Numerical analysis and a-posteriori error control for a new nonconforming quadrilateral linear finite element

Size: px
Start display at page:

Download "Numerical analysis and a-posteriori error control for a new nonconforming quadrilateral linear finite element"

Transcription

1 Numerical analysis and a-posteriori error control for a new nonconforming quadrilateral linear finite element M. Grajewski, J. Hron, S. Turek Matthias.Grajewski@math.uni-dortmund.de, jaroslav.hron@math.uni-dortmund.de, stefan.turek@math.uni-dortmund.de Institut für Angewandte Mathematik und Numerik, LS3, Universität Dortmund, Germany p.1/21

2 structure of the talk 1. Introduction of the P 1 -element 2. Numerical analysis of P 1 3. Dual-weighted a-posteriori error-control p.2/21

3 basic observations By connecting the midpoints of an arbitrary quadrilateral, one gets a parallelogram. p.3/21

4 basic observations By connecting the midpoints of an arbitrary quadrilateral, one gets a parallelogram. u P 1 u(m 1 ) + u(m 3 ) = u(m 2 ) + u(m 4 ) u m1 + u m3 = u m2 + u m4!u P 1 : u(m i ) = u mi p.3/21

5 definition of P 1 v j : vertex, m i : edge midpoint M(j) := {i N Γ T : mi Γ v j Γ} v j p.4/21

6 definition of P 1 v j : vertex, m i : edge midpoint M(j) := {i N Γ T : mi Γ v j Γ} v j Φ j (m i ) = { 1, i M(j) 0, else,φ j P 1 (T) p.4/21

7 definition of P 1 v j : vertex, m i : edge midpoint M(j) := {i N Γ T : mi Γ v j Γ} v j Φ j (m i ) = { 1, i M(j) 0, else,φ j P 1 (T) P 1 (T) := { v : Ω R F Γ (v) = v(m Γ ) (continuity constraint) v T P 1 (T) T T vcont. w.r.t. F Γ } p.4/21

8 P 1 basis function Φ (0,0) p.5/21

9 theorem (Park) Ω simply connected with polygonal boundary, T triangulation of Ω with N vertices, 0 < ĵ N p.6/21

10 theorem (Park) Ω simply connected with polygonal boundary, T triangulation of Ω with N vertices, 0 < ĵ N dim P 1 (T) = N 1. p.6/21

11 theorem (Park) Ω simply connected with polygonal boundary, T triangulation of Ω with N vertices, 0 < ĵ N dim P 1 (T) = N 1. {Φ j j {1..., N} \ {ĵ}} basis of P 1 (T) p.6/21

12 theorem (Park) Ω simply connected with polygonal boundary, T triangulation of Ω with N vertices, 0 < ĵ N dim P 1 (T) = N 1. {Φ j j {1..., N} \ {ĵ}} basis of P 1 (T) ( u, ϕ) Ω + (cu, ϕ) Ω + (u, ϕ) Ω = (f, ϕ) Ω + (g, ϕ) Ω ϕ H 1 (Ω). p.6/21

13 theorem (Park) Ω simply connected with polygonal boundary, T triangulation of Ω with N vertices, 0 < ĵ N dim P 1 (T) = N 1. {Φ j j {1..., N} \ {ĵ}} basis of P 1 (T) ( u, ϕ) Ω + (cu, ϕ) Ω + (u, ϕ) Ω = (f, ϕ) Ω + (g, ϕ) Ω ϕ H 1 (Ω). u u h 0 Ch 2 u 2, if g H1( Ω), f L 2 (Ω) 2 p.6/21

14 Dirichlet boundary cond. I (Park) u h (m j ) = c j + c j+1 ( ) p.7/21

15 Dirichlet boundary cond. I (Park) u h (m j ) = c j + c j+1 ( ) and dim P 1 (T) = N 1 p.7/21

16 Dirichlet boundary cond. I (Park) u h (m j ) = c j + c j+1 ( ) and dim P 1 (T) = N 1 explicit boundary treatment : fix one arbitrary coefficient per boundary component compute recursively the coefficients on the boundary according to (*) p.7/21

17 Dirichlet boundary cond. II p.8/21

18 Dirichlet boundary cond. II u h and coefficient vector of u h p.8/21

19 Dirichlet boundary cond. II u h and coefficient vector of u h p.8/21

20 comparison with other elements Test problem: u = 10, u Ω = 0 e h l2 := u u h l2 := ( 1 N ) 1/2 N u(v i ) u h (v i ) 2 i=1 NEL e h l2, Q 1 red. e h l2, Q 1 red. e h l2, P 1 red p.9/21

21 Dirichlet boundary cond. III observation: multiply connected domains and explicit boundary treatment: e h 0 = O(h) p.10/21

22 Dirichlet boundary cond. III observation: multiply connected domains and explicit boundary treatment: e h 0 = O(h) lemma Let us assume that u = α. If for one arbitrary T T holds c 1 + c 3 = c 2 + c 4, then: c 1 + c 3 = c 2 + c 4 T and representation is oscillationfree p.10/21

23 Dirichlet boundary cond. III observation: multiply connected domains and explicit boundary treatment: e h 0 = O(h) lemma Let us assume that u = α. If for one arbitrary T T holds c 1 + c 3 = c 2 + c 4, then: c 1 + c 3 = c 2 + c 4 T and representation is oscillationfree implicit boundary treatment : for one element on the first boundary component, apply c 1 + c 3 = c 2 + c 4 for all other boundary edges, apply u(m j ) = c j + c j+1 p.10/21

24 Dirichlet boundary cond. III observation: multiply connected domains and explicit boundary treatment: e h 0 = O(h) lemma Let us assume that u = α. If for one arbitrary T T holds c 1 + c 3 = c 2 + c 4, then: c 1 + c 3 = c 2 + c 4 T and representation is oscillationfree implicit boundary treatment : remark: for one element on the first boundary component, apply c 1 + c 3 = c 2 + c 4 for all other boundary edges, apply u(m j ) = c j + c j+1 on tensor product grids : Lemma even holds for linear functions with implicit boundary treatment: error of boundary treatment can be O(h 3 ) p.10/21

25 Dirichlet boundary cond. IV L 2 -error of computation of u = x + 1 and reduction rates of the error NEL implicit red. explicit red p.11/21

26 matrix structure standard treatment via elimination (in rows only) in Q 1 and Q 1 (left) P 1 with explicit boundary treatment (middle) P 1 with implicit boundary treatment (right) p.12/21

