用RetroPy v1.0验证反应驱动流动条件下的能斯特-普朗克输运模型

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Po-Wei Huang, B. Flemisch, C. Qin, M. Saar, A. Ebigbo
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引用次数: 1

摘要

摘要自然环境中的反应传输过程通常涉及许多离子物种。离子物质的扩散率各不相同。由于在平流-扩散方程中分配不同的扩散率会导致电荷不平衡,因此通常对所有物种使用单一的扩散率。在这项工作中,我们应用能斯特-普朗克方程来模拟反应输运,该方程以电中性的方式解决了物种的不平等扩散率。为了证明能斯特-普朗克模型的优势,我们将能斯特-Planck模型与常用的单扩散率模型在反应驱动流动条件下的输运模拟结果进行了比较。所有模拟还与厘米尺度上定义明确的实验进行了比较。我们的结果表明,能斯特-普朗克模型是有效的,尤其适用于模拟扩散、反应、电迁移和密度驱动对流之间复杂相互作用的反应输运过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
Abstract. Reactive transport processes in natural environments often involve many ionic species. The diffusivities of ionic species vary. Since assigning different diffusivities in the advection–diffusion equation leads to charge imbalance, a single diffusivity is usually used for all species. In this work, we apply the Nernst–Planck equation, which resolves unequal diffusivities of the species in an electroneutral manner, to model reactive transport. To demonstrate the advantages of the Nernst–Planck model, we compare the simulation results of transport under reaction-driven flow conditions using the Nernst–Planck model with those of the commonly used single-diffusivity model. All simulations are also compared to well-defined experiments on the scale of centimeters. Our results show that the Nernst–Planck model is valid and particularly relevant for modeling reactive transport processes with an intricate interplay among diffusion, reaction, electromigration, and density-driven convection.
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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