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There has been a growing interest in controlled low strength material CLSM due to its engineering features, such as self-leveling and early strength development, as well as it potential for utilizing industrial waste. Still, the dynamic properties on CLSM are rarely studied. This study evaluates the feasibility of red mud as a partial aggregate replacement in foamed-lightweight CLSM, incorporating high-carbon fly ash and preformed foam. We varied both the red mud contents RMc and foam volume ratio FVR within the mixtures and examined their impact on unconfined compressive strength and dynamic properties including shear modulus G and damping ratio D. The results reveal that the red mud enhances foam stability, leading to more uniform pore structures and increased porosity, which reduces bulk densities. Despite higher porosity, red mud serves as a strong alkaline activator, enhancing geopolymer reactions of high-carbon fly ash and thereby increasing both compressive strength and initial shear modulus G0. Interestingly, increasing FVR had minimal impact on the D, while higher RMcnotably increased D, highlighting its distinct role in energy dissipation. The red mud-incorporated foamed CLSM exhibits strain-dependent normalized shear modulus G/G0 comparable to that of gravel, while its D is 40-100 % higher than gravel or gravelly soil at shear strain of 1.10-5, which corresponds to typical traffic-induced vibration levels. Moreover, theoretical volumetric-gravimetric relationships are introduced to account for the combined effects of FVR and RMcon CLSM behavior. These findings demonstrate that the red mud included foamed CLSM can be utilized as advanced structural backfill material capable of effectively mitigating the vibrations induced by traffic, low-amplitude seismic events, and mechanical sources.

期刊论文 2025-12-01 DOI: 10.1016/j.cscm.2025.e04893 ISSN: 2214-5095

This paper presents a method for analyzing slope stability in anisotropic and heterogeneous clay using a strength reduction finite element method (SRFEM) integrated with the level set method (LSM). Anisotropy refers to the inherent anisotropy in the clay's strength, while heterogeneity describes the spatial variability in strength parameters. The static LSM uses a zero level set function to model heterogeneous clay slopes. The method is validated through undrained slope stability analyses on different types of anisotropic clay and heterogeneous fields, showing its effectiveness in modeling anisotropic shear strength and capturing the characteristics of heterogeneous regions. The results indicate that the proposed method accurately predicts factors of safety and slip surfaces across various soil conditions, accounting for both anisotropic and heterogeneous characteristics.

期刊论文 2025-06-12 DOI: 10.1007/s11440-025-02641-8 ISSN: 1861-1125

Deep foundation pits, pipe gallery troughs, culverts, and other infrastructure often require backfilling operations. Soil-based controlled low-strength material (soil-based CLSM), with its advantages of self-compaction, self-leveling, and self-hardening, has garnered significant attention in recent years and shows potential as a replacement for traditional rolling compaction backfill materials. Based on the backfill project of the pipe gallery at the Xihong Bridge in Ningbo, this study investigates the unconfined compressive strength, permeability coefficient, compression characteristics, and flow behavior of soil-based CLSM with varying curing agent ratios, assessing its engineering feasibility through field testing. The results demonstrate that soil-based CLSM, particularly with polycarboxylate superplasticizer agent, exhibits substantially improved strength, permeability, construction workability, and other service performance. Additionally, a detailed simulation of the entire pipe gallery foundation pit construction process-including pipe gallery construction, trench backfilling, support removal, and road construction-was performed using the Hardening soil with small strain stiffness model of the soil. The deformation characteristics were analyzed under different backfill conditions to assess the suitability of soil-based CLSM for trench backfilling. The analysis also considered soil deformation under varying curing ages and upper load conditions. The optimized backfilling solution for soil-based CLSM was obtained and validated with field test data. The findings suggest that using soil-based CLSM for foundation trench backfilling can effectively mitigate settlement issues.

期刊论文 2025-05-01 DOI: 10.1007/s40571-025-00943-y ISSN: 2196-4378

The fracture network of hydraulic crack is significantly influenced by the bedding plane in coalbed methane extraction. Under mode II loading, crack deflection holds a key position in hydraulic cracking, especially in hydraulic shearing. This study first analyzed the crack deflection theory of layered rock. The semi-circle bending test under asymmetric loading is performed, and the four-dimensional Lattice Spring Model (4D-LSM) is established to examine how the bedding parameters affect coal crack propagation under mode II dominant loads. The 4D-LSM results are comparable to the coal loading test results under quasi-mode II and the analytical prediction of crack deflection theory. During mode II loading, the coal crack propagation is greatly influenced by the angle, strength, and elastic modulus of the bedding plane, while the effects of thickness and spacing of bedding are insignificant. The crack of coal tends to propagate towards the bedding, following a decrease in bedding angle, a decrease in bedding strength, and an increase in elastic modulus. With higher bedding strength, spacing, and thickness, the peak load on the coal sample is higher. The influences of bedding strength, elastic modulus, spacing, and thickness on the peak load of coal samples and its anisotropy gradually decrease. It is proved that compared with the tangential stress ratio and traditional energy release ratio theories, the corrected energy release ratio criterion can more accurately predict the direction of crack deflection of coal, especially under mode II loading. The results can provide assistance in the design of initiation pressure and fracturing direction in coal seam hydraulic fracturing. (c) 2025 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/).

