CAREER: Fundamental Controls of Transport Attributes from Porous Media Microstructure

职业：多孔介质微观结构输运属性的基本控制

基本信息

批准号：
1847689
负责人：
Veronica Morales
金额：
$ 50万
依托单位：
University of California-Davis
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-02-15 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1847689&HistoricalAwards=false
关键词：
CAREER Fundamental Controls Transport Attributes

项目摘要

Clean groundwater, a primary source of drinking water for many people, is a valuable Earth resource. Risks of groundwater contamination frequently arise from natural, agricultural, or industrial activities. To preserve the safety of these drinking water sources, it is crucial to understand how contaminants are expected to move and spread underground. An important factor that influences the movement of contaminants is the variability of the void spaces in soil and rocks known as pores. Complex flow patterns arise as groundwater moves through intricate pores of different shapes and sizes, which make predictions of flow complicated. Many mathematical predictions of groundwater flow ignore the complex variability in pores. This oversimplification results in a large discrepancy between flow predictions and observations. The central scientific goal of this project is to better understand how contaminant movement is controlled by measurable features of the pores. The first step of this project will statistically identify the most relevant attributes of pores that effectively describe flow in rock. The second step will apply this relationship to develop a new mathematical model of flow and contaminant movement. Collectively, this work will deliver more accurate tools to predict contaminant movement and to help protect water resources. The project will train students and water managers through the development of an interactive web-based tool designed to allow users to understand and manipulate groundwater flow in a virtual environment.Solving the flow and mass transport through heterogeneous porous media is central to many technological applications spanning groundwater remediation, oil recovery, and geotechnical engineering. The approaches to do so are currently limited, because the required calculations become computationally expensive as accuracy and domain size increase. The central scientific goal of this project is to establish a formal quantitative relationship that explains how local fluid velocities and overall flow arrangement are controlled by spatially correlated variations of geometric pore characteristics. This association would enable predicting non-Gaussian velocity distributions from relevant statistical descriptors of the pore space alone, which in turn can be used to predict effective transport. Finding this elusive link will lead to significant improvements in predictive capabilities for groundwater flow and contaminant transport in heterogeneous porous systems of arbitrary domain size. To achieve this goal, the proposed work will first statistically identify how velocity variations are induced by the physical attributes of the underlying pore space in digitally-scanned rock samples of diverse heterogeneities. These virtual data contain detailed information of the structure, the flow and the transport. Next, the newly-determined pore structure-flow relation will be integrated into the leading modeling framework for anomalous transport behavior and assessed for performance. The main educational goal is to enhance student understanding about how groundwater flows and how contaminants spread in it. This will be done through the development of interactive web tools for non-experts (targeting high-school, college and continued education students) that can be used in flipped-classroom environments. The interactive tool design allows the user to manipulate groundwater models, explore the results as automatically-generated graphics, and discover answers to their own questions in a self-directed application of the scientific method.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.

干净的地下水是许多人的主要饮用水来源，是宝贵的地球资源。地下水污染的风险通常来自自然，农业或工业活动。为了保留这些饮用水源的安全性，至关重要的是要了解污染物如何在地下移动和扩散。影响污染物运动的一个重要因素是土壤和岩石中的空隙空间的变化。随着地下水在不同形状和大小的复杂孔中移动时，复杂的流动模式就会产生，从而使流动的预测变得复杂。地下水流的许多数学预测忽略了孔中的复杂变异性。这种过度简化导致流动预测和观测之间存在很大的差异。该项目的主要科学目标是更好地了解污染物运动如何受孔的可测量特征控制。该项目的第一步将从统计上确定有效描述岩石流动的毛孔的最相关属性。第二步将应用这种关系来开发一种新的流动和污染物运动的数学模型。总的来说，这项工作将提供更准确的工具，以预测污染物的运动并帮助保护水资源。该项目将通过开发基于互动Web的工具来培训学生和水管理人员，旨在使用户在虚拟环境中理解和操纵地下水流程。通过异质的多孔培养基来溶解流量和大规模运输对于许多技术应用是跨越地下水补救，石油恢复和地理技术工程的许多技术应用的核心。目前，这样做的方法是有限的，因为随着准确性和域大小的增加，所需的计算在计算上变得昂贵。该项目的主要科学目标是建立形式的定量关系，该关系解释了局部流体速度和整体流动排列如何受到几何孔特征的空间相关变化的控制。该关联将使仅孔隙空间的相关统计描述符预测非高斯速度分布，这反过来又可用于预测有效的运输。找到这种难以捉摸的链接将导致地下水流量的预测能力显着提高，并在任意域大小的异质多孔系统中的地下水流量和污染物转运。为了实现这一目标，拟议的工作将首先从统计学上确定如何通过不同异质性的数字扫描岩石样本中基础孔隙空间的物理属性引起的速度变化。这些虚拟数据包含结构，流量和传输的详细信息。接下来，新确定的孔结构 - 流相关关系将集成到针对异常运输行为的领先建模框架中，并评估了性能。主要的教育目标是增强学生对地下水流动方式以及污染物如何散布的理解。这将通过开发用于非专家的交互式网络工具（针对高中，大学和持续教育学生），这些工具可用于翻转的教室环境。交互式工具设计使用户可以操纵地下水模型，探索自动生成图形的结果，并在科学方法的自我指导的应用中发现其自己问题的答案。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子和宽广的影响来评估的支持，并被视为值得通过评估的支持。