Math 2.0

Numerical analysis Boundary value problems and finite elements Theorem

Ladyzhenskaya–Babuška–Brezzi condition

Builds on Hilbert spaceBilinear formCoercive bilinear formContinuous dual spaceLax–Milgram theoremKernel

Statement

Let VV and QQ be real Hilbert spaces. Let a ⁣:V×V→ℝa \colon V \times V \to \R and b ⁣:V×Q→ℝb \colon V \times Q \to \R be bounded bilinear forms, and let f∈V′f \in V' and g∈Q′g \in Q', where ′' denotes the continuous dual space. Consider the saddle-point problem: find (u,p)∈V×Q(u, p) \in V \times Q with a(u,v)+b(v,p)=f(v)  for all v∈V,b(u,q)=g(q)  for all q∈Q.a(u, v) + b(v, p) = f(v) \ \text{ for all } v \in V, \qquad b(u, q) = g(q) \ \text{ for all } q \in Q. Let Vh⊆VV_h \subseteq V and Qh⊆QQ_h \subseteq Q be finite-dimensional subspaces, and let Zh={v∈Vh:b(v,q)=0 for all q∈Qh}Z_h = \set{v \in V_h : b(v, q) = 0 \text{ for all } q \in Q_h}. Assume that there are constants α>0\alpha > 0 and β>0\beta > 0, independent of hh, such that:

  1. aa is coercive on ZhZ_h: a(v,v)≥α∥v∥V2a(v, v) \ge \alpha \norm{v}_V^2 for all v∈Zhv \in Z_h;
  2. the inf-sup condition, or LBB condition, holds: inf⁡q∈Qh∖{0} sup⁡v∈Vh∖{0}b(v,q)∥v∥V∥q∥Q≥β.\inf_{q \in Q_h \setminus \set{0}} \ \sup_{v \in V_h \setminus \set{0}} \frac{b(v, q)}{\norm{v}_V \norm{q}_Q} \ge \beta.

Then the discrete problem, posed with VhV_h and QhQ_h in place of VV and QQ, has a unique solution (uh,ph)(u_h, p_h). If the continuous problem has a solution (u,p)(u, p), then ∥u−uh∥V+∥p−ph∥Q≤C(inf⁡v∈Vh∥u−v∥V+inf⁡q∈Qh∥p−q∥Q),\norm{u - u_h}_V + \norm{p - p_h}_Q \le C \Big( \inf_{v \in V_h} \norm{u - v}_V + \inf_{q \in Q_h} \norm{p - q}_Q \Big), where CC depends only on α\alpha, β\beta and the bounds of aa and bb.

Remarks

The same two conditions with VV, QQ and the kernel Z={v∈V:b(v,q)=0 for all q∈Q}Z = \set{v \in V : b(v, q) = 0 \text{ for all } q \in Q} give existence and uniqueness for the continuous problem; this is Brezzi's theorem. The inf-sup condition says that the operator B ⁣:V→Q′B \colon V \to Q' given by bb maps onto Q′Q' with a bounded right inverse. So one first finds ugu_g with b(ug,q)=g(q)b(u_g, q) = g(q) and ∥ug∥≤∥g∥/β\norm{u_g} \le \norm{g} / \beta. Then one solves for u−ugu - u_g in ZZ by the Lax–Milgram theorem. Finally one recovers pp from the first equation, using the inf-sup condition again. The point of the discrete theorem is that β\beta does not depend on hh; otherwise the constant CC can blow up as the mesh is refined.

Example: for the Stokes equations, V=H01(Ω)dV = H^1_0(\Omega)^d, Q=L02(Ω)Q = L^2_0(\Omega), a(u,v)=∫Ω∇u:∇va(u, v) = \int_\Omega \nabla u : \nabla v and b(v,q)=−∫Ωq ∇⋅vb(v, q) = -\int_\Omega q \, \nabla \cdot v. The Taylor–Hood pair, continuous piecewise quadratic velocities with continuous piecewise linear pressures, satisfies the inf-sup condition uniformly on suitable meshes.

Necessity: the pair of continuous piecewise linear velocities and pressures on a triangle mesh violates the condition. The discrete problem then has spurious pressure modes or a constant βh\beta_h that tends to 00, and the computed pressure oscillates.