27 iterative solvers for P 1 problem : implicit boundary treatment affects solver behaviour example : square in the channel, u(x, y) = x(x 1)(1 y)y 2 sin(x + 2y), solver: BiCGStab NEL ILU(0) ILU(0) sort ILU(1) ILU(1) sort >10000 > p.13/21

28 P 1 not LBB-stable problem: P 1 does not fulfill the LBB-condition: Ω = [0,1] 2, T tensor product grid, u(x, y) = (y, 0), p(x, y) = const. p.14/21

29 P 1 not LBB-stable problem: P 1 does not fulfill the LBB-condition: Ω = [0,1] 2, T tensor product grid, u(x, y) = (y, 0), p(x, y) = const. observation: checkerboard oscillation of the pressure problem: P 1 does not fulfill Korn s inequality (analogous to the Q 1 -case according to Knobloch) p.14/21

30 fast matrix assembly advantage: extremely fast matrix assembly possible: 1-point Gauss rule exact nonparametric transformation for P 1 as fast as parametric one par par NEL P 1, G 1 P 1, G 2 P1,G 1 P1, G 2 Qpar 1, G 2 Q 1, G 2 133, s , s ,129, s remark: for Q 1 : 2 2-Gauss rule necessary for Douglas-element (enhanced Q 1 ): even 3 3-Gauss necessary! p.15/21

31 a-posteriori error control (conforming case) a(u, ϕ) := ( u, ϕ) = (f, ϕ) ϕ V := H0(Ω) 1 wanted: upper bound of the error of an output quantity J( ) Becker, Rannacher: dual problem ( ϕ, z) = J(ϕ) ϕ H 1 0(Ω) p.16/21

32 a-posteriori error control (conforming case) a(u, ϕ) := ( u, ϕ) = (f, ϕ) ϕ V := H0(Ω) 1 wanted: upper bound of the error of an output quantity J( ) Becker, Rannacher: dual problem ( ϕ, z) = J(ϕ) ϕ H 1 0(Ω) J(e h ) = a(e h, z) p.16/21

33 a-posteriori error control (conforming case) a(u, ϕ) := ( u, ϕ) = (f, ϕ) ϕ V := H0(Ω) 1 wanted: upper bound of the error of an output quantity J( ) Becker, Rannacher: dual problem ( ϕ, z) = J(ϕ) ϕ H 1 0(Ω) J(e h ) = a(e h, z) = ( u }{{} + u h, z z h ) T 1 2 ([ nu h ], z z h ) T T T =f p.16/21

34 a posteriori error control (nonconf. case) problem 1: e h V, as u h V J(e h ) =? remedy: dual problem defined by (ϕ, z) = J(ϕ) ϕ L 2 (Ω), z H 2 (Ω) p.17/21

35 a posteriori error control (nonconf. case) problem 1: e h V, as u h V J(e h ) =? remedy: dual problem defined by (ϕ, z) = J(ϕ) ϕ L 2 (Ω), z H 2 (Ω) problem 2: Galerkin-orthogonality : V V h too small for z h remedy: element enhacing by (parametric) bulb function ϕ B (x, y) = xy z C h p.17/21

36 a posteriori error control (nonconf. case) problem 1: e h V, as u h V J(e h ) =? remedy: dual problem defined by (ϕ, z) = J(ϕ) ϕ L 2 (Ω), z H 2 (Ω) problem 2: Galerkin-orthogonality : V V h too small for z h remedy: element enhacing by (parametric) bulb function ϕ B (x, y) = xy z C h J(e h ) = T T { (f + u N h, z zh C }{{} ) T 1 2 ([ nu N h ], z zc h ) T =0 1 } 2 ([un h ], nz) T + a h (e h, zh C ) p.17/21

37 practical aspects observation: consistency error a h (e h, z C h ) = O(h4 ) for Laplace equation u N h P 1 (T) : u N h = 0 replace z (unknown) by z I obtained by patchwise biquadratic interpolation of z h in nonconformity term ([u N h ], nz) T : n z replaced by n z := 0.5( n z h T1 + n z h T2 ) p.18/21

38 practical aspects lemma: observation: consistency error a h (e h, z C h ) = O(h4 ) for Laplace equation u N h P 1 (T) : u N h = 0 replace z (unknown) by z I obtained by patchwise biquadratic interpolation of z h in nonconformity term ([u N h ], nz) T : n z replaced by n z := 0.5( n z h T1 + n z h T2 ) T T : ([u N h ], nz N h ) T = 0 p.18/21

39 practical aspects lemma: observation: consistency error a h (e h, z C h ) = O(h4 ) for Laplace equation u N h P 1 (T) : u N h = 0 replace z (unknown) by z I obtained by patchwise biquadratic interpolation of z h in nonconformity term ([u N h ], nz) T : n z replaced by n z := 0.5( n z h T1 + n z h T2 ) error estimation: T T : ([u N h ], nz N h ) T = 0 J(e h ) η(e h ) := (f, z I zh C ) T 1 2 ([ nu N h ], z I zh C ) T T T p.18/21

40 numerical test I square in a channel, analytical solution, point error in (0.35, 0.5) NEL J r (0.35,0.5) (e h ) η(e h ) I eff p.19/21

41 numerical test II DFG-benchmark-grid cylinder in channel, u = 10, u Ω = 0, J(ϕ) = Ω c u n ds NEL J Γ (e h ) η(e h ) I eff p.20/21

42 conclusion advantages of P 1 simplest nonconforming quadrilateral element optimal approximation order very fast matrix assembly (for parametric and non-parametric trafo) fast solvers possible rigorous a-posteriori error control open problems multigrid stabilization for mixed formulation problems (CFD) realistic applications p.21/21

A note on accurate and efficient higher order Galerkin time stepping schemes for the nonstationary Stokes equations

A note on accurate and efficient higher order Galerkin time stepping schemes for the nonstationary Stokes equations A note on accurate and efficient higher order Galerkin time stepping schemes for the nonstationary Stokes equations S. Hussain, F. Schieweck, S. Turek Abstract In this note, we extend our recent work for

More information

Scientific Computing WS 2017/2018. Lecture 18. Jürgen Fuhrmann Lecture 18 Slide 1

Scientific Computing WS 2017/2018. Lecture 18. Jürgen Fuhrmann Lecture 18 Slide 1 Scientific Computing WS 2017/2018 Lecture 18 Jürgen Fuhrmann juergen.fuhrmann@wias-berlin.de Lecture 18 Slide 1 Lecture 18 Slide 2 Weak formulation of homogeneous Dirichlet problem Search u H0 1 (Ω) (here,

