geological property of loess. Choosing appropriate parameters to build the prediction model of loess collapsibility is an essential step toward solving the loess collapsibility problem. A case study was performed for the loess in Xinyuan County of the Yili River Basin, China. A large amount of data was collected from preliminary geotechnical tests in this region. Mathematical statistics were applied to analyse the correlations between the loess collapsibility and soil parameters. Multiple linear regression and neural network theories were adopted to build this region’s prediction model of loess collapsibility. The results showed that microscopically, the soils in this region were predominantly flocculated structures. The soil particles were flaky and in bracket contact, and the pores were round or irregularly shaped. Regarding the material composition, the soils were primarily composed of quartz and albite, with a low hematite content. In the study area, the correlation coefficients between the collapsibility coefficient of the loess vs. the density, dry density, saturation, porosity ratio, and porosity varied between 0.628 and 0.857, indicating a strong or very strong correlation. In terms of predicting loess collapsibility, the effectiveness of neural networks based on RBF (radial basis function) and multiple linear regression models was contrasted. The latter was discovered to be more appropriate, dependable, and accurate, with an accuracy percentage of 94.42%. Simultaneously, the model’s assessment index is 0.014 for the root mean squared error (RMSE), 0.962 for the correlation coefficient (CC), 0.919 for the Nash–Sutcliffe efficiency coefficient (NSE), and −1.494 percent for the percent bias (PBIAS). It works well for estimating whether local loess may collapse. Therefore, the RBF neural network model built in the present study has adequate precision and meets the engineering requirements. Our research sheds new light on loess collapsibility assessment in this region. Full article

A large-scale immersion experiment was carried out to assess the collapsibility characteristics of loess in Bu Li village located in the Weibei Loess Tableland, and the seepage characteristics and collapsibility evolution of loess were determined. The effects of void ratio, natural moisture content, material composition, and microstructure evolution on the loess collapsibility were characterized by X-ray diffraction, scanning electron microscopy, and water-soluble salt analysis to elucidate the collapsibility mechanisms. The water diffusion morphologies considering various foundation lithologies, initial water contents, and stratum combinations were studied with the numerical simulation method, and an inverted-box-shape barrier measure preventing loess from the water immersion was proposed. The results showed that the maximum consolidation settlement was approximately 380.5 mm for the test site, and the expansion of clay minerals and the dissolution of soluble salts during wetting were the critical reasons for loess collapse. The void ratio and natural moisture content showed a positive and negative correlation with the collapsibility coefficient, respectively, and the concept of collapsibility potential was introduced. The water diffusion morphologies in distinct stratum combinations significantly depended on the permeability capacity of the lower soil layer, and the optimal depths of the vertical barrier were recommended to be set at the maximum inflection point in the diffusion morphology or the main action layer. Full article

Collapsible loess is a kind of soil with special properties, and is widely distributed in China. When it is not wetted by water, its strength is generally high and its compressibility is low. However, when collapsible loess is wetted by water under a certain pressure, the soil structure will be rapidly destroyed, resulting in large additional subsidence. Therefore, when engineering constructions on collapsible loess sites are carried out, appropriate foundation treatment measures must be taken to eliminate foundation collapsibility. Because of their advantages, static pressure plain soil compaction (SP−PSC) piles are widely used for collapsible loess foundation treatments in China. However, at present, there is still a lack of accurate understanding of the distribution of compaction coefficient of soil among SP−PSC pile groups on collapsible loess foundations. The present study systematically investigated the distribution of the soil compaction coefficient among SP−PSC pile groups based on SP−PSC pile group tests and finite element analyses. The effect of different factors on soil compaction coefficient was analyzed and explored, including the pile diameter and length of SP−PSC piles, the soil moisture content, the pile spacing within the SP−PSC pile group, and the depth to ground. Finally, the simplified calculation models of the compaction coefficient of the soil at the center of pile group and at the midpoints of adjacent piles were analytically formulated. These models established a theoretical basis for the design and construction of SP−PSC pile groups on collapsible loess foundations. Full article

