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A forward particle tracking Eulerian Lagrangian Localized Adjoint Method for multicomponent reactive transport modelling of biodegradation

机译:用于生物降解的多组分反应运输建模的前向粒子跟踪欧拉拉格朗日局部伴随方法

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A solution of the contaminant transport equation obtained with the forward particle tracking Eulerian Lagrangian Localised Adjoint Method (ELLAM) is coupled via Strang operator splitting to a modified Monod microbial kinetics model for simulating biodegradation. The model includes substrate, oxygen, and biomass concentrations. The reaction equations are solved using a predictor corrector algorithm with adaptive time stepping and adjustment of time step size near the inflow boundary. The method is benchmarked against the direct ELLAM solution of Wang et al. (1995) for the test problem of Celia et al. (1989). The split operator approach is shown to be competitive with the direct solution for simple test problems and is expected to have better performance for more complex multi-component systems. Nonlinear regression using a shuffled complex evolution algorithm is then used to fit the transport and biodegradation model to column experiment data. A Metropolis algorithm is used for uncertainty analysis. These inverse methods were employed in a case study of aniline substrate depletion data from laboratory scale column experiments using pristine aquifer material from CFB Borden, Ontario as a microbial population source under aerobic conditions. Results show that the transport and biodegradation model parameters were uniquely identified when fitted to the aniline and oxygen concentration data from the column experiment.
机译:与正向粒子跟踪欧拉拉格朗日本地化伴随方法(ELLAM)中获得的污染物输运方程中的溶液经由斯特朗算子分裂耦合到用于模拟生物降解的改性的Monod微生物动力学模型。该模型包括基板,氧和生物量浓度。反应方程使用具有自适应时间步进和流入边界附近的时间步长大小的调整的预测校正算法得到解决。该方法针对基准王等人的直接ELLAM解决方案。 (1995),用于西莉亚等人的试验问题。 (1989)。拆分操作方法证明是与简单的测试问题,直接的解决方案竞争力,预计将有更多的复杂的多组分体系更好的性能。然后用混洗复杂进化算法的非线性回归来拟合的运输和生物降解模型柱实验数据。一个大都市算法用于不确定性分析。在使用原始含水层的材料从CFB博登,安大略如在有氧条件下微生物群体源实验室规模的柱实验苯胺底物耗尽数据的案例研究中所用的这些逆方法。结果表明,当装配到从塔实验苯胺和氧浓度数据的传输和生物降解模型参数唯一地识别。

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