Estimation of air permeability function from soil-water characteristic curve

Zhai, Qian; Rahardjo, Harianto; Satyanaga, Alfrendo

doi:10.1139/cgj-2017-0579

Cited by 37 publications

(14 citation statements)

References 28 publications

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“…where θ is the water content of the soil, θ s is the saturation water content, a is the parameter related to the intake value, n is the parameter in the dehydration process of saturated soil, m is the parameter related to the residual saturation, e is the parameter related to the natural logarithm, C is the correction coefficient, and C r is an input value related to the residual water saturation, which can be roughly estimated as C r ¼ 1500 kPa for most cases. [51,52] Then, we can derive Equation ( 5) from Equation ( 1)-( 4); the relationship between water content (θ) and RH is written as…”

Section: Resultsmentioning

confidence: 99%

“…Fredlund and Xing's formula is one of the most widely used fitting formulas of the water–soil characteristics curve [ 51 ]

θ = C \frac{θ_{normals}}{{false{ln false[e + {false(\frac{ψ}{a} false)}^{n} false] false}}^{m}}

C = 1 - \frac{ln false(1 + \frac{ψ}{C_{normalr}} false)}{ln false(1 + \frac{10^{6}}{C_{normalr}} false)}

where θ is the water content of the soil,

θ_{normals}

is the saturation water content, a is the parameter related to the intake value, n is the parameter in the dehydration process of saturated soil, m is the parameter related to the residual saturation, e is the parameter related to the natural logarithm, C is the correction coefficient, and

C_{normalr}

is an input value related to the residual water saturation, which can be roughly estimated as C r = 1500 kPa for most cases. [ 51,52 ] Then, we can derive Equation () from Equation ()–(); the relationship between water content ( θ ) and

RH

is written as

θ = (1 - \frac{ln false[1 + \frac{R T}{g w_{normalw} C_{normalr}} ln false(RH false) false]}{\ln false(1 + \frac{10^{6}}{C_{normalr}} false)}) \times \frac{θ_{normals}}{false{ln false[e + {false(\frac{RT}{a g w_{normalw}} ln false(RH false) false)}^{n <...}}

…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

Huang

Shan

Xuan

et al. 2022

Physica Rapid Research Ltrs

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The humidity sensors based on metal halide perovskite have achieved outstanding improvement. However, there are few reports of perovskite nanocrystals for humidity sensors. Herein, CsPdBr3 nanocrystals with high surface‐to‐volume ratio are synthesized by the in situ spin‐coating method. Subsequently, the humidity sensor based on CsPdBr3 nanocrystals is prepared and the response mechanism is demonstrated to originate from the formation of the Pd––O bond on the surface by performing density functional theory calculation. The humidity sensor shows a fast response/recovery time of 0.68/2.43 s in a relative humidity range from 88.9%RH to 4.7%RH; the fast response/recovery properties are used to monitor human respiratory and noncontact switch. Moreover, the hydromechanical characteristics of unsaturated soil are obtained by noncontact testing with the humidity sensor for the first time in geological engineering, and the strong correlation between relative humidity and hydromechanical characteristics is revealed by mathematical derivation, which lays the theoretical foundation for the noncontact real‐time sensing of hydromechanical characteristics of unsaturated soil. These findings not only open the door to the development of perovskite nanocrystals materials for humidity measurement, but also offer a new method for nondestructive and real‐time test of the mechanical properties of soil in geological engineering.

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Section: Resultsmentioning

confidence: 99%

“…Fredlund and Xing's formula is one of the most widely used fitting formulas of the water–soil characteristics curve [ 51 ]

θ = C \frac{θ_{normals}}{{false{ln false[e + {false(\frac{ψ}{a} false)}^{n} false] false}}^{m}}

C = 1 - \frac{ln false(1 + \frac{ψ}{C_{normalr}} false)}{ln false(1 + \frac{10^{6}}{C_{normalr}} false)}

where θ is the water content of the soil,

θ_{normals}

C_{normalr}

RH

is written as

θ = (1 - \frac{ln false[1 + \frac{R T}{g w_{normalw} C_{normalr}} ln false(RH false) false]}{\ln false(1 + \frac{10^{6}}{C_{normalr}} false)}) \times \frac{θ_{normals}}{false{ln false[e + {false(\frac{RT}{a g w_{normalw}} ln false(RH false) false)}^{n <...}}