More information

Newton-Multigrid Least-Squares FEM for S-V-P Formulation of the Navier-Stokes Equations

Newton-Multigrid Least-Squares FEM for S-V-P Formulation of the Navier-Stokes Equations Newton-Multigrid Least-Squares FEM for S-V-P Formulation of the Navier-Stokes Equations A. Ouazzi, M. Nickaeen, S. Turek, and M. Waseem Institut für Angewandte Mathematik, LSIII, TU Dortmund, Vogelpothsweg

More information

Goal-oriented error control of the iterative solution of finite element equations

Goal-oriented error control of the iterative solution of finite element equations J. Numer. Math., Vol. 0, No. 0, pp. 1 31 (2009) DOI 10.1515/ JNUM.2009.000 c de Gruyter 2009 Prepared using jnm.sty [Version: 20.02.2007 v1.3] Goal-oriented error control of the iterative solution of finite

More information

Simple Examples on Rectangular Domains

Simple Examples on Rectangular Domains 84 Chapter 5 Simple Examples on Rectangular Domains In this chapter we consider simple elliptic boundary value problems in rectangular domains in R 2 or R 3 ; our prototype example is the Poisson equation

More information

Scientific Computing WS 2018/2019. Lecture 15. Jürgen Fuhrmann Lecture 15 Slide 1

Scientific Computing WS 2018/2019. Lecture 15. Jürgen Fuhrmann Lecture 15 Slide 1 Scientific Computing WS 2018/2019 Lecture 15 Jürgen Fuhrmann juergen.fuhrmann@wias-berlin.de Lecture 15 Slide 1 Lecture 15 Slide 2 Problems with strong formulation Writing the PDE with divergence and gradient

More information

PREPRINT 2010:23. A nonconforming rotated Q 1 approximation on tetrahedra PETER HANSBO

PREPRINT 2010:23. A nonconforming rotated Q 1 approximation on tetrahedra PETER HANSBO PREPRINT 2010:23 A nonconforming rotated Q 1 approximation on tetrahedra PETER HANSBO Department of Mathematical Sciences Division of Mathematics CHALMERS UNIVERSITY OF TECHNOLOGY UNIVERSITY OF GOTHENBURG

More information

Chapter Two: Numerical Methods for Elliptic PDEs. 1 Finite Difference Methods for Elliptic PDEs

Chapter Two: Numerical Methods for Elliptic PDEs. 1 Finite Difference Methods for Elliptic PDEs Chapter Two: Numerical Methods for Elliptic PDEs Finite Difference Methods for Elliptic PDEs.. Finite difference scheme. We consider a simple example u := subject to Dirichlet boundary conditions ( ) u

More information

Weierstraß-Institut. für Angewandte Analysis und Stochastik. im Forschungsverbund Berlin e.v. Preprint ISSN

Weierstraß-Institut. für Angewandte Analysis und Stochastik. im Forschungsverbund Berlin e.v. Preprint ISSN Weierstraß-Institut für Angewandte Analysis und Stochastik im Forschungsverbund Berlin e.v. Preprint ISSN 946 8633 Computational comparison between the Taylor Hood and the conforming Crouzeix Raviart element

More information

1. Fast Iterative Solvers of SLE

1. Fast Iterative Solvers of SLE 1. Fast Iterative Solvers of crucial drawback of solvers discussed so far: they become slower if we discretize more accurate! now: look for possible remedies relaxation: explicit application of the multigrid

More information

Lecture 9 Approximations of Laplace s Equation, Finite Element Method. Mathématiques appliquées (MATH0504-1) B. Dewals, C.

Lecture 9 Approximations of Laplace s Equation, Finite Element Method. Mathématiques appliquées (MATH0504-1) B. Dewals, C. Lecture 9 Approximations of Laplace s Equation, Finite Element Method Mathématiques appliquées (MATH54-1) B. Dewals, C. Geuzaine V1.2 23/11/218 1 Learning objectives of this lecture Apply the finite difference

More information

Numerical Solution I

Numerical Solution I Numerical Solution I Stationary Flow R. Kornhuber (FU Berlin) Summerschool Modelling of mass and energy transport in porous media with practical applications October 8-12, 2018 Schedule Classical Solutions

More information

Goal-oriented error control of the iterative solution of finite element equations

Goal-oriented error control of the iterative solution of finite element equations J. Numer. Math., Vol. 17, No. 2, pp. 143 172 (2009) DOI 10.1515/ JNUM.2009.009 c de Gruyter 2009 Goal-oriented error control of the iterative solution of finite element equations D. MEIDNER, R. RANNACHER,

More information

An interpolation operator for H 1 functions on general quadrilateral and hexahedral meshes with hanging nodes

An interpolation operator for H 1 functions on general quadrilateral and hexahedral meshes with hanging nodes An interpolation operator for H 1 functions on general quadrilateral and hexahedral meshes with hanging nodes Vincent Heuveline Friedhelm Schieweck Abstract We propose a Scott-Zhang type interpolation

More information

Universität Dortmund UCHPC. Performance. Computing for Finite Element Simulations

Universität Dortmund UCHPC. Performance. Computing for Finite Element Simulations technische universität dortmund Universität Dortmund fakultät für mathematik LS III (IAM) UCHPC UnConventional High Performance Computing for Finite Element Simulations S. Turek, Chr. Becker, S. Buijssen,

More information

Numerical Benchmarking of Fluid-Structure Interaction: A comparison of different discretization and solution approaches

Numerical Benchmarking of Fluid-Structure Interaction: A comparison of different discretization and solution approaches Numerical Benchmarking of Fluid-Structure Interaction: A comparison of different discretization and solution approaches Stefan Turek, Jaroslav Hron, Mudassar Razzaq, Hilmar Wobker, and Michael Schäfer

More information

Projection Theorem 1

Projection Theorem 1 Projection Theorem 1 Cauchy-Schwarz Inequality Lemma. (Cauchy-Schwarz Inequality) For all x, y in an inner product space, [ xy, ] x y. Equality holds if and only if x y or y θ. Proof. If y θ, the inequality

More information

AMS 529: Finite Element Methods: Fundamentals, Applications, and New Trends

AMS 529: Finite Element Methods: Fundamentals, Applications, and New Trends AMS 529: Finite Element Methods: Fundamentals, Applications, and New Trends Lecture 3: Finite Elements in 2-D Xiangmin Jiao SUNY Stony Brook Xiangmin Jiao Finite Element Methods 1 / 18 Outline 1 Boundary

