CAREER: Predicting Transport, Mixing, and Reaction in Three-dimensional Heterogeneous Fractured Media Across Scales

职业：跨尺度预测三维异质断裂介质中的传输、混合和反应

• 批准号: 2046015
• 负责人: Peter Kang
• 金额: $ 58.03万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2046015&HistoricalAwards=false
• 关键词: CAREER; Predicting; Transport; Mixing; Reaction

About 99% of global unfrozen freshwater is stored in groundwater systems, and about 75% of near-surface groundwater aquifers on earth are fractured. Recent field studies have shown the presence of emerging contaminants such as microplastics, viruses, and harmful bacteria in groundwater, and fractures are often major pathways through which contaminants migrate long distances at anomalously fast rates. However, conventional groundwater models ignore fracture flow, and as a result, often fail to predict contaminant transport in the subsurface. To secure sustainable water resources, there is urgent need for a new model that predicts flow and transport in fractured media. This project presents an integrated research, education, and outreach plan that will advance the current practices of modeling fractured media and teaching fractured rock hydrogeology. This project will first combine visual laboratory experiments and direct numerical simulations to elucidate fundamental physical laws that govern flow and transport at single fracture scales. The identified key single-fracture scale processes will then be incorporated into field-scale models. Finally, the developed models will be validated through field experiments at a fractured aquifer site. The project has three major outreach and teaching activities that are directly synergistic with the proposed research: (i) a professional hydrogeologists’ working group will be formed to bridge the gap between academia, industry, and government agencies in the area of fractured rock hydrogeology, (ii) visual groundwater teaching tools will be developed for K-12 and college-level education, and lastly (iii) accessible modules based on a contaminated fractured aquifer site will be developed for a new urban field course.Conventional groundwater models often treat aquifers as two-dimensional continuous porous media, thereby missing critical complexities that govern flow and transport in fractured aquifers. Recent studies have shown that complex three-dimensional (3D) flows can alter the overall mixing and reaction dynamics up to the field scale, but the underlying processes and how they scale up in fracture networks are still not well understood. This project will establish a mechanistic understanding of 3D flow effects on Transport, Mixing, and Reaction (TMR) at single-fracture scales and translate that knowledge across scales to predict processes at fracture network scales. This project first combines visual laboratory experiments and direct numerical simulations to elucidate how the interplay between fracture heterogeneity (e.g., fracture roughness and aperture variability) and flow boundary conditions (Reynolds number) controls 3D flows and TMR at single fracture scales. The single-fracture scale processes will then be incorporated into fracture network-scale models, and an upscaled modeling framework that predicts TMR will be developed. A comprehensive data set will be generated and analyzed with machine-learning-based methods to yield a powerful map that links upscaled model parameters to key medium properties and flow conditions. The developed upscaled model will be validated through controlled field tracer experiments at a fractured aquifer site. Overall, this project will transform how we understand and model fractured media and will provide a new foundation for modeling coupled biogeochemistry and fluid flow.This proposal is co-funded by the Hydrologic Sciences and Education and Human Resources programs in the Division of Earth Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

全球约99%的未冻淡水储存在地下水系统中，地球上约75%的近地表地下水含水层是裂缝性的。最近的实地研究表明，地下水中存在新出现的污染物，如微塑料，病毒和有害细菌，裂缝通常是污染物以极快的速度长距离迁移的主要途径。然而，传统的地下水模型忽略了裂隙流，因此，往往无法预测污染物在地下的传输。为了确保可持续的水资源，迫切需要一个新的模型，预测在裂隙介质中的流动和运输。该项目提出了一项综合研究、教育和外展计划，将推进裂缝介质建模和裂缝岩石水文地质学教学的当前实践。该项目将首先结合联合收割机可视化实验室实验和直接数值模拟，以阐明在单一裂缝尺度下控制流动和运输的基本物理定律。确定的关键单裂缝规模的过程，然后将被纳入现场规模的模型。最后，开发的模型将通过现场实验在裂隙含水层网站进行验证。该项目有三个主要的推广和教学活动，与拟议的研究直接协同：（i）将成立一个专业水文地质学家工作组，以弥合学术界、工业界和政府机构之间在断裂岩石水文地质学领域的差距，（ii）将为K-12和大学教育开发可视化地下水教学工具，最后（iii）可访问模块的基础上污染的裂隙含水层网站将开发一个新的城市领域course.Conventional地下水模型往往把含水层作为二维连续多孔介质，从而错过了关键的复杂性，管理流和运输裂隙含水层。最近的研究表明，复杂的三维（3D）流动可以改变整体的混合和反应动力学领域的规模，但基本的过程，以及它们如何在裂缝网络的规模仍然没有得到很好的理解。该项目将建立在单裂缝尺度上的运输，混合和反应（TMR）的3D流动效应的机械理解，并将该知识跨尺度转化为裂缝网络尺度的预测过程。该项目首先将可视化实验室实验和直接数值模拟相结合，以阐明裂缝非均质性（例如，裂缝粗糙度和孔径可变性）和流动边界条件（雷诺数）控制单裂缝尺度下的3D流动和TMR。然后将单裂缝尺度过程纳入裂缝网络尺度模型，并开发预测TMR的升级建模框架。将使用基于机器学习的方法生成和分析一个全面的数据集，以生成一个强大的地图，将放大的模型参数与关键介质特性和流动条件联系起来。开发的放大模型将通过控制现场示踪剂实验在裂隙含水层网站进行验证。总的来说，该项目将改变我们对裂隙介质的理解和建模方式，并将为耦合地球化学和流体流动的建模提供新的基础。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响进行评估，被认为值得支持审查标准。

项目成果

Inertia and diffusion effects on reactive transport with fluid-solid reactions in rough fracture flows

• DOI: 10.1103/physrevfluids.8.054502
• 发表时间: 2023-05
• 期刊: Physical Review Fluids
• 影响因子: 2.7
• 作者: Wee Sun Lee;Seonkyoo Yoon;P. Kang

Predicting Remediation Efficiency of LNAPLs using Surrogate Polynomial Chaos Expansion Model and Global Sensitivity Analysis

• DOI: 10.1016/j.advwatres.2022.104179
• 发表时间: 2022-03
• 期刊: Advances in Water Resources
• 影响因子: 4.7
• 作者: Taehoon Kim;W. Han;J. Piao;P. Kang;Jehyun Shin