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A new <i>ϕ</i>‐FEM approach for problems with natural boundary conditions

Michel Duprez, Vanessa Lleras, Alexei Lozinski

2022Numerical Methods for Partial Differential Equations14 citationsDOIOpen Access PDF

Abstract

Abstract We present a new finite element method, called ‐FEM, to solve numerically elliptic partial differential equations with natural (Neumann or Robin) boundary conditions using simple computational grids, not fitted to the boundary of the physical domain. The boundary data are taken into account using a level‐set function, which is a popular tool to deal with complicated or evolving domains. Our approach belongs to the family of fictitious domain methods (or immersed boundary methods) and is close to recent methods of CutFEM/XFEM type. Contrary to the latter, ‐FEM does not need any nonstandard numerical integration on cut mesh elements or on the actual boundary, while assuring the optimal convergence orders with finite elements of any degree and providing reasonably well conditioned discrete problems. In the first version of ‐FEM, only essential (Dirichlet) boundary conditions was considered. Here, to deal with natural boundary conditions, we introduce the gradient of the primary solution as an auxiliary variable. This is done only on the mesh cells cut by the boundary, so that the size of the numerical system is only slightly increased. We prove theoretically the optimal convergence of our scheme and a bound on the discrete problem conditioning, independent of the mesh cuts. The numerical experiments confirm these results.

Topics & Concepts

MathematicsFinite element methodRobin boundary conditionNeumann boundary conditionBoundary value problemBoundary (topology)Mixed boundary conditionBoundary knot methodDirichlet boundary conditionMathematical analysisExtended finite element methodConvergence (economics)Applied mathematicsBoundary element methodEconomicsThermodynamicsEconomic growthPhysicsNumerical methods in engineeringAdvanced Numerical Methods in Computational MathematicsLattice Boltzmann Simulation Studies