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

Symmetry ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 16 ◽  
Author(s):  
Yufeng Liu ◽  
Qing Wang ◽  
Xudong Zhang ◽  
Shengyuan Song ◽  
Cencen Niu ◽  
...  
Keyword(s):  
Water Content ◽  
Saline Soil ◽  
Salt Content ◽  
Frozen Soil ◽  
Unfrozen Water ◽  
Initial Water Content ◽  
Initial Water ◽  
Inference System ◽  
Unfrozen Water Content ◽  
Western Jilin

: 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.

scholarly journals Study on the Mechanical Criterion of Ice Lens Formation Based on Pore Size Distribution

2020 ◽  
Vol 10 (24) ◽  
pp. 8981
Author(s):  
Yuhang Liu ◽  
Dongqing Li ◽  
Lei Chen ◽  
Feng Ming
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Water Content ◽  
Size Distribution ◽  
Initial Water Content ◽  
Mean Stress ◽  
Initial Water ◽  
Unfrozen Water Content ◽  
The Mean ◽  
Lens Formation

Ice lens is the key factor which determines the frost heave in engineering construction in cold regions. At present, several theories have been proposed to describe the formation of ice lens. However, most of these theories analyzed the ice lens formation from a macroscopic view and ignored the influence of microscopic pore sizes and structures. Meanwhile, these theories lacked the support of measured data. To solve this problem, the microscopic crystallization stress was converted into the macro mean stress through the principle of statistics with the consideration of pore size distribution. The mean stress was treated as the driving force of the formation of ice lens and induced into the criterion of ice lens formation. The influence of pore structure and unfrozen water content on the mean stress was analyzed. The results indicate that the microcosmic crystallization pressure can be converted into the macro mean stress through the principle of statistics. Larger mean stress means the ice lens will be formed easier in the soil. The mean stress is positively correlated with initial water content. At the same temperature, an increase to both the initial water content and the number of pores can result in a larger mean stress. Under the same initial water content, mean stress increases with decreasing temperature. The result provides a theoretical basis for studying ice lens formation from the crystallization theory.

scholarly journals Modeling the Unfrozen Water Content of Frozen Soil Based on the Absorption Effects of Clay Surfaces

2020 ◽  
Vol 56 (12) ◽  
Author(s):  
Xiao Jin ◽  
Wen Yang ◽  
Xiaoqing Gao ◽  
Jian‐Qi Zhao ◽  
Zhenchao Li ◽  
...  
Keyword(s):  
Water Content ◽  
Frozen Soil ◽  
Unfrozen Water ◽  
Unfrozen Water Content

Strength of frozen saline soils

1995 ◽  
Vol 32 (2) ◽  
pp. 336-354 ◽  
Author(s):  
E.G. Hivon ◽  
D.C. Sego
Keyword(s):  
Water Content ◽  
Fine Particles ◽  
Constant Strain Rate ◽  
Significant Loss ◽  
Time Domain Reflectometry ◽  
Frozen Soil ◽  
Unfrozen Water ◽  
Strain Behavior ◽  
Unfrozen Water Content ◽  
The Time Domain

This paper summarizes an extensive laboratory program undertaken to study the influence of soil type, temperature, and salinity on the strength of three different frozen soils under conditions of unconfined constant strain rate tests. Since the effects of temperature and salinity can be unified by studying the variation of unfrozen water content, measurements of unfrozen water at different temperatures were carried out using the time-domain reflectometry (TDR) method. The stress–strain behavior is influenced by the presence of fine particles in the soil, and an increase in temperature and salinity (unfrozen water content) causes a significant loss of strength. For each soil tested, a predictive model of its strength in terms of salinity and temperature (unfrozen water content) is presented. Key words : frozen soil, saline, unfrozen water, strength.

scholarly journals Coupled cellular automata for frozen soil processes

SOIL ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 103-116 ◽  
Author(s):  
R. M. Nagare ◽  
P. Bhattacharya ◽  
J. Khanna ◽  
R. A. Schincariol
Keyword(s):  
Cellular Automata ◽  
Phase Change ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Potential ◽  
Frozen Soil ◽  
Soil Freezing ◽  
Unfrozen Water ◽  
First Order ◽  
Unfrozen Water Content

Abstract. Heat and water movement in variably saturated freezing soils is a strongly coupled phenomenon. The coupling is a result of the effects of sub-zero temperature on soil water potential, heat carried by water moving under pressure gradients, and dependency of soil thermal and hydraulic properties on soil water content. This study presents a one-dimensional cellular automata (direct solving) model to simulate coupled heat and water transport with phase change in variably saturated soils. The model is based on first-order mass and energy conservation principles. The water and energy fluxes are calculated using first-order empirical forms of Buckingham–Darcy's law and Fourier's heat law respectively. The liquid–ice phase change is handled by integrating along an experimentally determined soil freezing curve (unfrozen water content and temperature relationship) obviating the use of the apparent heat capacity term. This approach highlights a further subtle form of coupling in which heat carried by water perturbs the water content–temperature equilibrium and exchange energy flux is used to maintain the equilibrium rather than affect the temperature change. The model is successfully tested against analytical and experimental solutions. Setting up a highly non-linear coupled soil physics problem with a physically based approach provides intuitive insights into an otherwise complex phenomenon.

