Changes in residual air saturation after thorough drainage processes in an air–water fine sandy medium

Li, Yan; Wu, Pengfei; Xia, Zhen; Yang, Qingshu; Flores, Giancarlo; Jiang, Haoyu; Kamon, Masashi; Yu, Biao

doi:10.1016/j.jhydrol.2014.07.019

Cited by 10 publications

(3 citation statements)

References 54 publications

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“…The TDR and T5 tensiometer probes were calibrated following Li et al (, ). Effects of water velocity on the probes' accuracy, changes in their accuracy, and signal drifts during prolonged formal column tests were also monitored.…”

Section: Methodsmentioning

confidence: 99%

“…As shown in the illustration of the experimental apparatus in Figure , the sandy medium used in the drainage experiments was placed in 44‐cm‐long polymethyl methacrylate columns with an inner diameter of 10 cm, an upper boundary solely open to air, and lower boundary open to both air and water. The hydraulic properties were measured online using conventional instruments and techniques (Li et al, ,). An SWT5 tensiometer probe (Delta‐T Devices Ltd.) and Trime‐IT Time‐domain reflectometry (TDR) probe (IMKO, Micromodultechnik GmbH, Germany) were installed on opposite sides of each column, 22.0 cm above its bottom, to measure capillary pressure and water saturation, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Li¹,

He²,

et al. 2019

Water Resources Research

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In efforts to reduce uncertainties about effects of minor changes in the pore structure of porous media on dynamic nonequilibrium effects (DNEs), we monitored water saturation‐capillary pressure relationships in both dynamic flow and static states in stepwise drainage processes of a sandy medium. The acquired data were used to detect DNE and their changes with time in each drainage step and construct new parameters to characterize DNE. Effects of factors affecting water flow—including capillary number, water saturation, rate of change of water saturation with time (△Sw/△t), and the maximum value of this rate (RSMAX)—on the magnitude of the DNE were then determined. Results show that entry pressures are considerably larger under dynamic flow conditions than under static flow conditions, and DNE only occurs when the water saturation exceeds a threshold value in a drainage process. During either a smooth drainage or drainage step, the maximum capillary pressure (PMAX) is reached before the minimum water saturation (SMIN). Moreover, in drainage steps RSMAX occurs before the maximum difference between the capillary pressures associated with the static and dynamic states (DPMAX), except when they start from the saturated state. Accordingly, DNEs in a drainage step are mainly reflected in the time between PMAX and SMIN (△t), DPMAX, the average sum of the squares of the difference between capillary pressures of the static and dynamic states (DPAVE), and the dynamic coefficient τ (which is often used to characterize DNE). Furthermore, our results indicate that the water saturation and its rate of change with time are more important parameters than the capillary number for modeling DNE in a drainage process, and we detected no clear correlation between either maximum or minimum values of τ and the timing of the most significant DNE during drainages. τ appears to characterize DNE effectively in smooth drainage processes, while △t, DPAVE, and DPMAX constitute meaningful supplementary parameters for the characterization of DNE in a drainage step of a stepwise drainage.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Li¹,

He²,

et al. 2019

Water Resources Research

Self Cite

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“…Those air permeability models require a reference value of k a measured under completely dry conditions as a matching point in the air‐filled porosity‐ k a curves. However, it is usually difficult and time consuming to measure k a under completely dry conditions because of shrinkage and crack formation in porous media, and prolonged drying processes (Aljibury and Evans ; Bear ; Li et al ). For instance, Kawamoto et al () used k a measured at −100 cm H 2 O instead of under completely dry conditions as the reference point for developing an air permeability model.…”

Section: Introductionmentioning

confidence: 99%

Using Grain‐Size Distribution Methods for Estimation of Air Permeability

et al. 2015

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Knowledge of air permeability (ka ) at dry conditions is critical for the use of air flow models in porous media; however, it is usually difficult and time consuming to measure ka at dry conditions. It is thus desirable to estimate ka at dry conditions from other readily obtainable properties. In this study, the feasibility of using information derived from grain-size distributions (GSDs) for estimating ka at dry conditions was examined. Fourteen GSD-based equations originally developed for estimating saturated hydraulic conductivity were tested using ka measured at dry conditions in both undisturbed and disturbed river sediment samples. On average, the estimated ka from all the equations, except for the method of Slichter, differed by less than ± 4 times from the measured ka for both undisturbed and disturbed groups. In particular, for the two sediment groups, the results given by the methods of Terzaghi and Hazen-modified were comparable to the measured ka . In addition, two methods (e.g., Barr and Beyer) for the undisturbed samples and one method (e.g., Hazen-original) for the undisturbed samples were also able to produce comparable ka estimates. Moreover, after adjusting the values of the coefficient C in the GSD-based equations, the estimation of ka was significantly improved with the differences between the measured and estimated ka less than ±4% on average (except for the method of Barr). As demonstrated by this study, GSD-based equations may provide a promising and efficient way to estimate ka at dry conditions.

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A new hysteresis model of the water retention curve based on pore expansion and contraction

Chen

Yang

2020

Computers and Geotechnics

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Changes in residual air saturation after thorough drainage processes in an air–water fine sandy medium

Cited by 10 publications

References 54 publications

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Factors Influencing Dynamic Nonequilibrium Effects in Drainage Processes of an Air‐Water Two‐Phase Fine Sandy Medium

Using Grain‐Size Distribution Methods for Estimation of Air Permeability

A new hysteresis model of the water retention curve based on pore expansion and contraction

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