More information

Multigrid Methods and their application in CFD

Multigrid Methods and their application in CFD Multigrid Methods and their application in CFD Michael Wurst TU München 16.06.2009 1 Multigrid Methods Definition Multigrid (MG) methods in numerical analysis are a group of algorithms for solving differential

More information

1. Let a(x) > 0, and assume that u and u h are the solutions of the Dirichlet problem:

1. Let a(x) > 0, and assume that u and u h are the solutions of the Dirichlet problem: Mathematics Chalmers & GU TMA37/MMG800: Partial Differential Equations, 011 08 4; kl 8.30-13.30. Telephone: Ida Säfström: 0703-088304 Calculators, formula notes and other subject related material are not

More information

The Plane Stress Problem

The Plane Stress Problem The Plane Stress Problem Martin Kronbichler Applied Scientific Computing (Tillämpad beräkningsvetenskap) February 2, 2010 Martin Kronbichler (TDB) The Plane Stress Problem February 2, 2010 1 / 24 Outline

More information

Scientific Computing II

Scientific Computing II Technische Universität München ST 008 Institut für Informatik Dr. Miriam Mehl Scientific Computing II Final Exam, July, 008 Iterative Solvers (3 pts + 4 extra pts, 60 min) a) Steepest Descent and Conjugate

More information

Proposal for numerical benchmarking of fluid-structure interaction between an elastic object and laminar incompressible flow

Proposal for numerical benchmarking of fluid-structure interaction between an elastic object and laminar incompressible flow Proposal for numerical benchmarking of fluid-structure interaction between an elastic object and laminar incompressible flow Stefan Turek and Jaroslav Hron Institute for Applied Mathematics and Numerics,

More information

An Iterative Substructuring Method for Mortar Nonconforming Discretization of a Fourth-Order Elliptic Problem in two dimensions

An Iterative Substructuring Method for Mortar Nonconforming Discretization of a Fourth-Order Elliptic Problem in two dimensions An Iterative Substructuring Method for Mortar Nonconforming Discretization of a Fourth-Order Elliptic Problem in two dimensions Leszek Marcinkowski Department of Mathematics, Warsaw University, Banacha

More information

Adaptive Finite Element Methods Lecture Notes Winter Term 2017/18. R. Verfürth. Fakultät für Mathematik, Ruhr-Universität Bochum

Adaptive Finite Element Methods Lecture Notes Winter Term 2017/18. R. Verfürth. Fakultät für Mathematik, Ruhr-Universität Bochum Adaptive Finite Element Methods Lecture Notes Winter Term 2017/18 R. Verfürth Fakultät für Mathematik, Ruhr-Universität Bochum Contents Chapter I. Introduction 7 I.1. Motivation 7 I.2. Sobolev and finite

More information

Discontinuous Galerkin Methods

Discontinuous Galerkin Methods Discontinuous Galerkin Methods Joachim Schöberl May 20, 206 Discontinuous Galerkin (DG) methods approximate the solution with piecewise functions (polynomials), which are discontinuous across element interfaces.

More information

Multigrid Method ZHONG-CI SHI. Institute of Computational Mathematics Chinese Academy of Sciences, Beijing, China. Joint work: Xuejun Xu

Multigrid Method ZHONG-CI SHI. Institute of Computational Mathematics Chinese Academy of Sciences, Beijing, China. Joint work: Xuejun Xu Multigrid Method ZHONG-CI SHI Institute of Computational Mathematics Chinese Academy of Sciences, Beijing, China Joint work: Xuejun Xu Outline Introduction Standard Cascadic Multigrid method(cmg) Economical

More information

Hamburger Beiträge zur Angewandten Mathematik

Hamburger Beiträge zur Angewandten Mathematik Hamburger Beiträge zur Angewandten Mathematik Numerical analysis of a control and state constrained elliptic control problem with piecewise constant control approximations Klaus Deckelnick and Michael

More information

Chapter 1: The Finite Element Method

Chapter 1: The Finite Element Method Chapter 1: The Finite Element Method Michael Hanke Read: Strang, p 428 436 A Model Problem Mathematical Models, Analysis and Simulation, Part Applications: u = fx), < x < 1 u) = u1) = D) axial deformation

More information

An additive average Schwarz method for the plate bending problem

An additive average Schwarz method for the plate bending problem J. Numer. Math., Vol. 10, No. 2, pp. 109 125 (2002) c VSP 2002 Prepared using jnm.sty [Version: 02.02.2002 v1.2] An additive average Schwarz method for the plate bending problem X. Feng and T. Rahman Abstract

More information

ngsxfem: Geometrically unfitted discretizations with Netgen/NGSolve (https://github.com/ngsxfem/ngsxfem)

ngsxfem: Geometrically unfitted discretizations with Netgen/NGSolve (https://github.com/ngsxfem/ngsxfem) ngsxfem: Geometrically unfitted discretizations with Netgen/NGSolve (https://github.com/ngsxfem/ngsxfem) Christoph Lehrenfeld (with contributions from F. Heimann, J. Preuß, M. Hochsteger,...) lehrenfeld@math.uni-goettingen.de

More information

AMS 147 Computational Methods and Applications Lecture 17 Copyright by Hongyun Wang, UCSC

AMS 147 Computational Methods and Applications Lecture 17 Copyright by Hongyun Wang, UCSC Lecture 17 Copyright by Hongyun Wang, UCSC Recap: Solving linear system A x = b Suppose we are given the decomposition, A = L U. We solve (LU) x = b in 2 steps: *) Solve L y = b using the forward substitution

More information

c 2007 Society for Industrial and Applied Mathematics

c 2007 Society for Industrial and Applied Mathematics SIAM J. NUMR. ANAL. Vol. 45, No. 1, pp. 68 82 c 2007 Society for Industrial and Applied Mathematics FRAMWORK FOR TH A POSTRIORI RROR ANALYSIS OF NONCONFORMING FINIT LMNTS CARSTN CARSTNSN, JUN HU, AND ANTONIO

More information

Numerical Solutions to Partial Differential Equations

Numerical Solutions to Partial Differential Equations Numerical Solutions to Partial Differential Equations Zhiping Li LMAM and School of Mathematical Sciences Peking University The Residual and Error of Finite Element Solutions Mixed BVP of Poisson Equation

More information

Priority Program 1253

Priority Program 1253 Deutsche Forschungsgemeinschaft Priority Program 1253 Optimization with Partial Differential Equations Klaus Deckelnick and Michael Hinze A note on the approximation of elliptic control problems with bang-bang

