Experimental Investigation of Water Migration
Characteristics for Saline Soil

Zhang, Xudong; Liu, Shouwei; Wang, Qing; Wang, Gang; Liu, Yufeng; Peng, Wei; Xu, Xingkai; Liu, Yaowu

doi:10.15244/pjoes/85952

Cited by 41 publications

(12 citation statements)

References 11 publications

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“…During the process of soil freezing, the water in the saline soil will migrate upwards (frozen process from top to bottom) as the temperature decreases, and the dissolved salts in the water will be transported upward together. In this process, due to the interaction of the temperature field, hydraulic field, and stress field, water and salt migration will occur, leading to soil frost heave and soil salinization [6,12]. The unfrozen water in the soil is the source of water migration, and the amount of water migration (unfrozen water content) at different temperatures is different.…”

Section: Introductionmentioning

confidence: 99%

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Using ANFIS and BPNN Methods to Predict the Unfrozen Water Content of Saline Soil in Western Jilin, China

et al. 2018

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: Saline soil in seasonally frozen soil areas has caused tremendous damage to engineering and the ecological environment. The unfrozen water is the main factor affecting the properties of saline soil in seasonally frozen soil area and therefore needs to be studied. However, due to the high cost of laboratory measurement of the unfrozen water content, this study focuses on using an adaptive network fuzzy inference system (ANFIS) and a back propagation neural network (BPNN) to predict the unfrozen water content of saline soil in the Zhenlai area, Western Jilin. The data for the constructed model is obtained by nuclear magnetic resonance (NMR) testing. The initial water content (W0), salt content (S), and temperature (T) are used as input parameters for predicting the unfrozen water content (Wu). The results of the ANFIS and BPNN models are compared. The results show that although both methods are suitable for predicting the unfrozen water content of saline soil in the Zhenlai area, western Jilin, the prediction accuracy of the ANFIS model is higher.

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Section: Introductionmentioning

confidence: 99%

“…The unfrozen water content is a key physical parameter of frozen soil and salinized soil. The prediction and analysis of unfrozen water content will provide theoretical support for water and salt migration and is of great significance to the study of frozen soil and its salinization [12,13].…”

Section: Introductionmentioning

confidence: 99%

Using ANFIS and BPNN Methods to Predict the Unfrozen Water Content of Saline Soil in Western Jilin, China

et al. 2018

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“…The high clay and silt content in the saline soil increases the soil's specific surface area and surface energy and strengthens the adsorption capacity of the soil surface. The higher the content of Na + in the soil, the thicker the bound water film on the outer surface of the soil particles [20]. When the water content is very low, salt crystallizes and forms a bond between soil particles.…”

Section: Specimen Designmentioning

confidence: 99%

Prediction of the Structural Yield Strength of Saline Soil in Western Jilin Province, China: A Comparison of the Back-Propagation Neural Network and Support Vector Machine Models

et al. 2020

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With the increase in transportation emissions, road diseases in the saline soil area of Jilin Province have become a problem that requires serious attention. In order to improve the subgrade performance, the structural yield strength (SYS) of remolded soil and its factor sensitivity are investigated in this study. Saline soils in Western Jilin are structural in the sense that the bonding strength of soil skeleton is mainly provided by the solidification bond formed by a physicochemical interaction between particles. Its SYS is influenced by its cementation type, genetic characteristics, original rock structure, and environment. Because of the high clay content in Zhenlai saline soil, the specific surface area of soil particles is large, and the surface adsorption capacity of soil particles is strong. In addition, the main cation is Na+. The cementation strength of bound water film between soil particles is thus easily affected by water content and salt content, and compaction is also an important factor affecting the strength of soil. Therefore, in this study, the back-propagation neural network (BPNN) model and a support vector machine (SVM) are used to explore the relationship of saline soil’s SYS with its compactness, water content, and salt content. In total, 120 data points collected by a high-pressure consolidation experiment are applied to building BPNN and SVM model. For eliminate redundant features, Pearson correlation coefficient (rPCC) is used as an evaluation standard of feature selection. The K-fold cross-validation method was used to avoid over fitting. To compare the performance of the BPNN and SVM models, three statistical parameters were used: the determination coefficient (R2), root mean square error (RMSE), and mean absolute percentage deviation (MAPD). The result shows that the average values of R2, RMSE, and MAPD of the BPNN model are superior to the values of the SVM. We conclude that the BPNN model is slightly better than the SVM for predicting the SYS of saline soil. Thus, the BPNN model is used to analyze the factor sensitivity of SYS. The results indicate that the influence degrees of the three parameters are as follows: water content > compactness > salt content. This study can provide a basis for estimating the structural yield pressure of soil from its basic properties, and can provide a new way to obtain parameters for geotechnical engineering, ensuring safety while maintaining symmetry in engineering costs.

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“…e high groundwater level and salinity degree may produce secondary salinization of the subgrade soil under the action of capillary water in winter and transpiration in summer [7]. e dynamic groundwater can intensify the increase of the soil moisture and salt content, which provide water and salt replenishment for the salt heave and frost heave of the highway [8]. Additionally, the large temperature fluctuation process, especially the cooling process, provides temperature conditions for salt expansion and also provides sufficient temperature stress for the moisture in the roadbed soil to move it to the top of the roadbed, thereby causing roadbed salt cracking [9,10].…”

Section: Introductionmentioning

confidence: 99%

Evaporative Cracking Characteristics of the Embankment Soil Affected by the Saline Concentration

Liu

Xia

et al. 2022

Advances in Civil Engineering

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Embankment soil affected by saline can not only cause roadbed settlement, frosting, and road cracks but also cause corrosion and cracking of roadbed pipelines, which seriously affects the stability of the road. Water evaporation and dry cracking of the saline soil mainly cause soil swelling, poor water stability, and corrosive characteristics of the embankment soil. In this study, the evaporative cracking characteristics of soil with different saline concentrations were investigated. The results showed that the moisture content decreased linearly with the drying time in the early evaporation process, subsequently decreased slow down in the mid-term evaporation, and finally become got and remain a residual moisture content, which are 46.39%, 44.05%, 42.70%, and 40.27% with the increase of the saline concentration. The evaporation process with different saline concentrations in the soil can be divided into three stages: uniform evaporation stage, slow down evaporation stage, and equilibrium evaporation stage, which was consistent with the moisture content change. With the development of the drying time, the cracks gradually appeared on the soil surface, gradually deepened in the soil, and expanded the crack network. The development of cracks can be divided into three stages: the cracking preparation stage, the crack development stage, and the crack stable stage. The cracking began at high evaporation rate under high saline concentration, and the fractal dimension remained stable under similar saline concentration. The fractal dimension was gradually increased with the decrease of the moisture content and the increase of the saline concentration, respectively. The soil began to crack with larger moisture under high saline concentration. The drying cracks in the nature were consistent with the configuration of the cracks formed in the experimental results.

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Experimental Investigation of Water Migration Characteristics for Saline Soil

Cited by 41 publications

References 11 publications

Using ANFIS and BPNN Methods to Predict the Unfrozen Water Content of Saline Soil in Western Jilin, China

Using ANFIS and BPNN Methods to Predict the Unfrozen Water Content of Saline Soil in Western Jilin, China

Prediction of the Structural Yield Strength of Saline Soil in Western Jilin Province, China: A Comparison of the Back-Propagation Neural Network and Support Vector Machine Models

Evaporative Cracking Characteristics of the Embankment Soil Affected by the Saline Concentration

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