Hybrid high-order methods for flow simulations in extremely large discrete fracture networks

Ern, Alexandre; Hédin, Florent; Pichot, Géraldine; Pignet, Nicolas

doi:10.5802/smai-jcm.92

Ern, Alexandre ¹ ; Hédin, Florent ² ; Pichot, Géraldine ² ; Pignet, Nicolas ³

¹ Université Paris-Est, CERMICS (ENPC), 6 et 8 av. Blaise Pascal, 77455 Marne-la-Vallée Cedex 2, France and Inria, 2 rue Simone Iff, 75589 Paris, France
² Inria, 2 rue Simone Iff, 75589 Paris, France and Université Paris-Est, CERMICS (ENPC), 6 et 8 av. Blaise Pascal, 77455 Marne-la-Vallée Cedex 2, France
³ EDF Lab Paris-Saclay, 7 boulevard Gaspard Monge, 91120 Palaiseau, France

The SMAI Journal of computational mathematics, Tome 8 (2022), pp. 375-398.

Résumé

We investigate the computational performance of hybrid high-order methods applied to flow simulations in extremely large discrete fracture networks (over one million of fractures). We study the choice of basis functions, the trade-off between increasing the polynomial order and refining the mesh, and how to take advantage of polygonal cells to reduce the number of degrees of freedom.

Publié le : 2023-03-31

DOI : 10.5802/smai-jcm.92

Classification : 65N30, 65N50, 86A05
Mots clés : discrete fracture networks, flow simulations, hybrid high-order methods

Affiliations des auteurs :

Ern, Alexandre ¹ ; Hédin, Florent ² ; Pichot, Géraldine ² ; Pignet, Nicolas ³

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     author = {Ern, Alexandre and H\'edin, Florent and Pichot, G\'eraldine and Pignet, Nicolas},
     title = {Hybrid high-order methods for flow simulations in extremely large discrete fracture networks},
     journal = {The SMAI Journal of computational mathematics},
     pages = {375--398},
     publisher = {Soci\'et\'e de Math\'ematiques Appliqu\'ees et Industrielles},
     volume = {8},
     year = {2022},
     doi = {10.5802/smai-jcm.92},
     language = {en},
     url = {http://www.numdam.org/articles/10.5802/smai-jcm.92/}
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Ern, Alexandre; Hédin, Florent; Pichot, Géraldine; Pignet, Nicolas. Hybrid high-order methods for flow simulations in extremely large discrete fracture networks. The SMAI Journal of computational mathematics, Tome 8 (2022), pp. 375-398. doi : 10.5802/smai-jcm.92. http://www.numdam.org/articles/10.5802/smai-jcm.92/

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