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We emphasize that the aim is not to present and analyze these methods rigorously in any way, but only to give an overview of them and their connection to finite elements. In this chapter we study the mathematical theory of finite element methods from a broader perspective by introducing a general theory for linear second order elliptic partial differential equations. This allows us to handle a large class of problems with the same analytical techniques.

We do this by first introducing a general elliptic problem and its abstract weak form posed on a so-called Hilbert space. We show that this weak problem has a solution by proving the Lax-Milgram lemma, and that this solution is unique. Knowing that the solution exists we then show how to approximate it by finite elements. Finally, we prove basic a priori and a posteriori error estimates for the finite element approximation.

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In this chapter we study the concept of a finite element in some more detail. We begin with the classical definition of a finite element as the triplet of a polygon, a polynomial space, and a set of functionals. We then show how to derive shape functions for the most common Lagrange elements. The isoparametric mapping is introduced as a tool to allow for elements with curved boundaries, and to simplify the computation of the element stiffness matrix and load vector.

We finish by presenting some more exotic elements. Many real-world problems are governed by non-linear mathematical models. The drying of paint, the weather, or the mixing of fluids are just some examples of non-linear phenomenons. In fact, most of the physical, biological, and chemical processes going on around us everyday are described by more or less non-linear laws of nature.

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Thus, extensions of the finite element method to non-linear equations are of special interest. In this chapter we study the important transport equation that models transport of various physical quantities, such as density, momentum, and energy, for instance. In particular, the transportation of heat through convection is modeled by this equation. That is, the transfer of heat by some external physical process, such as air blown by a fan, or a moving fluid, for instance. Often, high convection takes place alongside low diffusion i.

As we shall see, this may cause numerical instabilities unless special care is taken. We illustrate with numerical examples. Solid mechanics is arguably one of the most important areas of application for finite elements. Indeed, finite element analysis is used together with computer aided design CAD to optimize and speed up the design and manufacturing process of practically all mechanical structures, ranging from bearings to airplanes. In this chapter we derive the equations of linear elasticity and formulate finite element approximations of them. We do this in the abstract setting of elliptic partial differential equations introduced before and prove existence and uniqueness of the solution using the Lax-Milgram lemma.

A priori and a posteriori error estimates are also proved.

Some effort is laid on explaining the implementation of the finite element method. We also touch upon thermal stress — and modal analysis. In this chapter we study finite elements for incompressible fluids i. External students may apply for a grant to cover travel costs e. If you want to be considered for this grant, please include your expected travel costs in the application form and attach a short CV. Applicants will be selected based on their scientific background.

Good skills in English and a basic knowledge in mathematics and programming is necessary. Presentation Partial Differential Equations and their numerical simulations play a decisive role in scientific researches in a vast of academic and industrial fields. Objectives This summer school gives an introduction to the mathematical theory of the Finite Element method for the approximation of partial differential equations.

Some Remarks on Finite Element Approximations of Crack Problems and an Analysis of Hybrid Methods

Prerequisites The summer school is targeted for up to 30 advanced students of mathematics, engineering or related subjects. What results, as in 0. One important step in this process is the assembly of the innerproduct a u, v by summing its constituent parts over each sub-interval, or element, which are computed separately. This is facilitated through the use of a numbering scheme called the global-to-local index.

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This index, i e, j , relates the local node number, j, on a particular element, e, to its position in the global data structure. Their relationship is represented by the mapping i e, j. The expression 0. In particular, the cardinality of the image of the index mapping i e, j is the dimension of the space of piecewise linear functions. Note that the expression 0. Including v0 in the data structure with a value of zero makes the assembly of bilinear forms equally easy in the presence of boundary conditions. Combining the above estimates, we have proved the following.

Let uS be determined by 0. For such problems, it makes sense to adapt the mesh to match the variation in the solution. Let us consider the problem of approximating functions of one variable whose derivatives are integrable. This is an even weaker condition than what we used in section 0. We begin by deriving a basic estimate analogous to 0.

From its proof and 0. Using the orthogonality relation 0. This will allow us to neglect the term 0. From 0. We summarize the above results in the following theorem. The condition that the derivative of h be small is easy to interpret. However, this does not preclude strong mesh gradings, e. If f is piecewise linear, i. Basic Concepts a the o. That is, explain in both contexts why this problem is not well-posed.

Hint: use a homogeneity argument as in the proof of Theorem 0. Give a value for C. Hint: see the hint in exercise 0. Hint: apply exercise 0. Prove that 22 Chapter 0.

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Halmos , Royden or Rudin A vector space endowed with the topology induced by this metric is called a normed linear space. This theorem whose proof may be found in the references at the beginning of this section is a cornerstone of Lebesgue integration theory. On the other hand, one can show see exercise 1.

Sobolev Spaces 1. In the previous section, we have seen that pointwise values of functions in Lebesgue spaces are irrelevant cf. Thus, it is natural to develop a global notion of derivative more suited to the Lebesgue spaces. First, let us introduce some short-hand notation for calculus partial derivatives, the multi-index notation.

If this is a compact set i. When 1. For x 1. Thus, the claimed formula holds for all x. Sobolev Spaces 1 1. One may check cf. This phenomenon depends on the dimension n as well, precluding a simple characterization of the relation between the calculus and weak derivatives, as the following example shows.

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This example shows that the relationship between the calculus and weak derivatives depends on dimension. That is, whether a function such as x r has a weak derivative depends not only on r but also on n cf. However, the following fact whose proof is left as an exercise shows that the latter is a generalization of the former. The following theorem shows that it is complete. Thus, Theorem 1.

For technical reasons it is useful to introduce the following notation for the Sobolev semi-norms. However, there are more subtle relations among the Sobolev spaces. The existence of Sobolev derivatives imply a stronger integrability condition of a function. To set the stage, let us consider an example to give us guidance as to possible relations among k, m, p, and q for such a result to hold.

From exercise 1. This result says that any function with suitably regular weak derivatives may be viewed as a continuous, bounded function. Note that Example 1. The result will be proved as a corollary to our polynomial approximation theory to be developed in Chapter 4. Note that we can apply it to derivatives of functions in Sobolev spaces to derive the following: 1. The derivation of the variational formulation 0.