Consider the Poisson equation on an interval with homogeneous Dirichlet boundary conditions:Two integrations and the endpoint conditions give the exact solution . To approximate it, multiply by a test function that vanishes at both endpoints. Integration by parts givesThe boundary term is zero. Thus the weak formulation is to find such thatThe zero-trace Sobolev space consists of square-integrable functions with square-integrable weak derivatives and zero endpoint values in their continuous representatives; it does not require a classical second derivative. This is why continuous piecewise linear functions are admissible despite corners. The Poincaré inequality makes a coercive bilinear form on . Strang derives this one-dimensional weak formulation, the piecewise-linear hat functions, and their load and derivative-product integrals in the cited lecture; its endpoint example uses a free left endpoint, while both endpoints here are fixed.[ref]
https://ocw.mit.edu/courses/18-085-computational-science-and-engineering-i-fall-2008/676ba0a00eef45a6cb3823c4da61ee11_18-085F08-L18.pdf. Strang, MIT 18.085, Lecture 18, transcript pp. 2–8: weak form, hat basis, and assembly
Take the uniform finite element mesh , , with . The continuous trial space isHere means polynomials of degree at most one on each interval. This is a conforming finite element space in , with interior piecewise-linear hat functions as a basis. Their endpoint values enforce the Dirichlet boundary conditions automatically. Set and test the weak formulation against each :Each interior hat has two slopes and , each over a length . Its squared derivative therefore integrates to . Adjacent hats have opposite slopes on their one shared interval, giving . All other derivative products vanish. The stiffness matrix is the tridiagonal matrixThe load is the area of a triangle of base and height one, including hats next to the boundary. Boundary hats are omitted because the boundary values are prescribed. The piecewise-linear hat function article explains how the same entries arise by adding local two-node contributions.
With four mesh intervals, , there are three unknowns:For example, the first row gives and the middle gives . The coefficients are the nodal values . At , linear interpolation gives , whereas : exactness at the nodes still leaves a visible error between them.
In this model the Galerkin method solution equals the nodal approximation obtained by linear interpolation on any finite element mesh. Indeed, on each interval , is the average of and is constant. Therefore . Summing proves Galerkin orthogonality for , and uniqueness gives . This argument relies on the constant diffusion coefficient, conformity and exact integration; nodal exactness is not a general promise for finite element methods with other operators or integration rules.
On a uniform mesh, direct subtraction of the chord from the parabola gives, on every element of length ,The largest value error is at an element midpoint. Its size and the energy norm error are exactlyThus gives and . With eight elements, , these become and . Halving the mesh spacing quarters the maximum value error but only halves the energy norm error: values and slopes converge at different rates. The figure shows the small value error at its own scale, where the four-to-one reduction becomes clear.
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