The influence of coupled physical swelling and chemical reactions on deformable geomaterials

Coupled thermo‐hydro‐mechanical‐chemical modelling has attracted attention in past decades due to many contemporary geotechnical engineering applications (e.g., waste disposal, carbon capture and storage). However, molecular‐scale interactions within geomaterials (e.g., swelling and dissolution/precipitation) have a significant influence on the mechanical behaviour, yet are rarely incorporated into existing Thermal‐Hydro‐Mechanical‐Chemical (THMC) frameworks. This paper presents a new coupled hydro‐mechanical‐chemical constitutive model to bridge molecular‐scale interactions with macro‐physical deformation by combining the swelling and dissolution/precipitation through an extension of the new mixture‐coupling theory. Entropy analysis of the geomaterial system provides dissipation energy, and Helmholtz free energy gives the relationship between solids and fluids. Numerical simulation is used to compare with the selected recognized models, which demonstrates that the swelling and dissolution/precipitation processes may have a significant influence on the mechanical deformation of the geomaterials.     

Quantifying the impact of landscape changes on hydrological variables in the alpine and cold region using hydrological model and remote sensing data

Quantifying the impact of landscape on hydrological variables is essential for the sustainable development of water resources. Understanding how landscape changes influence hydrological variables will greatly enhance the understanding of hydrological processes. Important vegetation parameters are considered in this study by using remote sensing data and VIC-CAS model to analyse the impact of landscape changes on hydrology in upper reaches of the Shule River Basin (URSLB). The results show there are differences in the runoff generation of landscape both in space and time. With increasing altitude, the runoff yields increased, with approximately 79.9% of the total runoff generated in the high mountains (4200–5900 m), and mainly consumed in the mid-low mountain region. Glacier landscape produced the largest runoff yields (24.9% of the total runoff), followed by low-coverage grassland (LG; 22.5%), alpine cold desert (AL; 19.6%), mid-coverage grassland (MG; 15.6%), bare land (12.5%), high-coverage grassland (HG; 4.5%) and shrubbery (0.4%). The relative capacity of runoff generation by landscapes, from high to low, was the glaciers, AL, LG, HG, MG, shrubbery and bare land. Furthermore, changes in landscapes cause hydrological variables changes, including evapotranspiration, runoff and baseflow. The study revealed that HG, MG, and bare land have a positive impact on evapotranspiration and a negative impact on runoff and baseflow, whereas AL and LG have a positive impact on runoff and baseflow and a negative impact on evapotranspiration. In contrast, glaciers have a positive impact on runoff. After the simulation in four vegetation scenarios, we concluded that the runoff regulation ability of grassland is greater than that of bare land. The grassland landscape is essential since it reduced the flood peak and conserved the soil and water.     

A cavity expansion–based solution for interpretation of CPTu data in soils under partially drained conditions

A cavity expansion–based solution is proposed in this paper for the interpretation of CPTu data under a partially drained condition. Variations of the normalized cone tip resistance, cone factor, and undrained-drained resistance ratio are examined with different initial specific volume and overconsolidation ratio, based on the exact solutions of both undrained and drained cavity expansion in CASM, which is a unified state parameter model for clay and sand. A drainage index is proposed to represent the partially drained condition, and the critical state after expansion and stress paths of cavity expansion are therefore predicted by estimating a virtual plastic region and assuming a drainage-index–based mapping technique. The stress paths and distributions of stresses and specific volume are investigated for different values of drainage index, which are also related to the penetration velocity with comparisons of experimental data and numerical results. The subsequent consolidation after penetration is thus predicted with the assumption of constant deviatoric stress during dissipation of the excess pore pressure. Both spherical and cylindrical consolidations are compared for dissipation around the cone tip and the probe shaft, respectively. The effects of overconsolidation ratio on the stress paths and the distributions of excess pore pressure and specific volume are then thoroughly investigated. The proposed solution and the findings would contribute to the interpretation of CPTu tests under a random drained condition, as well as the analysis of pile installation and the subsequent consolidation.     

Three‐dimensional shakedown solutions for anisotropic cohesive‐frictional materials under moving surface loads

Previous work on three‐dimensional shakedown analysis of cohesive‐frictional materials under moving surface loads has been entirely for isotropic materials. As a result, the effects of anisotropy, both elastic and plastic, of soil and pavement materials are ignored. This paper will, for the first time, develop three‐dimensional shakedown solutions to allow for the variation of elastic and plastic material properties with direction. Melan's lower‐bound shakedown theorem is used to derive shakedown solutions. In particular, a generalised, anisotropic Mohr–Coulomb yield criterion and cross‐anisotropic elastic stress fields are utilised to develop anisotropic shakedown solutions. It is found that shakedown solutions for anisotropic materials are dominated by Young's modulus ratio for the cases of subsurface failure and by shear modulus ratio for the cases of surface failure. Plastic anisotropy is mainly controlled by material cohesion ratio, the rise of which increases the shakedown limit until a maximum value is reached. The anisotropic shakedown limit varies with frictional coefficient, and the peak value may not occur for the case of normal loading only. Copyright © 2013 John Wiley & Sons, Ltd.     

A nonstationary extreme value distribution for analysing the cessation of karst spring discharge

The effects of climate change and population growth in recent decades are leading us to consider their combined and potentially extreme consequences, particularly regarding hydrological processes, which can be modeled using a generalized extreme value (GEV) distribution. Most of the GEV models were based on a stationary assumption for hydrological processes, in contrast to the nonstationary reality due to climate change and human activities. In this paper, we present the nonstationary generalized extreme value (NSGEV) distribution and use it to investigate the risk of Niangziguan Springs discharge decreasing to zero. Rather than assuming the location, scale, and shape parameters to be constant as one might do for a stationary GEV distribution analysis, the NSGEV approach can reflect the dynamic processes by defining the GEV parameters as functions of time. Because most of the GEV model is designed to evaluate maxima (e.g. flooding, represented by positive numbers), and spring discharge cessation is a ?minima’, we deduced an NSGEV model for minima by applying opposite numbers, i.e. negative instead of positive numbers. The results of the model application to Niangziguan Springs showed that the probability of zero discharge at Niangziguan Springs will be 1/80 in 2025, and 1/10 in 2030. After 2025, the rate of decrease in spring discharge will accelerate, and the probability that Niangziguan Springs will cease flowing will dramatically increase. The NSGEV model is a robust method for analysing karst spring discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.