期刊论文 2025-02-01 DOI: 10.1016/j.jrmge.2024.02.043 ISSN: 1674-7755

Advanced machine learning and deep Learning modeling applications for landslide susceptibility mapping are becoming increasingly popular. This study applied a deep learning model (DL) with a multilayer neural network to landslide research in the Phuoc Son district, Quang Nam province. Two methods for selecting conditioning factors, Correlation Attribute and OneR, were used to choose 12 condition parameters for landslides (Slope, Relief, Elevation, Distance to road, Rainfall, Land use, Weathering crust, Geology, Aspect, Soil, Distance to fault, and Curvature). Comparing the predicted results with two standard models, Naive Bayes (NB) and Support Vector Machine (SVM), showed that the DL model has higher and better prediction performance. Accordingly, the prediction performance of the DL model on the training dataset was ACC = 92.12%, AUC = 0.970, and on the validation dataset was ACC = 87.52, AUC = 0.944. The LSM developed based on the DL model indicates that areas with high landslide susceptibility are primarily concentrated in the southern part of the study area. These findings could be highly beneficial for urban planning management, risk management, and efforts to prevent and mitigate the damage caused by landslides in Phuoc Son.

期刊论文 2025-01-01 DOI: 10.15625/2615-9783/21658 ISSN: 0866-7187

With the rapid growth of shield-discharged soil (SDS), there is an increasing demand for effective recycling and transformation methods. This study aims to develop an alkali-activated controlled low-strength material (CLSM) by utilizing ground granulated blast furnace slag (GGBFS) and fly ash (FA) as precursors, SDS as fine aggregate, and sodium hydroxide (NaOH) solution as an activator. The Box-Behnken design (BBD) within the response surface methodology (RSM) framework was employed, considering liquid-to-solid ratio, alkali equivalent, aggregate-to-binder ratio, and foam agent content (FC) in SDS as key factors. Regression models were constructed to analyze the effects of these factors on flowability, bleeding rate, setting time, compressive strength, elastic modulus, and water absorption. The results confirmed the effectiveness of RSM in determining optimal conditions for material performance. In addition, microscopic analyses were conducted to explore hydration products, microstructural characteristics, and pore distribution. The findings revealed that the fresh density of the CLSM ranged from 1460 to 1740 kg/m(3), classifying it as a low-density material. The 28-day compressive strength varied from 1.837 to 7.884 MPa, while the setting time ranged between 1.2 and 5.6 hours. These properties comply with the ACI 229 standard and are suitable for practical applications. Interestingly, when the aggregate-to-binder (A/B) ratio was between 0.2 and 0.4, increasing the ratio did not lead to a consistent reduction in mechanical properties. Instead, the properties initially decreased and then improved. Moreover, an increase in foam agent content (FC) extended the setting time and reduced mechanical strength. The correlation coefficients of all models exceeded 0.98, with a coefficient of variation below 10 % and a signal-to-noise ratio greater than 4, demonstrating strong reliability and accuracy of the models. Additionally, the average relative error between predicted and experimental values in six scenarios was under 6 %, validating the feasibility of optimizing the design of alkali-activated CLSM using RSM. The formation of Ca(OH)(2) crystals facilitates early strength development, resulting in final cementitious materials reticular, fibrous C-S-H, C-A-H, and other gel-like hydration products. Calcium promotes the formation of gels such as C-S-H, shortening the setting time and enhancing microstructural density. This study provides valuable insights for optimizing the design of alkali-activated CLSM containing SDS, thereby expanding methods for utilizing construction and demolition waste.

期刊论文 2024-12-01 DOI: 10.1016/j.cscm.2024.e03800 ISSN: 2214-5095

The storage of mining waste not only consumes a vast tract of land, but it also poses environmental problems due to the leaching of heavy metals, dusting, and occasional slope failure. A coal mine overburden (hereafter referred to as black shale) is one of the mining wastes produced during the coal mining activity, dumping of which causes an environmental problem. By considering the issue associated with waste storage and the requirement for alternate civil engineering material, an attempt has been made to develop cementless controlled low strength material (CLSM) from black shale. For this purpose, black shale is mixed with a varying percentage of alkali activated ground granulated blast furnace slag (GGBS) and fly ash. The fresh CLSM is investigated for flowability, bleeding, and density, whereas the hardened CLSM is examined for unconfined compressive strength (UCS), hardened density, water absorption, ultrasonic pulse velocity, and durability. The CLSM developed in the present research is found to have self-flowing and self-leveling consistency, with flowability higher than 200 mm and a relative flow area between 2.06 and 7.70. The CLSM is found easily excavatable with a removability modulus less than 1. The 28-day UCS of CLSM is found between 0.48 MPa and 2.1 MPa, whereas it is found low to medium durable with a durability index between 84.44 % and 87.39 %. Further, the shear modulus of the hardened CLSM is evaluated using ultrasonic pule velocity. Finally, the CLSM is found non-toxic based on the result of the leaching analysis.

