scispace - formally typeset
K

Konstantin Brenner

Researcher at French Institute for Research in Computer Science and Automation

Publications -  46
Citations -  763

Konstantin Brenner is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Discretization & Finite volume method. The author has an hindex of 13, co-authored 43 publications receiving 635 citations. Previous affiliations of Konstantin Brenner include Centre national de la recherche scientifique & University of Nice Sophia Antipolis.

Papers
More filters
Journal ArticleDOI

Finite volume approximation for an immiscible two-phase flow in porous media with discontinuous capillary pressure

TL;DR: In this paper, the authors considered an immiscible incompressible two-phase flow in a porous medium composed of two different rocks so that the capillary pressure field is discontinuous at the interface between the rocks.
Journal ArticleDOI

Gradient discretization of hybrid-dimensional Darcy flow in fractured porous media with discontinuous pressures at matrix-fracture interfaces

TL;DR: In this article, the authors investigated the discretization of Darcy flow through fractured porous media on general meshes, and they considered a hybrid dimensional model, invoking a complex network of planar fractures.
Journal ArticleDOI

Gradient discretization of hybrid dimensional Darcy flows in fractured porous media

TL;DR: In this article, the convergence analysis is carried out in the framework of gradient schemes which accounts for a large family of conforming and nonconforming discretizations of hybrid dimensional Darcy flows in fractured porous media.
Journal ArticleDOI

Hybrid-dimensional modelling of two-phase flow through fractured porous media with enhanced matrix fracture transmission conditions

TL;DR: This work extends, to two-phase flow, the single-phase Darcy flow model proposed in [26], [12] in which the (d − 1)-dimensional flow in the fractures is coupled with the d-dimensionalflow in the matrix, leading to deep insight about the quality of the proposed reduced models.