共查询到20条相似文献，搜索用时 31 毫秒
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Thomas Willingham Changyong Zhang Charles J. Werth Albert J. Valocchi Mart Oostrom Thomas W. Wietsma 《Advances in water resources》2010
A key challenge for predictive modeling of transverse mixing and reaction of solutes in groundwater is to determine values of transverse dispersivity (αT) in heterogeneous flow fields that accurately describe mixing and reaction at the pore scale. We evaluated the effects of flow focusing in high permeability zones on mixing enhancement using experimental micromodel flow cells and pore-scale lattice-Boltzmann-finite-volume model (LB-FVM) simulations. Micromodel results were directly compared to LB-FVM simulations using two different pore structures, and excellent agreement was obtained. Six different flow focusing pore structures were then systematically tested using LB-FVM, and both analytical solutions and a two-dimensional (2D) continuum-scale model were used to fit αT values to pore-scale results. Pore-scale results indicate that the overall rate of mixing-limited reaction increased by up to 40% when flow focusing occurred, and it was greater in pore structures with longer flow focusing regions and greater porosity contrast. For each pore structure, αT values from analytical solutions of transverse concentration profiles or total product at a given longitudinal location showed good agreement for nonreactive and reactive solutes, and values determined in flow focusing zones were always smaller than those downgradient after the flow focusing zone. Transverse dispersivity values from the 2D continuum model were between values within and downgradient from the flow focusing zone determined from analytical solutions. Also, total product and transverse concentration profiles along the entire pore structure from the 2D continuum model matched pore scale results. These results indicate that accurate quantification of pore-scale flow focusing with transverse dispersion coefficients is possible only when the entire flow and concentration fields are considered. 相似文献
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Zhi-Ping Mei François J. Saucier Vincent Le Fouest Bruno Zakardjian Simon Sennville Huixiang Xie Michel Starr 《Continental Shelf Research》2010
The effects of colored dissolved organic matter (CDOM) from freshwater runoff and seasonal cycle of temperature on the dynamic of phytoplankton and zooplankton biomass and production in the Gulf of St. Lawrence (GSL) are studied using a 3-D coupled physical-plankton ecosystem model. Three simulations are conducted: (1) the reference simulation based on Le Fouest et al. (2005), in which light attenuation by CDOM is not considered and maximum growth rate (μmax) of phytoplankton and zooplankton are not temperature-dependent (REF simulation); (2) light attenuation by CDOM is added to REF simulation (CDOM simulation); and (3) in addition to CDOM, the μmax of phytoplankton and zooplankton are regulated by temperature (CDOM+TEMP simulation). CDOM simulation shows that CDOM substantially reduces phytoplankton biomass and production in the Lower St. Lawrence Estuary (LSLE), but slightly reduces overall primary production in the GSL. In the LSLE, the spring phytoplankton bloom is delayed from mid-March to mid-April, resulted from light attenuation by CDOM. The CDOM+TEMP simulation shows that the spring phytoplankton bloom in the LSLE is further delayed to July, which is more consistent with observations. Annual primary production is reduced by 33% in CDOM+TEMP simulation from REF and CDOM simulations. Zooplankton production is the same in all three simulations, and export of organic matter to depth is reduced in CDOM+TEMP simulation, suggesting that temperature controlled growth of phytoplankton and zooplankton enhances the coupling between primary production and zooplankton production under the seasonal temperature cycle of the GSL. 相似文献
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This study focuses on the development of a next generation multiobjective evolutionary algorithm (MOEA) that can learn and exploit complex interdependencies and/or correlations between decision variables in monitoring design applications to provide more robust performance for large problems (defined in terms of both the number of objectives and decision variables). The proposed MOEA is termed the epsilon-dominance hierarchical Bayesian optimization algorithm (ε-hBOA), which is representative of a new class of probabilistic model building evolutionary algorithms. The ε-hBOA has been tested relative to a top-performing traditional MOEA, the epsilon-dominance nondominated sorted genetic algorithm II (ε-NSGAII) for solving a four-objective LTM design problem. A comprehensive performance assessment of the ε-NSGAII and various configurations of the ε-hBOA have been performed for both a 25 well LTM design test case (representing a relatively small problem with over 33 million possible designs), and a 58 point LTM design test case (with over 2.88×1017 possible designs). The results from this comparison indicate that the model building capability of the ε-hBOA greatly enhances its performance relative to the ε-NSGAII, especially for large monitoring design problems. This work also indicates that decision variable interdependencies appear to have a significant impact on the overall mathematical difficulty of the monitoring network design problem. 相似文献
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Field and laboratory measurements of suspended sediments over wave ripples show, for time-averaged concentration profiles in semi-log plots, a contrast between upward convex profiles for fine sand and upward concave profiles for coarse sand. Careful examination of experimental data for coarse sand shows a near-bed upward convex profile beneath the main upward concave profile. Available models fail to predict these two profiles for coarse sediments. The 1-DV gradient diffusion model predicts the main upward concave profile for coarse sediments thanks to a suitable β(y)-function (where β is the inverse of the turbulent Schmidt number and y is the distance from the bed). In order to predict the near-bed upward convex profile, an additional parameter α is needed. This parameter could be related to settling velocity (α equal to inverse of dimensionless settling velocity) or to convective sediment entrainment process. The profiles are interpreted by a relation between second derivative of the logarithm of concentration and derivative of the product between sediment diffusivity and α. 相似文献
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Two equivalent permeability tensors are defined for 3D heterogeneous media, Kp and Kq, valid respectively for linear pressure and constant flux conditions at the block boundary. Both tensors are symmetric and positive-definite and the second one produces lower magnitude of directional permeability than the first one. These tensors only depends upon the internal block structure and 3D distribution of the local permeability values. On this basis, we develop first a straightforward method for evaluating the coefficients of the 2D tensor for the problem of flow through fracture traces in a cross-section, subject to linear pressure conditions. A quartzite rock mass is used as an example to illustrate this method. Then, an approximated method is proposed to build up the 3D permeability tensor of the fractured block from the ellipses within cross-sections in varied orientations. 相似文献
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In this study, a probabilistic collocation method (PCM) on sparse grids is used to solve stochastic equations describing flow and transport in three-dimensional, saturated, randomly heterogeneous porous media. The Karhunen–Loève decomposition is used to represent log hydraulic conductivity Y=lnKs. The hydraulic head h and average pore-velocity v are obtained by solving the continuity equation coupled with Darcy’s law with random hydraulic conductivity field. The concentration is computed by solving a stochastic advection–dispersion equation with stochastic average pore-velocity v computed from Darcy’s law. The PCM approach is an extension of the generalized polynomial chaos (gPC) that couples gPC with probabilistic collocation. By using sparse grid points in sample space rather than standard grids based on full tensor products, the PCM approach becomes much more efficient when applied to random processes with a large number of random dimensions. Monte Carlo (MC) simulations have also been conducted to verify accuracy of the PCM approach and to demonstrate that the PCM approach is computationally more efficient than MC simulations. The numerical examples demonstrate that the PCM approach on sparse grids can efficiently simulate solute transport in randomly heterogeneous porous media with large variances. 相似文献