期刊论文 2024-11-22 DOI: 10.1016/j.conbuildmat.2024.138928 ISSN: 0950-0618

Landslides are a prevalent natural hazard in West Bengal, India, particularly in Darjeeling and Kurseong, resulting in substantial socio-economic and physical consequences. This study aims to develop a hybrid model, integrating a Genetic-based Random Forest (GA-RF) and a novel Self-Attention based Convolutional Neural Network and Long Short-term Memory (SA-CNN-LSTM), for accurate landslide susceptibility mapping (LSM) and generate landslide vulnerability-building map in these regions. To achieve this, we compiled a database with 1830 historical data points, incorporating a landslide inventory as the dependent variable and 32 geoenvironmental parameters from Remote Sensing (RS) and Geographic Information Systems (GIS) layers as independent variables. These parameters include features like topography, climate, hydrology, soil properties, terrain distribution, radar features, and anthropogenic influences. Our hybrid model exhibited superior performance with an AUC of 0.92 and RMSE of 0.28, outperforming standalone SA-CNN-LSTM, GA-RF, RF, MLP, and TreeBagger models. Notably, slope, Global Human Modification (gHM), Combined Polarization Index (CPI), distances to streams and roads, and soil erosion emerged as key layers for LSM in the region. Our findings identified around 30% of the study area as having high to very high landslide susceptibility, 20% as moderate, and 50% as low to very low. The vulnerability-building map for 244,552 building footprints indicated varying landslide risk levels, with a significant proportion (27.74%) at high to very high risk. Our model highlighted high-risk zones along roads in the northeastern and southern areas. These insights can enhance landslide risk management in Darjeeling and Kurseong, guiding sustainable strategies for future damage qualification.

期刊论文 2024-06-01 DOI: 10.1016/j.qsa.2024.100187 ISSN: 2666-0334

The volume of shield tunnel spoil (STS) is very large, its effective management is difficult, and it even causes environmental pollution. In this study, to achieve its recycling, a novel controlled low strength material (CLSM) was prepared by utilizing high fine-grained STS as partial aggregates instead of sand, and its engineering performance was thoroughly evaluated. In the process of mix proportion design, key parameters such as the STS-tototal aggregate ratio (TS/TA), foam agent content (F), water-to-binder ratio (W/B), binder-to-total aggregate ratio (B/TA), and fly ash-to-cement ratio (FA/C) were employed. Workability aspects (i.e., flowability, bleeding rate, and setting time) and physical and mechanical properties (i.e., unconfined compressive strength and density) were evaluated. Additionally, the pH of bleeding and leachate, as well as the impact of foam agent content on CLSM properties, were examined. The findings revealed that an increase in the TS/TA ratio was associated with a decrease in flowability, density, and compressive strength, as well as an extension in setting time. The CLSM, with a flowability range of 150-300 mm, exhibited a bleeding rate below 2%, setting times between 3.6 and 6.1 hours, 28-day strength ranging from 1.06 to 3.24 MPa, and fresh density ranging from 1810 to 2060 kg/m3. Generally, these results met the required specifications, although the fresh density was slightly lower. The pH results indicated that the CLSM is non-corrosive. Furthermore, our investigation highlighted the substantial influence of foam agent content on flowability and setting time. An increase of 0.1 parts per thousand in the proportion of foam agent within the total aggregates resulted in a flowability increase of 2.1-2.6 mm and a setting time increase of 4.25-4.99 minutes. Therefore, it is feasible to utilize high fine-grained STS in the production of CLSM.

期刊论文 2024-04-12 DOI: 10.1016/j.conbuildmat.2024.135836 ISSN: 0950-0618

在气候变化背景下,活动层厚度的变化会对多年冻土区水文,生态,寒区工程等产生较大的影响.本研究利用中科院气候系统模式CAS-FGOALS-g3和陆面过程模式CAS-LSM模拟分析了活动层厚度的变化趋势和相对变化.结果表明:活动层厚度整体上呈现出增加的趋势.1979-2014年,多年冻土区活动层厚度的区域平均为1.08 m,变化趋势为0.33 cm yr-1,其变化趋势与2 m气温变化趋势基本一致,相对变化范围为1%-58%,平均为10.9%.在未来四种不同的气候情景(SSP-2.6,SSP2-4.5,SSP3-7.0和SSP5-8.5)下,到2100年预计活动层厚度的相对变化分别为10.3%,14.6%,30.1%和51%.

期刊论文 2021-03-08
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