So far, we have seen mathematical models in PDE form. That is not the
only way of developing a model even though it is commonly used.
Many finite element models are based on an alternative form called the
variational problem. The problem is formulated as one where the
goal is to minimize a functional.
The variational form and the partial differential equation form are
equivalent for the same problem. Each can be derived from the other.
Let us look at a simplified problem - the Poisson equation. Simplify
it further by assuming that the temperature is prescribed to be
zero on the entire boundary.
The first stage is to find a functional that applies to the problem.This is the most difficult part of the process. One way of
finding the right functional is to try out a number of different forms
and see if they correspond to known differential equations. This
process is relatively easy for linear problems but not for nonlinear problems.
Recall that a functional converts a function () to a real number.
For the Poisson equation, we can find a functional by thinking in terms
of the membrane problem. In that problem, the total potential energy
is stored energy of the membrane minus the work done by the force. The
functional can be written in the form
where . The functional in equation (18)
represents the total potential energy of the membrane. The first term of
the functional represents the stored energy and the second term represents
the work done by the applied forces. For the membrane the solution is
the one that minimizes potential energy.
Since the same functional also works for the heat conduction problem
(same PDE), we can minimize the functional to get at the temperature
field that we seek.
If the PDE form of the BVP is known, then we can derive the variational form directly from the PDE!
This process has the following steps:
Start with the PDE BVP. Let's look at the Poisson equation for heat conduction as an example. The PDE is
where .
Choose an arbitrary function .
Multiply (23) by and integrate over . We get
The left hand side of the equation has second derivatives. We want simplify things so that only first derivatives are involved. To do this, we use the identity
where is a scalar valued function ( in our case), and is a vector valued function (like ). Apply this identity to the first term in equation (24). We get
Rearrange to get
The first term is (25) still has second derivatives. Apply the Gauss divergence theorem
where is a vector valued function and is the normal to the boundary . The first term of (25) becomes
The final form of (25) is called the Weak Form of the PDE and is written as
At this point, we can break the integral over the boundary into two parts -
an integral over and another over , that is
Recall that the function has to meet the requirement that
on . Therefore,
We also have the boundary condition that the boundary is insulated
() on . This implies that
Then, the weak form becomes
which is the same as the variational boundary value problem
(21). We have arrived at the variational BVP without
knowing the functional to be minimized!
Note that the variational BVP implicitly contains the flux boundary condition and we do not have to apply it separately when solving the BVP. This type of BC is called a natural boundary condition.
The prescribed boundary condition is not satisfied by the variational BVP and has to be applied explicitly when solving the BVP. This type of BC is called an essential boundary condition.
You will often see the variational BVP (27)
written in the form
where
Here is a linear functional acting on and
is an example of a symmetric bilinear form.
A bilinear form is an operator that maps a pair of elements to the real
numbers, and which is linear in each of its slots. Let and
be constants, and let , , and be functions. Then a bilinear
form has the properties that
A symmetric bilinear form has the additional property that
(Show that equation (27) is actually a symmetric bilinear form.)