…”

Section: Resultsmentioning

confidence: 99%

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

Huang

Shan

Xuan

et al. 2022

Physica Rapid Research Ltrs

View full text Add to dashboard Cite

show abstract

“…Besides, considering the relation between the grain-size distribution and SWCC [22][23][24], some equations can be used to estimate unimodal SWCC with unimodal grain-size distribution [11,25]. Pore size distribution function (PSDF) and volumetric shrinkage curve (VSC) also play an important role in estimating SWCC.…”

Section: Introductionmentioning

confidence: 99%

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Zhou

Ren

2021

Mathematical Problems in Engineering

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Much attention has been paid on the soil-water characteristic curve (SWCC) during decades because it plays great roles in unsaturated soil mechanics. However, it is time-consuming and costly to obtain a series of entire saturation-suction data by experiments. The curves acquired by directly fitting empirical equations to limited experimental data are greatly different from the actual SWCC, and the relevant soil parameters obtained by inaccurate curve are also incorrect. Thus, an improved prediction method for more accurate entire SWCC was established. This novel method was based on the analysis of shape characteristics of SWCC with three critical points S , C 1 , and C 2 under the hypothesis of geometrical symmetric relation. The theoretical computation was specifically deduced under conventional Gardner, VG, and FX models, respectively, and then inferred on different soil types of 45 collected SWCC datasets. This geometrical symmetric relation exhibited well in all these three conventional empirical equations, especially in Gardner equation. Finally, a series of filer paper tests on sand, silt, and clay were also carried out to acquire entire SWCC curve for the verification and evaluation of the proposed geometrical method. Results show that this improved prediction method effectively decreases deviation resulting from directly fitting empirical equations to limited data of wide types of soils. The averaged improvement was larger under VG equation than under Gardner and FX equation. It proved that the accuracy of predicting greatly depends on the shape characteristic point of maximum curve curvature (point C 2 ), other than the number of points. This research provides a novel computation method to improve prediction accuracy even under relative less experimental data.

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“…In particular, the matric suction, that is the component of the total suction pertaining to the soil skeleton, arises from two distinct sources: capillary and short-range adsorption phenomena. The first source is controlled by the pore size density distribution [1,2]. The importance of the second one increases with an increase in the amount of silty and clayey fractions present in the soil.…”

Section: Introductionmentioning

confidence: 99%

Two-Scale Investigation of the Retention Behavior of a Well-Graded Mixed Soil

Bottiglieri¹,

Cafaro²,

Cotecchia³

2021

Geosciences

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The hydraulic characterization of mixed compacted soils is helpful for the design of earthworks subjected to drying–wetting cycles. When the mixed soil is well-graded and made of both coarse and fine fractions, its matric suction may also be due to the short-range adsorption phenomena, as for the soil investigated in this research work. A silty–clayey sand was created by a mixing procedure and experimentally investigated at two different scales. Physical modeling of an infiltration process was performed, allowing an inverse numerical analysis to infer the water retention and the hydraulic conductivity functions of the soil, whereas element testing on soil specimens allowed direct determination of the same equations. In the article, problems related to the employed suction measurement techniques have been pointed out and discussed. By this two-scale combined strategy, features of the soil hydraulic behavior, such as the wetting collapse, the shrinkage during drying, and the loop of hysteresis, were also determined.

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Estimation of air permeability function from soil-water characteristic curve

Cited by 37 publications

References 28 publications

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Two-Scale Investigation of the Retention Behavior of a Well-Graded Mixed Soil

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Estimation of air permeability function from soil-water characteristic curve

Cited by 37 publications

References 28 publications

High‐Performance Humidity Sensor Based on CsPdBr3Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

High‐Performance Humidity Sensor Based on CsPdBr3Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Two-Scale Investigation of the Retention Behavior of a Well-Graded Mixed Soil

Contact Info

Product

Resources

About

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil

High‐Performance Humidity Sensor Based on CsPdBr₃Nanocrystals for Noncontact Sensing of Hydromechanical Characteristics of Unsaturated Soil