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Arid saline soils are well-distributed over the globe, with a variety of nomenclature. Along the seaboard of the Arabian Gulf, these soils exist widely and are known as “sabkhas”. Despite the cemented and saline characteristics of the sabkha matrix, a recent investigation indicated that flooding the saline sabkha with distilled water in the conventional oedometer apparatus was incapable of producing a sudden reduction in volume and/or a significant collapse. This study proposes a modification to the conventional oedometer on undisturbed sabkha specimens to consolidating specimens under a constant head. Tests were, therefore, conducted on undisturbed sabkha specimens to assess their compressibility and collapse potential whereby percolation of water was commenced under two pressures to evaluate the role of sustained pressure on the collapse mechanisms.
Despite the low compressibility of sabkhas, results of these tests indicated that these arid, saline soils possess a high collapse potential attributable primarily to dissolution of sodium chlorides, leaching of calcium ions and soil grain adjustment. The collapse potential increases with an increase in the acting pressure at which percolation of water takes place. In contrast to other typical soils, the collapse of arid, saline soils is not instantaneous but requires sufficient volume of water to percolate in order to enhance the dissolution of the cementing agents. 相似文献
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This paper presents a u‐p (displacement‐pressure) semi‐Lagrangian reproducing kernel (RK) formulation to effectively analyze landslide processes. The semi‐Lagrangian RK approximation is constructed based on Lagrangian discretization points with fixed kernel supports in the current configuration. As a result, it tracks state variables at discretization points while allowing extreme deformation and material separation that is beyond the capability of Lagrangian formulations. The u‐p formulation following Biot theory is incorporated into the formulation to describe poromechanics of saturated geomaterials. In addition, a stabilized nodal integration method to ensure stability of the domain integration and kernel contact algorithms to model contact between bodies are introduced in the u‐p semi‐Lagrangian RK formulation. The proposed method is verified with several numerical examples and validated with an experimental result and the field data of an actual landslide. 相似文献
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W. Ngan L. Van Waerbeke A. Mahdavi C. Heymans H. Hoekstra † 《Monthly notices of the Royal Astronomical Society》2009,396(2):1211-1216
The precision study of dark matter using weak lensing by large-scale structure is strongly constrained by the accuracy with which one can measure galaxy shapes. Several methods have been devised but none has demonstrated the ability to reach the level of precision required by future weak lensing surveys. In this paper, we explore new avenues to the existing 'Shapelets' approach, combining a priori knowledge of the galaxy profile with the power of orthogonal basis function decomposition. This paper discusses the new issues raised by this matched filter approach and proposes promising alternatives to shape measurement techniques. In particular, it appears that the use of a matched filter (e.g. Sérsic profile) restricted to elliptical radial fitting functions resolves several well-known Shapelet issues. 相似文献
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Deformation and strength characteristics of the soil of Sana'a, the Yemen Arab Republic, were investigated. Undisturbed soil samples were collected fro used in consolidation, collapse and strength tests. The classical and critical state compressibility parameters were determined using a one-dimensional collapsing potential of the investigated soil was determined by using both qualitative and quantitative analysis. Consolidated undrained triaxial tests different types of samples: saturated samples and samples at natural moisture content. The stress history of the fine soils are in the range of normal except for the stiff fissured lean clay which exhibited a relatively high overconsolidated stress history. The loess formations exhibited a moderate to under wetting and loading. The investigated soils are characterized by having high shear strength when they have low moisture content and a drastic dec content increases. 相似文献
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The potential mineralization and immobilization of soil nitrogen (N), phosphorus (P) and sulfur (S) are relatively high in natural ecosystems. This study was conducted to investigate the changes in essential plant macronutrients; N, P, and S status in response to different soil depth in rangeland ecosystems in vitro. The net nutrient mineralization was measured during 90 days at different depths (0–15, 15–30, 30–45 and 45–60 cm), using kinetic models to estimate the release rate. The net ammonification and mineralization of P and S were described using parabolic diffusion equation, while the power function equation was used to describe the net nitrification. The results indicated that the amount of released ammonium (NH4 +) decreased with time and depth and the rates of net ammonification were negative in all samples. Conversely, nitrification increased with time and depth and the rates were all positive. The net mineralization for both P and S reduced with time. The concentration of mineralized SO4 2? increased with depth like nitrate (NO3 ?). Accumulation of SO4 2? and NO3 ? in subsurface soils and NH4 + and P at surface horizons can increase the potential of their loss by leaching or volatilization. 相似文献
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This study challenges the use of three nature‐inspired algorithms as learning frameworks of the adaptive‐neuro‐fuzzy inference system (ANFIS) machine learning model for short‐term modeling of dissolved oxygen (DO) concentrations. Particle swarm optimization (PSO), butterfly optimization algorithm (BOA), and biogeography‐based optimization (BBO) are employed for developing predictive ANFIS models using seasonal 15 min data collected from the Rock Creek River in Washington, DC. Four independent variables are used as model inputs including water temperature (T), river discharge (Q), specific conductance (SC), and pH. The Mallow's Cp and R2 parameters are used for choosing the best input parameters for the models. The models are assessed by several statistics such as the coefficient of determination (R2), root‐mean‐square error (RMSE), Nash–Sutcliffe efficiency, mean absolute error, and the percent bias. The results indicate that the performance of all‐nature‐inspired algorithms is close to each other. However, based on the calculated RMSE, they enhance the accuracy of standard ANFIS in the spring, summer, fall, and winter around 13.79%, 15.94%, 6.25%, and 12.74%, respectively. Overall, the ANFIS‐PSO and ANFIS‐BOA provide slightly better results than the other ANFIS models. 相似文献