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Fast and robust flow simulations in discrete fracture networks with GPGPUs

  • S. BerroneEmail author
  • A. D’Auria
  • F. Vicini
Original Paper
Part of the following topical collections:
  1. Numerical methods for processes in fractured porous media

Abstract

A new approach for flow simulation in very complex discrete fracture networks based on PDE-constrained optimization has been recently proposed in Berrone et al. (SIAM J Sci Comput 35(2):B487–B510, 2013b; J Comput Phys 256:838–853, 2014) with the aim of improving robustness with respect to geometrical complexities. This is an essential issue, in particular for applications requiring simulations on geometries automatically generated like the ones used for uncertainty quantification analyses and hydro-mechanical simulations. In this paper, implementation of this approach in order to exploit Nvidia Compute Unified Device Architecture is discussed with the main focus to speed up the linear algebra operations required by the approach, being this task the most computational demanding part of the approach. Furthermore, two different approaches for linear algebra operations and two storage formats for sparse matrices are compared in terms of computational efficiency and memory constraints.

Keywords

Discrete fracture network flow simulations Simulations in complex geometries GPGPU CUDA 

Mathematics Subject Classification

65N30 68U20 68W10 68W40 86-08 86A05 

Notes

References

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Dipartimento di Scienze MatematichePolitecnico di TorinoTurinItaly

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