Collaborative Research: Hybrid Modeling of Reactive Transport in Porous and Fractured Media

合作研究：多孔和断裂介质中反应输运的混合建模

• 批准号: 1461608
• 负责人: Ilenia Battiato
• 金额: $ 12.64万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-13 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1461608&HistoricalAwards=false
• 关键词: Collaborative; Research; Hybrid; Modeling; Reactive

Subsurface flow and transport take place in complex heterogeneous environments that exhibit a hierarchy of scales. More often than not, physical and bio-geochemical phenomena on one scale (e.g., a pore scale) affect, and are coupled to phenomena on a vastly different scale (e.g., a field scale). Such phenomena defy coarse-scale continuum descriptions, since they exhibit high localization (e.g., propagation of reactive fronts and biofilm growth) and/or strong nonlinear coupling between the processes involved (e.g., dynamic changes in porosity and permeability due to dissolution or precipitation). Hybrid numerical algorithms are to be used when coarse-scale continuum models fail to accurately describe a physical phenomenon in a small part of a computational domain. Accurate and efficient coupling of two (or more) models operating on vastly different spatial and/or temporal scales in a hybrid remains a major theoretical and computational challenge. A key to the success of a hybrid method is an efficient implementation of coupling conditions on the interface between its constitutive models. Additionally, uncertainty about pore geometry undermines the veracity of pore-scale simulations and, hence, of hybrid simulations of which they are a constitutive part. Overreaching goals of the proposed activity are to establish a theoretical foundation for hybrid modeling of subsurface flow and transport, to develop corresponding numerical algorithms, and to provide computational tools for robust uncertainty quantification in hybrid models. To achieve these goals, the investigators will develop hybrid algorithms for reactive flows in fractured and porous media, quantify uncertainty in pore-scale geometry in hybrid simulations, and experimentally validate hybrid simulations. In terms of broader impact, this proposal will enhance sustainability of essential water resources. Groundwater is a principal source of domestic water supply in the United States, and it is a major source of fresh water for industrial, agricultural and public uses. By establishing a novel modeling framework, this proposal will provide a scientific basis for reliable predictions of impacts of land use change and climate change, and more accurate assessments of groundwater contamination risks. The methods and algorithms developed in the course of the proposed activity will lay a solid foundation for improved quantitative understanding of subsurface processes with tightly coupled pore- and field-scales. The proposal will support the efforts of graduate students. The investigators will actively promote STEM career paths of underrepresented groups, and establish an outreach K-12 program dedicated to providing an intensive college prep education for motivated low-income students.

地下流动和运输发生在复杂的异构环境中，呈现出尺度层次结构。通常，一种尺度（例如，孔隙尺度）的物理和生物地球化学现象会影响并耦合到截然不同尺度（例如，油田尺度）的现象。这种现象违背了粗尺度的连续描述，因为它们表现出高度局部化（例如，反应前沿的传播和生物膜生长）和/或所涉及过程之间的强非线性耦合（例如，由于溶解或沉淀而导致的孔隙度和渗透率的动态变化）。当粗尺度连续体模型无法准确描述计算域一小部分中的物理现象时，将使用混合数值算法。在混合体中在截然不同的空间和/或时间尺度上运行的两个（或更多）模型的准确和有效耦合仍然是主要的理论和计算挑战。混合方法成功的关键是在其本构模型之间的接口上有效实现耦合条件。此外，孔隙几何形状的不确定性破坏了孔隙尺度模拟的准确性，因此也破坏了作为其组成部分的混合模拟的准确性。该活动的总体目标是为地下流动和传输的混合建模建立理论基础，开发相应的数值算法，并为混合模型中鲁棒的不确定性量化提供计算工具。为了实现这些目标，研究人员将开发用于裂缝和多孔介质中反应流的混合算法，量化混合模拟中孔隙尺度几何形状的不确定性，并通过实验验证混合模拟。就更广泛的影响而言，该提案将增强基本水资源的可持续性。地下水是美国生活供水的主要来源，也是工业、农业和公共用途淡水的主要来源。通过建立新颖的建模框架，该提案将为可靠预测土地利用变化和气候变化的影响以及更准确地评估地下水污染风险提供科学依据。在所提出的活动过程中开发的方法和算法将为提高对孔隙和现场尺度紧密耦合的地下过程的定量理解奠定坚实的基础。该提案将支持研究生的努力。研究人员将积极促进代表性不足群体的 STEM 职业道路，并建立一个 K-12 外展计划，致力于为有积极性的低收入学生提供强化大学预科教育。