More information

FEM-Level Set Techniques for Multiphase Flow --- Some recent results

FEM-Level Set Techniques for Multiphase Flow --- Some recent results FEM-Level Set Techniques for Multiphase Flow --- Some recent results ENUMATH09, Uppsala Stefan Turek, Otto Mierka, Dmitri Kuzmin, Shuren Hysing Institut für Angewandte Mathematik, TU Dortmund http://www.mathematik.tu-dortmund.de/ls3

More information

Numerical Simulation of Powder Flow

Numerical Simulation of Powder Flow Numerical Simulation of Powder Flow Stefan Turek, Abderrahim Ouazzi Institut für Angewandte Mathematik, Univ. Dortmund http://www.mathematik.uni-dortmund.de/ls3 http://www.featflow.de Models for granular

More information

On the relationship of local projection stabilization to other stabilized methods for one-dimensional advection-diffusion equations

On the relationship of local projection stabilization to other stabilized methods for one-dimensional advection-diffusion equations On the relationship of local projection stabilization to other stabilized methods for one-dimensional advection-diffusion equations Lutz Tobiska Institut für Analysis und Numerik Otto-von-Guericke-Universität

More information

Axioms of Adaptivity (AoA) in Lecture 3 (sufficient for optimal convergence rates)

Axioms of Adaptivity (AoA) in Lecture 3 (sufficient for optimal convergence rates) Axioms of Adaptivity (AoA) in Lecture 3 (sufficient for optimal convergence rates) Carsten Carstensen Humboldt-Universität zu Berlin 2018 International Graduate Summer School on Frontiers of Applied and

More information

A posteriori error estimation for elliptic problems

A posteriori error estimation for elliptic problems A posteriori error estimation for elliptic problems Praveen. C praveen@math.tifrbng.res.in Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore 560065 http://math.tifrbng.res.in

More information

Stabilization Techniques and a Posteriori Error Estimates for the Obstacle Problem

Stabilization Techniques and a Posteriori Error Estimates for the Obstacle Problem Applied Mathematical Sciences, Vol. 7, 2013, no. 127, 6329-6346 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2013.39504 Stabilization Techniques and a Posteriori Error Estimates for the

More information

Monolithic Newton-multigrid solution techniques for incompressible nonlinear flow models

Monolithic Newton-multigrid solution techniques for incompressible nonlinear flow models Monolithic Newton-multigrid solution techniques for incompressible nonlinear flow models H. Damanik a,, J. Hron b, A. Ouazzi a, S. Turek a a Institut für Angewante Mathematik, TU Dortmund, Germany b Institute

More information

Multigrid Methods for Maxwell s Equations

Multigrid Methods for Maxwell s Equations Multigrid Methods for Maxwell s Equations Jintao Cui Institute for Mathematics and Its Applications University of Minnesota Outline Nonconforming Finite Element Methods for a Two Dimensional Curl-Curl

More information

OUTLINE ffl CFD: elliptic pde's! Ax = b ffl Basic iterative methods ffl Krylov subspace methods ffl Preconditioning techniques: Iterative methods ILU

OUTLINE ffl CFD: elliptic pde's! Ax = b ffl Basic iterative methods ffl Krylov subspace methods ffl Preconditioning techniques: Iterative methods ILU Preconditioning Techniques for Solving Large Sparse Linear Systems Arnold Reusken Institut für Geometrie und Praktische Mathematik RWTH-Aachen OUTLINE ffl CFD: elliptic pde's! Ax = b ffl Basic iterative

More information

Robust Monolithic - Multigrid FEM Solver for Three Fields Formulation Rising from non-newtonian Flow Problems

Robust Monolithic - Multigrid FEM Solver for Three Fields Formulation Rising from non-newtonian Flow Problems Robust Monolithic - Multigrid FEM Solver for Three Fields Formulation Rising from non-newtonian Flow Problems M. Aaqib Afaq Institute for Applied Mathematics and Numerics (LSIII) TU Dortmund 13 July 2017

More information

Geometric Multigrid Methods

Geometric Multigrid Methods Geometric Multigrid Methods Susanne C. Brenner Department of Mathematics and Center for Computation & Technology Louisiana State University IMA Tutorial: Fast Solution Techniques November 28, 2010 Ideas

More information

ETNA Kent State University

ETNA Kent State University Electronic Transactions on Numerical Analysis. Volume 37, pp. 166-172, 2010. Copyright 2010,. ISSN 1068-9613. ETNA A GRADIENT RECOVERY OPERATOR BASED ON AN OBLIQUE PROJECTION BISHNU P. LAMICHHANE Abstract.

More information

On Multigrid for Phase Field

On Multigrid for Phase Field On Multigrid for Phase Field Carsten Gräser (FU Berlin), Ralf Kornhuber (FU Berlin), Rolf Krause (Uni Bonn), and Vanessa Styles (University of Sussex) Interphase 04 Rome, September, 13-16, 2004 Synopsis

More information

Aspects of Multigrid

Aspects of Multigrid Aspects of Multigrid Kees Oosterlee 1,2 1 Delft University of Technology, Delft. 2 CWI, Center for Mathematics and Computer Science, Amsterdam, SIAM Chapter Workshop Day, May 30th 2018 C.W.Oosterlee (CWI)

More information

Overview. A Posteriori Error Estimates for the Biharmonic Equation. Variational Formulation and Discretization. The Biharmonic Equation

Overview. A Posteriori Error Estimates for the Biharmonic Equation. Variational Formulation and Discretization. The Biharmonic Equation Overview A Posteriori rror stimates for the Biharmonic quation R Verfürth Fakultät für Mathematik Ruhr-Universität Bochum wwwruhr-uni-bochumde/num1 Milan / February 11th, 013 The Biharmonic quation Summary

More information

An Introduction to the Discontinuous Galerkin Method

An Introduction to the Discontinuous Galerkin Method An Introduction to the Discontinuous Galerkin Method Krzysztof J. Fidkowski Aerospace Computational Design Lab Massachusetts Institute of Technology March 16, 2005 Computational Prototyping Group Seminar

More information

Universität Stuttgart

Universität Stuttgart Universität Stuttgart Second Order Lagrange Multiplier Spaces for Mortar Finite Elements in 3D Bishnu P. Lamichhane, Barbara I. Wohlmuth Berichte aus dem Institut für Angewandte Analysis und Numerische

More information

Discrete Projection Methods for Incompressible Fluid Flow Problems and Application to a Fluid-Structure Interaction

Discrete Projection Methods for Incompressible Fluid Flow Problems and Application to a Fluid-Structure Interaction Discrete Projection Methods for Incompressible Fluid Flow Problems and Application to a Fluid-Structure Interaction Problem Jörg-M. Sautter Mathematisches Institut, Universität Düsseldorf, Germany, sautter@am.uni-duesseldorf.de

More information

u(0) = u 0, u(1) = u 1. To prove what we want we introduce a new function, where c = sup x [0,1] a(x) and ɛ 0:

u(0) = u 0, u(1) = u 1. To prove what we want we introduce a new function, where c = sup x [0,1] a(x) and ɛ 0: 6. Maximum Principles Goal: gives properties of a solution of a PDE without solving it. For the two-point boundary problem we shall show that the extreme values of the solution are attained on the boundary.

