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Simulation of solute transport through heterogeneous networks: analysis using the method of moments and the statistics of local transport characteristics

机译:通过异质网络模拟溶质运移:使用矩量法分析和局部运移特征统计

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We used a time domain random walk approach to simulate passive solute transport in networks. In individual pores, solute transport was modeled as a combination of Poiseuille flow and Taylor dispersion. The solute plume data were interpreted via the method of moments. Analysis of the first and second moments showed that the longitudinal dispersivity increased with increasing coefficient of variation of the pore radii CV and decreasing pore coordination number Z. The third moment was negative and its magnitude grew linearly with time, meaning that the simulated dispersion was intrinsically non-Fickian. The statistics of the Eulerian mean fluid velocities $${hat{{oldsymbol{u}}}}_{{oldsymbol{i}}}$$ u ? i , the Taylor dispersion coefficients $${hat{{oldsymbol{D}}}}_{{oldsymbol{i}}}$$ D ? i and the transit times $${hat{{oldsymbol{au }}}}_{{oldsymbol{i}}}$$ τ ? i were very complex and strongly affected by CV and Z. In particular, the probability of occurrence of negative velocities grew with increasing CV and decreasing Z. Hence, backward and forward transit times had to be distinguished. The high-τ branch of the transit-times probability curves had a power law form associated to non-Fickian behavior. However, the exponent was insensitive to pore connectivity, although variations of Z affected the third moment growth. Thus, we conclude that both the low- and high-τ branches played a role in generating the observed non-Fickian behavior.
机译:我们使用时域随机游走方法来模拟网络中的被动溶质传输。在单个孔中,溶质运移被建模为泊瓦斯流和泰勒分散的组合。溶羽数据通过矩量法解释。对第一和​​第二阶矩的分析表明,纵向弥散度随孔隙半径CV的变化系数的增加和孔隙配位数Z的减小而增大。第三阶矩为负,其幅度随时间线性增长,这意味着模拟弥散本来就是本征非菲克欧拉平均流体速度的统计信息$ {u {{hat {boldsymbol {u}}}} __ {{ boldsymbol {i}}} $$ u? i,泰勒色散系数$$ { hat {{ boldsymbol {D}}}} _ {{ boldsymbol {i}}}} $$ D? i和运输时间$$ { hat {{ boldsymbol { tau}}}} __ {{ boldsymbol {i}}}} $$τ?我非常复杂,并且受CV和Z的影响很大。特别是,出现负速度的可能性随CV的增加和Z的减小而增加。因此,必须区分前进和后退的穿越时间。运输时间概率曲线的高τ分支具有与非菲克行为相关的幂定律形式。然而,该指数对孔连通性不敏感,尽管Z的变化影响了第三矩的增长。因此,我们得出结论,低和高τ分支都在生成观察到的非菲克行为中起作用。

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