PFLOTRAN

PFLOTRAN User manual: A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes. PFLOTRAN is an open source, state-of-the-art massively parallel subsurface flow and reactive transport code. PFLOTRAN solves a system of generally nonlinear partial differential equations describing multiphase, multicomponent and multiscale reactive flow and transport in porous materials. The code is designed to run on massively parallel computing architectures as well as workstations and laptops. Parallelization is achieved through domain decomposition using the PETSc (Portable Extensible Toolkit for Scientific Computation) libraries. PFLOTRAN has been developed from the ground up for parallel scalability and has been run on up to 2^18 processor cores with problem sizes up to 2 billion degrees of freedom. PFLOTRAN is written in object oriented, free formatted Fortran 2003. The choice of Fortran over C/C++ was based primarily on the need to enlist and preserve tight collaboration with experienced domain scientists, without which PFLOTRAN’s sophisticated process models would not exist.The reactive transport equations can be solved using either a fully implicit Newton-Raphson algorithm or the less robust operator splitting method.


References in zbMATH (referenced in 34 articles )

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  1. Cui, Xin; Wong, Louis Ngai Yuen: A 3D fully thermo-hydro-mechanical coupling model for saturated poroelastic medium (2022)
  2. Hyman, Jeffrey D.; Sweeney, Matthew R.; Gable, Carl W.; Svyatsky, Daniil; Lipnikov, Konstantin; Moulton, J. David: Flow and transport in three-dimensional discrete fracture matrix models using mimetic finite difference on a conforming multi-dimensional mesh (2022)
  3. Knodel, Markus M.; Kräutle, Serge; Knabner, Peter: Global implicit solver for multiphase multicomponent flow in porous media with multiple gas components and general reactions. Global implicit solver for multiple gas components (2022)
  4. 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)
  5. Kyas, Svetlana; Volpatto, Diego; Saar, Martin O.; Leal, Allan M. M.: Accelerated reactive transport simulations in heterogeneous porous media using Reaktoro and Firedrake (2022)
  6. Ahmmed, B.; Mudunuru, M. K.; Karra, S.; James, S. C.; Vesselinov, V. V.: A comparative study of machine learning models for predicting the state of reactive mixing (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. Koch, Timo; Gläser, Dennis; Weishaupt, Kilian; Ackermann, Sina; Beck, Martin; Becker, Beatrix; Burbulla, Samuel; Class, Holger; Coltman, Edward; Emmert, Simon; Fetzer, Thomas; Grüninger, Christoph; Heck, Katharina; Hommel, Johannes; Kurz, Theresa; Lipp, Melanie; Mohammadi, Farid; Scherrer, Samuel; Schneider, Martin; Seitz, Gabriele; Stadler, Leopold; Utz, Martin; Weinhardt, Felix; Flemisch, Bernd: DuMu(^\textx 3) -- an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling (2021)
  9. Kuhlman, Kristopher L.; Malama, Bwalya: Uncoupling electrokinetic flow solutions (2021)
  10. Poonoosamy, J.; Wanner, C.; Alt Epping, P.; Águila, J. F.; Samper, J.; Montenegro, L.; Xie, M.; Su, D.; Mayer, K. U.; Mäder, U.; van Loon, L. R.; Kosakowski, G.: Benchmarking of reactive transport codes for 2D simulations with mineral dissolution-precipitation reactions and feedback on transport parameters (2021)
  11. Su, Danyang; Mayer, K. Ulrich; MacQuarrie, Kerry T. B.: MIN3P-HPC: a high-performance unstructured grid code for subsurface flow and reactive transport simulation (2021)
  12. 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)
  13. Damiani, Leonardo Hax; Kosakowski, Georg; Glaus, Martin A.; Churakov, Sergey V.: A framework for reactive transport modeling using FEniCS-Reaktoro: governing equations and benchmarking results (2020)
  14. Guérillot, Dominique; Bruyelle, Jérémie: Geochemical equilibrium determination using an artificial neural network in compositional reservoir flow simulation (2020)
  15. 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)
  16. 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)
  17. 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)
  18. Fourno, André; Ngo, Tri-Dat; Noetinger, Benoit; La Borderie, Christian: FraC: a new conforming mesh method for discrete fracture networks (2019)
  19. Srinivasan, Shriram; Karra, Satish; Hyman, Jeffrey; Viswanathan, Hari; Srinivasan, Gowri: Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways (2019)
  20. Burstedde, Carsten; Fonseca, Jose A.; Kollet, Stefan: Enhancing speed and scalability of the ParFlow simulation code (2018)

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