More information

On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion

On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion Volker John and Ellen Schmeyer FR 6.1 Mathematik, Universität des Saarlandes, Postfach 15 11

More information

A STOKES INTERFACE PROBLEM: STABILITY, FINITE ELEMENT ANALYSIS AND A ROBUST SOLVER

A STOKES INTERFACE PROBLEM: STABILITY, FINITE ELEMENT ANALYSIS AND A ROBUST SOLVER European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS 2004 P. Neittaanmäki, T. Rossi, K. Majava, and O. Pironneau (eds.) O. Nevanlinna and R. Rannacher (assoc. eds.) Jyväskylä,

More information

Numerical Solutions to Partial Differential Equations

Numerical Solutions to Partial Differential Equations Numerical Solutions to Partial Differential Equations Zhiping Li LMAM and School of Mathematical Sciences Peking University Nonconformity and the Consistency Error First Strang Lemma Abstract Error Estimate

More information

Projected Surface Finite Elements for Elliptic Equations

Projected Surface Finite Elements for Elliptic Equations Available at http://pvamu.edu/aam Appl. Appl. Math. IN: 1932-9466 Vol. 8, Issue 1 (June 2013), pp. 16 33 Applications and Applied Mathematics: An International Journal (AAM) Projected urface Finite Elements

More information

Lecture 18 Classical Iterative Methods

Lecture 18 Classical Iterative Methods Lecture 18 Classical Iterative Methods MIT 18.335J / 6.337J Introduction to Numerical Methods Per-Olof Persson November 14, 2006 1 Iterative Methods for Linear Systems Direct methods for solving Ax = b,

More information

NUMERICAL SOLUTION OF CONVECTION DIFFUSION EQUATIONS USING UPWINDING TECHNIQUES SATISFYING THE DISCRETE MAXIMUM PRINCIPLE

NUMERICAL SOLUTION OF CONVECTION DIFFUSION EQUATIONS USING UPWINDING TECHNIQUES SATISFYING THE DISCRETE MAXIMUM PRINCIPLE Proceedings of the Czech Japanese Seminar in Applied Mathematics 2005 Kuju Training Center, Oita, Japan, September 15-18, 2005 pp. 69 76 NUMERICAL SOLUTION OF CONVECTION DIFFUSION EQUATIONS USING UPWINDING

More information

ON THE MULTIPOINT MIXED FINITE VOLUME METHODS ON QUADRILATERAL GRIDS

ON THE MULTIPOINT MIXED FINITE VOLUME METHODS ON QUADRILATERAL GRIDS ON THE MULTIPOINT MIXED FINITE VOLUME METHODS ON QUADRILATERAL GRIDS VINCENT FONTAINE 1,2 AND ANIS YOUNES 2 1 Laboratoire de Physique des Bâtiments et des Systèmes, Université de La Réunion, 15 avenue

More information

Math 1 Unit 1 EOC Review

Math 1 Unit 1 EOC Review Math 1 Unit 1 EOC Review Name: Solving Equations (including Literal Equations) - Get the variable to show what it equals to satisfy the equation or inequality - Steps (each step only where necessary):

More information

High order, finite volume method, flux conservation, finite element method

High order, finite volume method, flux conservation, finite element method FLUX-CONSERVING FINITE ELEMENT METHODS SHANGYOU ZHANG, ZHIMIN ZHANG, AND QINGSONG ZOU Abstract. We analyze the flux conservation property of the finite element method. It is shown that the finite element

More information

LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES)

LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES) LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES) RAYTCHO LAZAROV 1 Notations and Basic Functional Spaces Scalar function in R d, d 1 will be denoted by u,

More information

R T (u H )v + (2.1) J S (u H )v v V, T (2.2) (2.3) H S J S (u H ) 2 L 2 (S). S T

R T (u H )v + (2.1) J S (u H )v v V, T (2.2) (2.3) H S J S (u H ) 2 L 2 (S). S T 2 R.H. NOCHETTO 2. Lecture 2. Adaptivity I: Design and Convergence of AFEM tarting with a conforming mesh T H, the adaptive procedure AFEM consists of loops of the form OLVE ETIMATE MARK REFINE to produce

More information

Constrained H 1 -interpolation on quadrilateral and hexahedral meshes with hanging nodes

Constrained H 1 -interpolation on quadrilateral and hexahedral meshes with hanging nodes Constrained H 1 -interpolation on quadrilateral and hexahedral meshes with hanging nodes Vincent Heuveline Friedhelm Schieweck Abstract We propose a Scott-Zhang type finite element interpolation operator

More information

FEniCS Course. Lecture 6: Incompressible Navier Stokes. Contributors Anders Logg André Massing

FEniCS Course. Lecture 6: Incompressible Navier Stokes. Contributors Anders Logg André Massing FEniCS Course Lecture 6: Incompressible Navier Stokes Contributors Anders Logg André Massing 1 / 11 The incompressible Navier Stokes equations u + u u ν u + p = f in Ω (0, T ] u = 0 in Ω (0, T ] u = g

More information

Stochastic multiscale modeling of subsurface and surface flows. Part III: Multiscale mortar finite elements for coupled Stokes-Darcy flows

Stochastic multiscale modeling of subsurface and surface flows. Part III: Multiscale mortar finite elements for coupled Stokes-Darcy flows Stochastic multiscale modeling of subsurface and surface flows. Part III: Multiscale mortar finite elements for coupled Stokes-Darcy flows Ivan otov Department of Mathematics, University of Pittsburgh

More information

On spurious oscillations at layers diminishing (SOLD) methods for convection-diffusion equations: Part II - Analysis for P1 and Q1 finite elements

On spurious oscillations at layers diminishing (SOLD) methods for convection-diffusion equations: Part II - Analysis for P1 and Q1 finite elements Volker John, Petr Knobloch On spurious oscillations at layers diminishing (SOLD) methods for convection-diffusion equations: Part II - Analysis for P and Q finite elements Preprint No. MATH-knm-27/4 27.

