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Collaborative Research: Data-enabled Modeling, Numerical Method, and Data Assimilation for Coupling Dual Porosity Flow with Free Flow

Collaborative Research: Data-enabled Modeling, Numerical Method, and Data Assimilation for Coupling Dual Porosity Flow with Free Flow
协作研究:双孔隙流动与自由流动​​耦合的数据建模、数值方法和数据同化
批准号:
1722692
负责人:
Craig Douglas
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2021-07-31

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中文摘要
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英文摘要
The coupling of dual porosity flow and free flow arises in many important applications. However, the existing Stokes-Darcy types of models cannot accurately describe this type of coupled problem since they only consider single porosity media. Therefore, with the support of lab experiment data, the PIs develop a new coupled multi-physics multi-scale model and the corresponding numerical methods for accurately describing this coupling. Furthermore, both the lab and field datum provide the possibility to improve the accuracy of the model prediction through data assimilation. This project provides students many valuable training opportunities in data-enabled modeling, development of numerical methods and code packages, data assimilation, mathematical analysis, and engineering applications. They can gain solid foundation in computational math and data science, valuable research experience, and extensive collaboration experience with engineers. Starting from this collaboration work, the investigators plan to disseminate the proposed model, methods, and packages to more engineers and scientists for solving their realistic problems, present the work in professional conferences and colloquia, and organize special sessions in conferences for related works. Moreover, this project is part of the expansion of the computational and applied mathematics program and Missouri Institute for Computational and Applied Mathematical Sciences at Missouri S&T. This department-oriented expansion will benefit the entire engineering-based university and help state of Missouri enhance its relatively less active research in computational mathematics. At the University of Wyoming, the mathematics and statistics departments are merging in 2017 with a new emphasis on data sciences, mathematics, and statistics. This project will provide an immediate boost to the data science initiative and provide a justification for recruiting new students, scientists, and faculty.It is challenging to propose appropriate interface conditions for the new model in order to couple the two flows in a physically valid way. Moreover, coupling two constituent models leads to a complex system involving different scales in the dual porosity flow and the free flow, which demands accurate and efficient numerical methods. The use of existing data to improve the model prediction will even further increase the complexity and computational cost by a significant amount due to the big amount of data and iterative feature of the data assimilation methods. When the nonlinearity, time-dependence, realistic interface/boundary conditions, and data information interact with each other in a dynamic system, the whole system becomes much more complicated and much larger in computational scale. Therefore, significant challenges still remain for the intricate multi-physics multi-scale model to couple the dual porosity flow with the free flow. This project proposes a dual-porosity-Navier-Stokes model with the support of lab experiment data, develops the decoupled non-iterative multi-physics domain decomposition method with optimal convergence rates, study the variational data assimilation method with a newly defined cost function for improving the interface model prediction, carries out the mathematical analysis for the model and the numerical methods, and applies them to one or two applications. This research dynamically combines all of these components into a hybrid system of research and development that will take full advantage of the inherent relationship between the novel mathematical modeling/methods/analysis and the practical engineering advances in validation/data assimilation/applications, hence will lay the groundwork for reliable modeling of many applications involving complex flow in fractured porous media with highly-conductive conduits.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
Deadlock Detection in MPI Programs Using Static Analysis and Symbolic Execution
使用静态分析和符号执行进行 MPI 程序中的死锁检测
DOI: --
发表时间: 2018
期刊: Lecture notes in computer science
影响因子: --
作者: [Douglas, Craig C., Krishnamoorthy, Krishnan]
通讯作者: Krishnamoorthy, Krishnan
DOI: 10.1007/978-3-030-50433-5_6
发表时间: 2020-05-25
期刊: Computational Science – ICCS 2020
影响因子: --
作者: [Hu X, Douglas CC]
通讯作者: Douglas CC
CC*DNI Engineer: Big Data Enabler for the UW-DMZ
  • 批准号:
    1541392
  • 项目类别:
    Standard Grant
  • 资助金额:
    $36.63万
  • 财政年份:
    2015
  • 负责人:
    Craig Douglas
  • 依托单位:
CC*IIE Networking Infrastructure: Enabling Scientific Discovery through a UW-DMZ
  • 批准号:
    1440610
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2014
  • 负责人:
    Craig Douglas
  • 依托单位:
Workshop on Dynamic Data-Driven Applications Systems (DDDAS) - InfoSymbiotic Systems
  • 批准号:
    1057753
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.0万
  • 财政年份:
    2010
  • 负责人:
    Craig Douglas
  • 依托单位:
CSR-CSI: Collaborative Research: Dynamic Sensor/Computation Network for Wildfire Management
  • 批准号:
    1018079
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.86万
  • 财政年份:
    2009
  • 负责人:
    Craig Douglas
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)