ORCID Profile
0000-0001-7208-5515
Current Organisation
Hong Kong University of Science and Technology
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Publisher: Wiley
Date: 28-02-2014
Publisher: Elsevier BV
Date: 04-2014
Publisher: Elsevier BV
Date: 04-2016
Publisher: Canadian Science Publishing
Date: 10-2010
DOI: 10.1139/T10-073
Publisher: Canadian Science Publishing
Date: 12-2009
DOI: 10.1139/T09-072
Abstract: Unsaturated hydraulic conductivity is the primary soil parameter required when performing seepage analyses for unsaturated–saturated soil systems. Unsaturated hydraulic conductivity is also one of the most difficult parameters to measure because of the time involved and the limited suction measurement range (e.g., 0∼1500 kPa in a test using the steady-state method). In this study, a new wetting front advancing method was developed for measuring unsaturated hydraulic conductivity. The wetting front advancing method simulates and monitors a soil wetting process through a large-scale soil column. A new interpretative procedure was developed to calculate the unsaturated hydraulic conductivity based on the monitored water content, suction, and wetting front advancing velocity. The proposed technique is used to measure the unsaturated hydraulic conductivities of five soils, which vary from gravel to clay. The results indicate that the proposed technique is time-saving (i.e., requires several days for a complete test) and is applicable over wide ranges of suctions and unsaturated hydraulic conductivities. The measured unsaturated hydraulic conductivity using the wetting front advancing method is similar to that obtained using the instantaneous profile method, with the latter covering narrower ranges of soil suction and hydraulic conductivity.
Publisher: ASTM International
Date: 09-09-2013
DOI: 10.1520/GTJ20130002
Publisher: ASTM International
Date: 2009
DOI: 10.1520/GTJ102201
Publisher: American Society of Civil Engineers (ASCE)
Date: 10-2010
Publisher: Canadian Science Publishing
Date: 07-2011
DOI: 10.1139/T11-027
Abstract: Cracks are widely present in natural and engineered soils. As water infiltration into a cracked soil often starts from unsaturated conditions, the soil-water characteristic curve (SWCC) and permeability function for the cracked soil are required when conducting seepage analysis. This paper presents a method to predict the SWCC and permeability function for cracked soil considering crack volume changes during drying–wetting processes. The cracked soil is viewed as an overlapping continuum of a crack network system and a soil matrix system. The pore-size distributions for the two pore systems at a particular state can be determined and used to estimate the SWCCs and permeability functions. The estimated SWCCs and permeability functions for the two pore systems can be combined to give the SWCC and the permeability function for the cracked soil at that state. Then, the SWCC and permeability function for the cracked soil at different states along a crack development path can be obtained and combined to give the SWCC or permeability function for the cracked soil considering crack volume changes. Ex les are presented to illustrate the prediction of the SWCCs and permeability functions for a cracked soil along five crack development paths.
Publisher: Thomas Telford Ltd.
Date: 04-2014
Abstract: Field measured data reflect real response of soil slopes under rainfall infiltration. Based on field measured pore-water pressure histories, prediction models for slope design can be calibrated. In this study, a probabilistic approach based on the Bayesian theory is adopted to calibrate a slope-stability model using time-varying response data and to justify appropriate monitoring duration and data recording interval for field monitoring programmes. As an illustrative case study, field measured pore-water pressure responses in a natural terrain slope in Hong Kong are used to calibrate a prediction model using the Markov chain Monte Carlo simulation method. It is found that with the increase of measurement duration for model calibration, the uncertainties of soil parameters can be reduced. The duration of the calibrated data should be sufficiently long so as not to underestimate the model error. With regard to the effect of measurement interval, both the uncertainties of input parameters and the model error are increased with the increase of data recording interval. The correlations among the soil parameters are subject to greater uncertainties and the prediction accuracy of the calibrated model is reduced with a larger recording interval.
Publisher: American Society of Civil Engineers
Date: 04-03-2013
Publisher: CRC Press
Date: 30-06-2008
Publisher: Canadian Science Publishing
Date: 02-2009
DOI: 10.1139/T08-110
Abstract: The microporosity structure of soil provides important information in understanding the shear strength, compressibility, water-retention ability, and hydraulic conductivity of soils. It is a soil characteristic that depends on s le preparation method and wetting–drying history. A comprehensive study of the microporosity structure of a lean clay with sand was conducted in this research to investigate variations of the microporosity structure during compaction, saturation, and drying processes. Scanning electron microscopy was used to observe the microporosity structure of soil s le surfaces. Mercury intrusion porosimetry was used to measure the microporosity structure quantitatively by showing the relationship between cumulative pore volumes and pore radius. The experimental results show that a dual-porosity structure (i.e., interaggregate pores and intra-aggregate pores) forms during the compaction process. The interaggregate pores are compressible and the associated volume is closely related to the final void ratio of the compacted s le. Changes to interaggregate pores is dominant during compaction, but changes to intra-aggregate pores is dominant during saturation and drying. Based on the experimental results, a dual-porosity structure model was developed by relating the pore-size distribution to the void ratio. Consequently, the pore-size distribution at any void ratio can be predicted.
No related grants have been discovered for Limin Zhang.