More information

Space-time Finite Element Methods for Parabolic Evolution Problems

Space-time Finite Element Methods for Parabolic Evolution Problems Space-time Finite Element Methods for Parabolic Evolution Problems with Variable Coefficients Ulrich Langer, Martin Neumüller, Andreas Schafelner Johannes Kepler University, Linz Doctoral Program Computational

More information

Universität des Saarlandes. Fachrichtung 6.1 Mathematik

Universität des Saarlandes. Fachrichtung 6.1 Mathematik Universität des Saarlandes U N I V E R S I T A S S A R A V I E N I S S Fachrichtung 6.1 Mathematik Preprint Nr. 219 On finite element methods for 3D time dependent convection diffusion reaction equations

More information

Institut für Mathematik

Institut für Mathematik U n i v e r s i t ä t A u g s b u r g Institut für Mathematik Xuejun Xu, Huangxin Chen, Ronald H.W. Hoppe Local Multilevel Methods for Adaptive Nonconforming Finite Element Methods Preprint Nr. 21/2009

More information

Une méthode de pénalisation par face pour l approximation des équations de Navier-Stokes à nombre de Reynolds élevé

Une méthode de pénalisation par face pour l approximation des équations de Navier-Stokes à nombre de Reynolds élevé Une méthode de pénalisation par face pour l approximation des équations de Navier-Stokes à nombre de Reynolds élevé CMCS/IACS Ecole Polytechnique Federale de Lausanne Erik.Burman@epfl.ch Méthodes Numériques

More information

INTRODUCTION TO FINITE ELEMENT METHODS

INTRODUCTION TO FINITE ELEMENT METHODS INTRODUCTION TO FINITE ELEMENT METHODS LONG CHEN Finite element methods are based on the variational formulation of partial differential equations which only need to compute the gradient of a function.

More information

Numerische Simulation zur Herstellung monodisperser Tropfen in pneumatischen Ziehdüsen

Numerische Simulation zur Herstellung monodisperser Tropfen in pneumatischen Ziehdüsen Numerische Simulation zur Herstellung monodisperser Tropfen in pneumatischen Ziehdüsen DFG SPP 1423 Prozess-Spray Prof. Dr. Stefan Turek, Dr. Institut für Angewandte Mathematik, LS III Technische Universität

More information

Three remarks on anisotropic finite elements

Three remarks on anisotropic finite elements Three remarks on anisotropic finite elements Thomas Apel Universität der Bundeswehr München Workshop Numerical Analysis for Singularly Perturbed Problems dedicated to the 60th birthday of Martin Stynes

More information

Inexact Algorithms in Function Space and Adaptivity

Inexact Algorithms in Function Space and Adaptivity Inexact Algorithms in Function Space and Adaptivity Anton Schiela adaptive discretization nonlinear solver Zuse Institute Berlin linear solver Matheon project A1 ZIB: P. Deuflhard, M. Weiser TUB: F. Tröltzsch,

More information

AND BARBARA I. WOHLMUTH

AND BARBARA I. WOHLMUTH A QUASI-DUAL LAGRANGE MULTIPLIER SPACE FOR SERENDIPITY MORTAR FINITE ELEMENTS IN 3D BISHNU P. LAMICHHANE AND BARBARA I. WOHLMUTH Abstract. Domain decomposition techniques provide a flexible tool for the

More information

1. Introduction. We consider the model problem that seeks an unknown function u = u(x) satisfying

1. Introduction. We consider the model problem that seeks an unknown function u = u(x) satisfying A SIMPLE FINITE ELEMENT METHOD FOR LINEAR HYPERBOLIC PROBLEMS LIN MU AND XIU YE Abstract. In this paper, we introduce a simple finite element method for solving first order hyperbolic equations with easy

More information

Dual-Primal Isogeometric Tearing and Interconnecting Solvers for Continuous and Discontinuous Galerkin IgA Equations

Dual-Primal Isogeometric Tearing and Interconnecting Solvers for Continuous and Discontinuous Galerkin IgA Equations Dual-Primal Isogeometric Tearing and Interconnecting Solvers for Continuous and Discontinuous Galerkin IgA Equations Christoph Hofer and Ulrich Langer Doctoral Program Computational Mathematics Numerical

More information

HIGHER-ORDER LINEARLY IMPLICIT ONE-STEP METHODS FOR THREE-DIMENSIONAL INCOMPRESSIBLE NAVIER-STOKES EQUATIONS

HIGHER-ORDER LINEARLY IMPLICIT ONE-STEP METHODS FOR THREE-DIMENSIONAL INCOMPRESSIBLE NAVIER-STOKES EQUATIONS STUDIA UNIV. BABEŞ BOLYAI, MATHEMATICA, Volume LIII, Number 1, March 2008 HIGHER-ORDER LINEARLY IMPLICIT ONE-STEP METHODS FOR THREE-DIMENSIONAL INCOMPRESSIBLE NAVIER-STOKES EQUATIONS IOAN TELEAGA AND JENS

More information

Optimal multilevel preconditioning of strongly anisotropic problems.part II: non-conforming FEM. p. 1/36

Optimal multilevel preconditioning of strongly anisotropic problems.part II: non-conforming FEM. p. 1/36 Optimal multilevel preconditioning of strongly anisotropic problems. Part II: non-conforming FEM. Svetozar Margenov margenov@parallel.bas.bg Institute for Parallel Processing, Bulgarian Academy of Sciences,

More information

Basic Concepts of Adaptive Finite Element Methods for Elliptic Boundary Value Problems

Basic Concepts of Adaptive Finite Element Methods for Elliptic Boundary Value Problems Basic Concepts of Adaptive Finite lement Methods for lliptic Boundary Value Problems Ronald H.W. Hoppe 1,2 1 Department of Mathematics, University of Houston 2 Institute of Mathematics, University of Augsburg

More information

SAROD Conference, Hyderabad, december 2005 CONTINUOUS MESH ADAPTATION MODELS FOR CFD

SAROD Conference, Hyderabad, december 2005 CONTINUOUS MESH ADAPTATION MODELS FOR CFD 1 SAROD Conference, Hyderabad, december 2005 CONTINUOUS MESH ADAPTATION MODELS FOR CFD Bruno Koobus, 1,2 Laurent Hascoët, 1 Frédéric Alauzet, 3 Adrien Loseille, 3 Youssef Mesri, 1 Alain Dervieux 1 1 INRIA