Going deeper

For a student

The condition is the key stability requirement of mixed finite element methods. It replaces the coercivity of the Lax–Milgram setting, which a saddle-point problem never has on the whole space V×QV \times Q. Checking it for a given pair of spaces is often done with a Fortin operator: a bounded projection Πh ⁣:V→Vh\Pi_h \colon V \to V_h with b(v−Πhv,q)=0b(v - \Pi_h v, q) = 0 for all q∈Qhq \in Q_h. Stable pairs include Taylor–Hood elements for Stokes flow and Raviart–Thomas elements with piecewise constants for the mixed Poisson problem.

Reading path

To understand this page from the ground up, read these 97 pages in order. The foundations come first.

  1. Bilinear form concept
  2. Closed set concept
  3. Coercive bilinear form concept
  4. Compact operator concept
  5. Continuous dual space concept
  6. Convex set concept
  7. Element definition
  8. Extended real number line object
  9. Hilbert space concept
  10. Hölder continuity concept
  11. Inequality of arithmetic and geometric means statement
  12. Kernel concept
  13. Linear form concept
  14. Lp space concept
  15. Orthogonal complement concept
  16. Proposition concept
  17. Real numbers object
  18. Set bounded above definition
  19. Sobolev space concept
  20. Uniform metric on bounded functions example
  21. Vector space definition
  22. Weak derivative concept
  23. Weak solution concept
  24. Set definition
  25. Young's inequality for products statement
  26. Sobolev embedding theorem statement
  27. Conjunction definition
  28. Disjunction definition
  29. Implication definition
  30. Predicate definition
  31. Supremum definition
  32. Inner product definition
  33. Linear map definition
  34. Linear subspace definition
  35. Norm definition
  36. Empty set object
  37. Family of sets definition
  38. Ordered pair definition
  39. Hölder's inequality statement
  40. Intersection definition
  41. Union definition
  42. Existential quantifier definition
  43. Universal quantifier definition
  44. Inner product space definition
  45. Orthogonal vectors definition
  46. Endomorphism definition
  47. Linear form definition
  48. Sum of subspaces definition
  49. Cartesian product definition
  50. Union of a family of sets definition
  51. Subset definition
  52. Uniqueness quantifier definition
  53. Norm induced by an inner product definition
  54. Orthogonal complement definition
  55. Riesz representation theorem in finite dimensions statement
  56. Sobolev inequality statement
  57. Direct sum of subspaces definition
  58. Binary relation definition
  59. Topological space definition
  60. Parallelogram law statement
  61. A space is the direct sum of a subspace and its orthogonal complement statement
  62. Projection definition
  63. Sequential compactness definition
  64. Function definition
  65. Subspace topology definition
  66. Orthogonal projection definition
  67. Preimage of a set definition
  68. Restriction of a function definition
  69. Orthogonal projection is the closest point statement
  70. Metric space definition
  71. Subspace metric definition
  72. Convergence of a sequence in a metric space definition
  73. Open ball definition
  74. Hilbert projection theorem statement
  75. Diameter of a set definition
  76. Metric topology definition
  77. Epsilon characterisation of Cauchy sequences statement
  78. Totally bounded set definition
  79. Riesz representation theorem statement
  80. Open set definition
  81. Complete metric space definition
  82. Open cover definition
  83. Open sets characterised by neighbourhoods statement
  84. Open sets of a metric space statement
  85. Compact space definition
  86. Continuity at a point of a topological space definition
  87. Compact set definition
  88. Lebesgue number lemma statement
  89. Epsilon-delta continuity in metric spaces statement
  90. Compactness and sequential compactness agree in metric spaces statement
  91. Equicontinuity definition
  92. Compact iff complete and totally bounded statement
  93. Arzelà–Ascoli theorem statement
  94. Rellich–Kondrachov theorem statement
  95. Poincaré inequality statement
  96. Lax–Milgram theorem statement
  97. Ladyzhenskaya–Babuška–Brezzi condition statement

Further reading

  1. Web https://en.wikipedia.org/wiki/Ladyzhenskaya%E2%80%93Babu%C5%A1ka%E2%80%93Brezzi_condition
About this page
TagSC5FV3GHV5
URIm2://SC5FV3GHV5
Kindstatement, theorem
WritingW0 stub
MSC65N30, 65N12, 76D07
StatusThis copy of the site has no build data. Run m2 status SC5FV3GHV5.
AboutMixed finite element method
UsesHilbert space, Bilinear form, Coercive bilinear form, Continuous dual space, Lax–Milgram theorem, Kernel
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