ConceptComplete

Finite Element Methods

The finite element method (FEM) provides a systematic framework for approximating PDEs on complex domains. By working with weak formulations and piecewise polynomial spaces, FEM combines mathematical rigor with practical flexibility.


Variational Formulation

Definition8.4Weak Formulation

Consider the boundary value problem βˆ’βˆ‡β‹…(aβˆ‡u)+cu=f-\nabla \cdot (a\nabla u) + cu = f in Ξ©\Omega, u=0u = 0 on βˆ‚Ξ©\partial\Omega. The weak formulation seeks u∈H01(Ξ©)u \in H_0^1(\Omega) such that B(u,v)=F(v)B(u, v) = F(v) for all v∈H01(Ξ©)v \in H_0^1(\Omega), where B(u,v)=∫Ω(aβˆ‡uβ‹…βˆ‡v+cuv) dxB(u,v) = \int_\Omega (a\nabla u \cdot \nabla v + cuv)\,dx is the bilinear form and F(v)=∫Ωfv dxF(v) = \int_\Omega fv\,dx is the linear functional. By the Lax-Milgram theorem, if BB is continuous and coercive, there exists a unique weak solution.

Definition8.5Galerkin Method

The Galerkin method restricts the weak formulation to a finite-dimensional subspace VhβŠ‚H01(Ξ©)V_h \subset H_0^1(\Omega): find uh∈Vhu_h \in V_h such that B(uh,vh)=F(vh)B(u_h, v_h) = F(v_h) for all vh∈Vhv_h \in V_h. Choosing a basis {Ο•1,…,Ο•N}\{\phi_1, \ldots, \phi_N\} for VhV_h and writing uh=βˆ‘jcjΟ•ju_h = \sum_j c_j \phi_j leads to the stiffness system Kc=fKc = f where Kij=B(Ο•j,Ο•i)K_{ij} = B(\phi_j, \phi_i) and fi=F(Ο•i)f_i = F(\phi_i).


Finite Element Spaces

Definition8.6Piecewise Linear Elements

On a triangulation Th\mathcal{T}_h of Ξ©\Omega, the space of continuous piecewise linear (P1) elements is Vh={v∈C(Ξ©Λ‰):v∣T∈P1Β forΒ allΒ T∈Th, vβˆ£βˆ‚Ξ©=0}V_h = \{v \in C(\bar{\Omega}) : v|_T \in \mathcal{P}_1 \text{ for all } T \in \mathcal{T}_h,\, v|_{\partial\Omega} = 0\}. The hat functions Ο•i\phi_i form a basis: Ο•i(xj)=Ξ΄ij\phi_i(x_j) = \delta_{ij} at mesh vertices. The stiffness matrix KK is sparse (bandwidth ∼N\sim \sqrt{N} in 2D) and SPD for coercive BB. Higher-order elements (P2, P3, ...) use additional degrees of freedom at edge midpoints or interior nodes.

ExampleP1 Elements in 1D

For βˆ’uβ€²β€²=f-u'' = f on [0,1][0,1], u(0)=u(1)=0u(0) = u(1) = 0, with NN equally spaced interior nodes: the stiffness matrix is K=1h(2βˆ’1βˆ’12βˆ’1β‹±β‹±β‹±βˆ’12)K = \frac{1}{h}\begin{pmatrix} 2 & -1 & & \\ -1 & 2 & -1 & \\ & \ddots & \ddots & \ddots \\ & & -1 & 2 \end{pmatrix} and the mass-weighted load vector has entries fi=∫01f(x)Ο•i(x) dxf_i = \int_0^1 f(x)\phi_i(x)\,dx. The FEM solution equals the FD solution when fif_i is evaluated by the trapezoidal rule.


Error Estimates

RemarkA Priori Error Estimates

For Pkk elements with mesh size hh: βˆ₯uβˆ’uhβˆ₯H1≀Chk∣u∣Hk+1\|u - u_h\|_{H^1} \leq Ch^k |u|_{H^{k+1}} and βˆ₯uβˆ’uhβˆ₯L2≀Chk+1∣u∣Hk+1\|u - u_h\|_{L^2} \leq Ch^{k+1}|u|_{H^{k+1}} (Aubin-Nitsche trick). The L2L^2 estimate gains one order over the H1H^1 estimate. For P1 elements: O(h)O(h) in H1H^1 and O(h2)O(h^2) in L2L^2. Adaptive mesh refinement uses a posteriori error estimators to locally refine the mesh where the error is large, achieving optimal convergence rates even for singular solutions.