The physical and mechanical properties of the loess differ from other kinds of soil due to its collapsibility, which has resulted in the complex displacement development law of the loess slope. Therefore, the accurate estimation of the displacement of high slopes in a loess gully region is critical for the safety of people and in construction activities. In the present study, to improve the accuracy of traditional methods, the original cumulative displacement curve was decomposed into trend and fluctuation terms using Empirical Mode Decomposition (EMD) and Wavelet Decomposition (WD). Subsequently, the results were estimated using the Support Vector Machine (SVR) and Long Short-Term Memory Network (LSTM) optimized by Biogeography-based Optimization (BBO), respectively. To select the most appropriate model, SVR, LSTM, EMD-SVR-LSTM, EMD-BBO-SVR-LSTM, and WD-BBO-SVR-LSTM were employed to predict the deformation of a loess slope in the Loess Plateau of China. According to the results, the displacement increases rapidly at the starting stage, and then gradually stabilizes, which is the same as the trend in reality. On comparing the predicted results with field data, it was found that the models with decomposition algorithms achieved higher accuracy. Particularly, the determination coefficient of the EMD-BBO-SVR-LSTM model reaches 0.928, which has better algorithm stability and prediction accuracy than other models. In this study, the decomposition algorithm was applied to the loess slope displacement innovatively, and the appropriate machine learning algorithm adopted for the displacement components. The method improves the accuracy of prediction and provides a new idea for instability warning of loess excavation slopes. The research has implications for urban construction and sustainable development in loess mountainous areas. Full article

To improve the problem of collapsibility of loess, adding industrial materials such as cement is common engineering treatment, but this seriously damages the reclamation performance of soil. Calcium lignosulfonate (CLS) from paper plant waste fluids is a natural bio-based polymer with good application prospects as a soil improver. In this paper, the collapsibility and mechanical properties of CLS improved loess were investigated using a collapsibility test, gray correlation analysis, and an unconfined compressive strength test (UCS). In addition, the strengthening mechanism of CLS-improved loess was also explored based on scanning electron microscopy (SEM), microstructure parameters, and X-ray diffraction. The collapsibility coefficient decreased rapidly after CLS was admixed, and the single and double-oedometer methods showed the same change trend. The order of grey correlation degree of collapsibility on each index from large to small was: moisture content, pore ratio, dry density, and CLS content. The dosage of CLS greatly influenced the mechanical properties and collapsibility of stabilized loess. The optimum amount of CLS for Xi’an loess was 3%, at which the collapsibility coefficient was reduced by more than 95%, and the 28 d UCS increased by 180.01%. From the microstructure and mineral composition analysis perspective, CLS plays a role in filling pores and linking soil particles. After the protonation and ion exchange effect of CLS, the grain size and double electric layer thickness of mineral composition were reduced, and the structural compactness was increased. These research results are of great scientific significance for the ecological modification of soils. Full article

The accurate evaluation method of LID toward the attenuation of urban flood is still a hot issue. This paper focuses on a coupled 1D and 2D hydrodynamic model, investigating the model parameters set in a collapsible loess area, and the changes in the surface runoff, waterlogged area, and drainage network indicators under different rainfall patterns. The results show that the coupled model can effectively simulate the effect of LID facilities under unaltered and retrofitted conditions. It is found that the infiltration parameters in a collapsible loess area are higher than in other eastern cities by calibration and validation. After implementing the LID facilities, the total runoff, peak flood flow, waterlogged area, runoff coefficient, and drainage pressure under different rainfall patterns have all been reduced. With the increases in the rainfall return period, the waterlogging reduction effect of LID facilities would gradually weaken. The rainfall return period has a great impact on the indicators of surface runoff, waterlogged area, and drainage capacity. The coefficient of rainfall peak has a relatively big impact on indicators of pipelines, such as the proportion of overflow nodes, the proportion of fully loaded pipelines, and the average full-load duration. The rainfall duration has a major impact on the total runoff quantity, runoff coefficient, and average full-load duration. Full article