dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport. dfnWorks is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfnGen, which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

References in zbMATH (referenced in 23 articles )

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  1. Benedetto, M. F.; Borio, A.; Kyburg, F.; Mollica, J.; Scialò, S.: An arbitrary order mixed virtual element formulation for coupled multi-dimensional flow problems (2022)
  2. Krotz, Johannes; Sweeney, Matthew R.; Gable, Carl W.; Hyman, Jeffrey D.; Restrepo, Juan M.: Variable resolution Poisson-disk sampling for meshing discrete fracture networks (2022)
  3. Zulian, Patrick; Schädle, Philipp; Karagyaur, Liudmila; Nestola, Maria G. C.: Comparison and application of non-conforming mesh models for flow in fractured porous media using dual Lagrange multipliers (2022)
  4. Berrone, Stefano; Borio, Andrea; D’Auria, Alessandro; Scialò, Stefano; Vicini, Fabio: A robust VEM-based approach for flow simulations in poro-fractured media (2021)
  5. Berrone, Stefano; Vicini, Fabio: A reduced basis method for a PDE-constrained optimization formulation in discrete fracture network flow simulations (2021)
  6. Borio, Andrea; Fumagalli, Alessio; Scialò, Stefano: Comparison of the response to geometrical complexity of methods for unstationary simulations in discrete fracture networks with conforming, polygonal, and non-matching grids (2021)
  7. Keilegavlen, Eirik; Berge, Runar; Fumagalli, Alessio; Starnoni, Michele; Stefansson, Ivar; Varela, Jhabriel; Berre, Inga: PorePy: an open-source software for simulation of multiphysics processes in fractured porous media (2021)
  8. Ushijima-Mwesigwa, Hayato; Hyman, Jeffrey D.; Hagberg, Aric; Safro, Ilya; Karra, Satish; Gable, Carl W.; Sweeney, Matthew R.; Srinivasan, Gowri: Multilevel graph partitioning for three-dimensional discrete fracture network flow simulations (2021)
  9. Osthus, Dave; Hyman, Jeffrey D.; Karra, Satish; Panda, Nishant; Srinivasan, Gowri: A probabilistic clustering approach for identifying primary subnetworks of discrete fracture networks with quantified uncertainty (2020)
  10. Srinivasan, Shriram; Cawi, Eric; Hyman, Jeffrey; Osthus, Dave; Hagberg, Aric; Viswanathan, Hari; Srinivasan, Gowri: Physics-informed machine learning for backbone identification in discrete fracture networks (2020)
  11. Sweeney, Matthew R.; Gable, Carl W.; Karra, Satish; Stauffer, Philip H.; Pawar, Rajesh J.; Hyman, Jeffrey D.: Upscaled discrete fracture matrix model (UDFM): an octree-refined continuum representation of fractured porous media (2020)
  12. Berrone, S.; Scialò, S.; Vicini, F.: Parallel meshing, discretization, and computation of flow in massive discrete fracture networks (2019)
  13. Fourno, André; Ngo, Tri-Dat; Noetinger, Benoit; La Borderie, Christian: FraC: a new conforming mesh method for discrete fracture networks (2019)
  14. Fumagalli, Alessio; Keilegavlen, Eirik; Scialò, Stefano: Conforming, non-conforming and non-matching discretization couplings in discrete fracture network simulations (2019)
  15. Berrone, S.; Borio, A.; Fidelibus, C.; Pieraccini, S.; Scialò, S.; Vicini, F.: Advanced computation of steady-state fluid flow in discrete fracture-matrix models: FEM-BEM and VEM-VEM fracture-block coupling (2018)
  16. Fumagalli, Alessio; Keilegavlen, Eirik: Dual virtual element method for discrete fractures networks (2018)
  17. Hyman, Jeffrey D.; Hagberg, Aric; Osthus, Dave; Srinivasan, Shriram; Viswanathan, Hari; Srinivasan, Gowri: Identifying backbones in three-dimensional discrete fracture networks: a bipartite graph-based approach (2018)
  18. Srinivasan, Shriram; Hyman, Jeffrey; Karra, Satish; O’Malley, Daniel; Viswanathan, Hari; Srinivasan, Gowri: Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics (2018)
  19. Valera, Manuel; Guo, Zhengyang; Kelly, Priscilla; Matz, Sean; Cantu, Vito Adrian; Percus, Allon G.; Hyman, Jeffrey D.; Srinivasan, Gowri; Viswanathan, Hari S.: Machine learning for graph-based representations of three-dimensional discrete fracture networks (2018)
  20. Berrone, Stefano; Pieraccini, Sandra; Scialò, Stefano: Flow simulations in porous media with immersed intersecting fractures (2017)

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