课题基金 / 基金详情

Developing Novel Numerical Methods for Flow and Transport in Porous Media

Developing Novel Numerical Methods for Flow and Transport in Porous Media
开发多孔介质中流动和传输的新型数值方法
批准号:
1419077
负责人:
Jiangguo Liu
金额:
$12.0万
依托单位:
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
项目状态:
已结题
起止时间:
2014-09-01 至 2018-08-31

项目摘要

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中文摘要
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英文摘要
Flow and transport in porous media arise from a wide variety of real world problems such as oil recovery, groundwater contaminant remediation, CO2 sequestration, wildfire, magma transport through the Earth crust, and viral protein trafficking inside host cells. All these problems have tremendous economic, environmental, medical, and social significance. Mathematical modeling and computer simulations will provide efficient and inexpensive tools to enhance our abilities in understanding, predicting, and controlling the aforementioned problems. Scientific challenges abound in the modeling and simulations of flow and transport, due to the heterogeneity and anisotropy of the media, multiple spatial and temporal scales, and uncertainty in these processes. This research project aims at developing a new class of efficient and robust numerical methods for coupled flow and transport problems. These methods will be implemented as computer software modules that can be used for a broad range of scientific computing tasks. This project will also provide hands-on training opportunities for graduate students, especially those from underrepresented groups.Specifically, this project focuses on development of novel finite element methods for solving coupled flow and transport problems in porous media. This will be accomplished by combining the weak Galerkin (WG) and Eulerian-Lagrangian approaches. The WG approach establishes a new type of approximations of differential operators by using degrees of freedom in element interiors as well as those on mesh skeleton. WG finite element schemes could offer preferred features such as local conservation and symmetric positive-definite discrete linear systems. The Eulerian-Lagrangian approach efficiently utilizes the flow information and produces small temporal truncation errors. This enables robust long-time simulations of transport problems. By incorporating these two approaches, the PI and collaborators will design, analyze, and implement a family of new finite element methods for solving the Darcy equation, convection-dominated transport equations, the miscible displacement problem, and two-phase flow problems. These new methods overcome disadvantages of existing methods but maintain those well-received advantages, for example, local conservation. Software modules (a Matlab toolbox and C++ libraries based on PETSc) will be developed to put these new methods into practical uses. PhD students will be trained through this project to gain integrated capabilities of mathematical modeling and algorithm development for challenging real world problems.
期刊论文(1)
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科研奖励(0)
会议论文
Machine learning and transport simulations for groundwater anomaly detection
用于地下水异常检测的机器学习和传输模拟
DOI: 10.1016/j.cam.2020.112982
发表时间: 2020
期刊: Journal of Computational and Applied Mathematics
影响因子: 2.4
作者: [Liu, Jiangguo, Gu, Jianli, Li, Huishu, Carlson, Kenneth H.]
通讯作者: Carlson, Kenneth H.
Developing Efficient and Robust Computational Tools for Subdiffusive Transport in Poroelastic Media
  • 批准号:
    2208590
  • 项目类别:
    Standard Grant
  • 资助金额:
    $23.49万
  • 财政年份:
    2022
  • 负责人:
    Jiangguo Liu
  • 依托单位:
Developing Efficient and Accessible Computational Tools for Poroelasticity Problems
  • 批准号:
    1819252
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.99万
  • 财政年份:
    2018
  • 负责人:
    Jiangguo Liu
  • 依托单位:
New techniques in characteristic finite element methods for flow problems
  • 批准号:
    0915253
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.84万
  • 财政年份:
    2009
  • 负责人:
    Jiangguo Liu
  • 依托单位:
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novel-miR75靶向OPR2,CA2和STK基因调控人参真菌胁迫响应的分子机制研究
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  • 项目类别:
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海南广藿香Novel17-GSO1响应p-HBA调控连作障碍的分子机制
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  • 项目类别:
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  • 资助金额:
    30万元
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白术多糖通过novel-mir2双靶向TRADD/MLKL缓解免疫抑制雏鹅的胸腺程序性坏死
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    32102747
  • 项目类别:
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  • 资助金额:
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