More information

Numerical Analysis and Methods for PDE I

Numerical Analysis and Methods for PDE I Numerical Analysis and Methods for PDE I A. J. Meir Department of Mathematics and Statistics Auburn University US-Africa Advanced Study Institute on Analysis, Dynamical Systems, and Mathematical Modeling

More information

Chapter 6. Finite Element Method. Literature: (tiny selection from an enormous number of publications)

Chapter 6. Finite Element Method. Literature: (tiny selection from an enormous number of publications) Chapter 6 Finite Element Method Literature: (tiny selection from an enormous number of publications) K.J. Bathe, Finite Element procedures, 2nd edition, Pearson 2014 (1043 pages, comprehensive). Available

More information

THE BEST L 2 NORM ERROR ESTIMATE OF LOWER ORDER FINITE ELEMENT METHODS FOR THE FOURTH ORDER PROBLEM *

THE BEST L 2 NORM ERROR ESTIMATE OF LOWER ORDER FINITE ELEMENT METHODS FOR THE FOURTH ORDER PROBLEM * Journal of Computational Mathematics Vol.30, No.5, 2012, 449 460. http://www.global-sci.org/jcm doi:10.4208/jcm.1203-m3855 THE BEST L 2 NORM ERROR ESTIMATE OF LOWER ORDER FINITE ELEMENT METHODS FOR THE

More information

PREPRINT 2010:25. Fictitious domain finite element methods using cut elements: II. A stabilized Nitsche method ERIK BURMAN PETER HANSBO

PREPRINT 2010:25. Fictitious domain finite element methods using cut elements: II. A stabilized Nitsche method ERIK BURMAN PETER HANSBO PREPRINT 2010:25 Fictitious domain finite element methods using cut elements: II. A stabilized Nitsche method ERIK BURMAN PETER HANSBO Department of Mathematical Sciences Division of Mathematics CHALMERS

More information

A NOTE ON CONSTANT-FREE A POSTERIORI ERROR ESTIMATES

A NOTE ON CONSTANT-FREE A POSTERIORI ERROR ESTIMATES A NOTE ON CONSTANT-FREE A POSTERIORI ERROR ESTIMATES R. VERFÜRTH Abstract. In this note we look at constant-free a posteriori error estimates from a different perspective. We show that they can be interpreted

More information

Examination paper for TMA4215 Numerical Mathematics

Examination paper for TMA4215 Numerical Mathematics Department of Mathematical Sciences Examination paper for TMA425 Numerical Mathematics Academic contact during examination: Trond Kvamsdal Phone: 93058702 Examination date: 6th of December 207 Examination

More information

Mathematical Methods - Lecture 9

Mathematical Methods - Lecture 9 Mathematical Methods - Lecture 9 Yuliya Tarabalka Inria Sophia-Antipolis Méditerranée, Titane team, http://www-sop.inria.fr/members/yuliya.tarabalka/ Tel.: +33 (0)4 92 38 77 09 email: yuliya.tarabalka@inria.fr

More information

Proper Orthogonal Decomposition (POD) for Nonlinear Dynamical Systems. Stefan Volkwein

Proper Orthogonal Decomposition (POD) for Nonlinear Dynamical Systems. Stefan Volkwein Proper Orthogonal Decomposition (POD) for Nonlinear Dynamical Systems Institute for Mathematics and Scientific Computing, Austria DISC Summerschool 5 Outline of the talk POD and singular value decomposition

More information

Partial Differential Equations

Partial Differential Equations Next: Using Matlab Up: Numerical Analysis for Chemical Previous: Ordinary Differential Equations Subsections Finite Difference: Elliptic Equations The Laplace Equations Solution Techniques Boundary Conditions

More information

Superconvergence analysis of the SDFEM for elliptic problems with characteristic layers

Superconvergence analysis of the SDFEM for elliptic problems with characteristic layers Superconvergence analysis of the SDFEM for elliptic problems with characteristic layers S. Franz, T. Linß, H.-G. Roos Institut für Numerische Mathematik, Technische Universität Dresden, D-01062, Germany

More information

A DISCRETE PROJECTION METHOD FOR INCOMPRESSIBLE VISCOUS FLOW WITH CORIOLIS FORCE

A DISCRETE PROJECTION METHOD FOR INCOMPRESSIBLE VISCOUS FLOW WITH CORIOLIS FORCE A DISCRETE PROJECTION METHOD FOR INCOMPRESSIBLE VISCOUS FLOW WITH CORIOLIS FORCE ANDRIY SOKOLOV, MAXIM A. OLSHANSKII, AND STEFAN TUREK Abstract. The paper presents a new discrete projection method (DPM)

More information

Time-dependent variational forms

Time-dependent variational forms Time-dependent variational forms Hans Petter Langtangen 1,2 1 Center for Biomedical Computing, Simula Research Laboratory 2 Department of Informatics, University of Oslo Oct 30, 2015 PRELIMINARY VERSION

More information

A Finite Element Method for the Surface Stokes Problem

A Finite Element Method for the Surface Stokes Problem J A N U A R Y 2 0 1 8 P R E P R I N T 4 7 5 A Finite Element Method for the Surface Stokes Problem Maxim A. Olshanskii *, Annalisa Quaini, Arnold Reusken and Vladimir Yushutin Institut für Geometrie und

More information

FEniCS Course. Lecture 0: Introduction to FEM. Contributors Anders Logg, Kent-Andre Mardal

FEniCS Course. Lecture 0: Introduction to FEM. Contributors Anders Logg, Kent-Andre Mardal FEniCS Course Lecture 0: Introduction to FEM Contributors Anders Logg, Kent-Andre Mardal 1 / 46 What is FEM? The finite element method is a framework and a recipe for discretization of mathematical problems

More information

Numerical Solutions to Partial Differential Equations

Numerical Solutions to Partial Differential Equations Numerical Solutions to Partial Differential Equations Zhiping Li LMAM and School of Mathematical Sciences Peking University Discretization of Boundary Conditions Discretization of Boundary Conditions On

More information

Stabilization and Acceleration of Algebraic Multigrid Method

Stabilization and Acceleration of Algebraic Multigrid Method Stabilization and Acceleration of Algebraic Multigrid Method Recursive Projection Algorithm A. Jemcov J.P. Maruszewski Fluent Inc. October 24, 2006 Outline 1 Need for Algorithm Stabilization and Acceleration

More information