Permeability function for oil sands tailings undergoing volume change during drying

Abstract

The coefficient of permeability function is an important unsaturated soil property required when modeling seepage and contaminant transport phenomena. Inaccuracies in the estimation of the permeability function can lead to significant errors in numerical modeling results. Changes in void ratio and degree of saturation are factors that influence the permeability function. Presently available methodologies for estimating the unsaturated permeability function make the assumption that there is no volume change as soil suction is changed. As a result, volume changes are interpreted as changes in degree of saturation. The commonly used estimation techniques for the permeability function are reasonable for soils such as sands that experience little volume change as soil suction is changed. On the other hand, inaccurate results are generated when soils undergo volume change as is the case with oil sands tailings. Revisions to previous methodologies are proposed to render the estimation of the permeability function more suitable for simulating the drying process associated with soils that undergo high volume changes. The revised methodology independently analyzes the effect of volume changes (i.e., changes in void ratio) and degree of saturation changes (i.e., changes in S-SWCC (degree of saturation - soil-water characteristic curve)). Laboratory data on thickened oil sands tailings are presented and interpreted within the context of the proposed methodology.

Soil-water characteristic curves - Determination, estimation and application

“…It has been highlighted earlier that the AEV determined from θ−SWCC, w-SWCC and S-SWCC are different for soils with volume change. The correct AEV is given by S-SWCC and this AEV should be used as the upper bound of the lower limit of integration (sL) when determining the permeability function from either θ−SWCC or w-SWCC (Wijaya and Leong, 2018). If S-SWCC is used, the difference in kr if sL values from less than AEV to AEV is only about 0.5 order in magnitude (Wijaya and Leong, 2018) as illustrated for oil tailing sands in Fig.…”

Shrinkage Curves for Powder and Granular Bentonites

“…However, change in the volume of bentonite, due to the change in water content, will lead to a change in the permeability of the bentonite [3][4][5]. Thus, it is necessary to construct shrinkage curve to understand the relationship between water content with void ratio of the bentonite [6][7][8].…”

Effects of grain-size distribution and hysteresis on soil-water characteristic curve (SWCC)

“…(v) A number of SWCC equations for unimodal SWCC have been evaluated by Leong and Rahardjo (1997a). Several bimodal SWCC equations have been proposed (Zhang and Chen, 2005;Carducci et al, 2011;Satyanaga et al, 2013;Li et al, 2014;and Wijaya and Leong, 2016;Zhang et al, 2017). Compared to the unimodal SWCC equations, bimodal SWCC equations have more unknown parameters.…”

“…The effects of the parameters of ZC and CA on the bimodal SWCC are similar as the effects of the parameters on and van Genuchten (1980) unimodal SWCC equations, respectively. The ZC equation parameters pl, and npl, ps and nps can be combined together as θl and θs (Zhang et al, 2017), respectively, and θs+ θl= θsat, where θsat is assumed known. Hence, the number of unknown parameters in the ZC equation can be reduced from 12 to 9 and the ZC equation can be rewritten as Equation 7.1 .…”