Effect of Sulfate Contaminant on Soil Properties and Infrastructure Safety in Permafrost Regions

2010 ◽  
Vol 113-116 ◽  
pp. 1208-1211
Author(s):  
Xi Zhong Yuan ◽  
Yuan Lin Zhu ◽  
Ning Zhang
Keyword(s):  
Physical Properties ◽  
Mechanical Behavior ◽  
Water Content ◽  
Contaminated Soil ◽  
Freezing Temperature ◽  
Frozen Soil ◽  
Unfrozen Water ◽  
Compression Tests ◽  
Exponential Relationship ◽  
Unfrozen Water Content

Contamination of unfrozen water in frozen soil could have adverse effects on surrounding infrastructure such as foundation instability or deterioration of trafficability. This paper describes the results of the experimental examination of the physical properties and mechanical behavior of Na2SO4 contaminated soil. Initial freezing temperature test, unfrozen water content test and unconfined compression tests were conducted on silts with 3 levels of concentrations (6, 18 and 42 ppt) of Na2SO4 and nonsaline cases at temperatures ranging between 0°C and -20°C. The test results indicate that the presence of salt significantly affect the physical properties and mechanical behavior of the frozen soil. Contamination of soils will cause depression of freezing temperature and degradation of permafrost. The freezing temperature depression ratio of Na2SO4 contaminated soil is 0.028°C/ppt. The unfrozen water content increases with an increase in salinity and temperature. The strength decreases with an increase in salinity, and the strength loss ratio of Na2SO4 contaminated soil is among 0.02-0.04MPa/ppt. Combined the effect of salinity and temperature on the strength, the decrease in strength with increase in unfrozen water content follows an exponential relationship. So estimation of salt concentration in the soil, and predictions of future increases of salt in the soil, is essential for design of buildings and roadways in permafrost.

scholarly journals Study on an AHP-Entropy-ANFIS Model for the Prediction of the Unfrozen Water Content of Sodium-Bicarbonate-Type Salinization Frozen Soil

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1209
Author(s):  
Qing Wang ◽  
Yufeng Liu ◽  
Xudong Zhang ◽  
Huicheng Fu ◽  
Sen Lin ◽  
...  
Keyword(s):  
Water Content ◽  
Frozen Soil ◽  
Support Vector ◽  
Unfrozen Water ◽  
Ensemble Model ◽  
Entropy Weight ◽  
Anfis Model ◽  
Inference System ◽  
Entropy Weight Method ◽  
Weight Method

The development of agriculture and ecology, and the construction of water conservancy facilities are seriously hindered by the salinization of seasonal frozen soil. Unfrozen water exists in the freezing and thawing of frozen soil. This unfrozen water is the core and foundation for studying the process of seasonal frozen soil salinization. However, it is difficult to obtain the unfrozen water content (UW) in routine experiments, and it shows nonlinear characteristics under the action of the main factors contained: salt content, water content, and temperature. In this paper, a new model is proposed to predict the UW of saline soil based on the combined weighting method and the adaptive neuro-fuzzy inference system (ANFIS). Firstly, the distance function was used to combine the analytic hierarchy process (AHP) with the entropy weight method (the combined weighting method) to determine the importance of the influencing factors (temperature, initial water content, and salt content) on UW. On this basis, the AHP, entropy weight method, and adaptive neuro-fuzzy inference system (AHP-entropy-ANFIS) ensemble model was established. Secondly, the five-fold cross-validation method and statistical factors (coefficient of determination, mean squared error, mean absolute percent error, and mean absolute error) were applied to evaluate and compare the AHP-entropy-ANFIS ensemble model, the ANFIS model, the support vector machine (SVM) model, and the AHP, entropy weight method, and support vector machine (AHP-entropy-SVM) ensemble model. In addition, the prediction values of the four models and the experimental values were also compared. The results show that the AHP-entropy-ANFIS model had the strongest prediction capability and the best stability, and so is more suitable for predicting the UW of saline soil. This study provides useful guidance for preventing and mitigating salinization hazards in seasonally frozen areas.

Unfrozen water content in saline soils: results using time-domain reflectometry

1985 ◽  
Vol 22 (1) ◽  
pp. 95-101 ◽  
Author(s):  
D. E. Patterson ◽  
M. W. Smith
Keyword(s):  
Water Content ◽  
Time Domain ◽  
Time Domain Reflectometry ◽  
Frozen Soil ◽  
Probe Design ◽  
Unfrozen Water ◽  
Use Of Time ◽  
Unfrozen Water Content ◽  
Pore Water Salinity ◽  
Apparent Dielectric Constant

The use of time-domain reflectometry (TDR) for determining the phase composition of saline permafrost from measurement of the apparent dielectric constant, Ka, is examined.Combined TDR–dilatometry experiments were performed to assess whether the TDR method could be used on frozen soil samples with high pore water salinity. In general, unfrozen water content determinations by TDR were within ±0.025 cm3∙cm−3 of those obtained by dilatometry, with no marked influence due to salinity. A novel probe design for use on saline core samples shows promise as a means for determining unfrozen water contents in the field.

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