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Some Stable Solutions
\def \half {\frac{1}{2}}
\def \slechts {\quad \Longleftrightarrow \quad}
A Finite Difference scheme is associated with any (normed) tri-diagonal system
of equations in the following manner:
- b.T_{i-1} + T_i - a.T_{i+1} = 0
The equations, when put in this form, can be solved in a direct fashion. Let's
try the most simple of all possible solutions: a constant. Substitution of
T_i = C gives:
- b.C + C - a.C = 0 \quad \Longrightarrow \quad a + b = 1
Assuming that C \ne 0 (which would result in an even more trivial solution).
It is seen that a constant solution can be obtained only if (minus) the sum of
the off-diagonal elements is one.
The next trivial solution of the finite difference equation would be a straight
line. Substitute T_i = C.i + D with D \ne 0 and C \ne 0 , giving:
- b.\left[ C.(i-1) + D \right]
+ \left[ C.i + D \right]
- a.\left[ C.(i+1) + D \right] =
C.i ( - b + 1 - a ) + D ( - b + 1 - a ) + ( b - a ) = 0
Resulting in the same condition a + b = 1 , augmented with b - a = 0. It is
concluded that a {\em linear solution} can only be obtained for:
a = b = \half
Let another possible solution be given as:
T_i = \left( \frac{b}{a} \right)^i
And substitute. Then:
- b \left( \frac{b}{a} \right)^{i-1}
+ \left( \frac{b}{a} \right)^i
- a \left( \frac{b}{a} \right)^{i+1} = 0
\quad \Longrightarrow
( b / a )^i ( - b . a / b + 1 - a . b / a ) =
( b / a )^i ( - b + 1 - a ) = 0
Resulting again in the condition a + b = 1 . A more general solution may be
cast into the form:
T_i = C \left( \frac{b}{a} \right)^i + D
Suppose that we have boundary conditions, like:
T_1 = 1 \quad \mbox{and} \quad T_N = 0
Then the constants C and D can be calculated explicitly, resulting in:
T_i = \frac{ (b/a)^i - (b/a)^N }{ (b/a) - (b/a)^N }
= \frac{ (b/a)^{i-1} - (b/a)^{N-1} }{ 1 - (b/a)^{N-1} }
This result is more general than it seems at first sight, because it may be
multiplied with an arbitrary constant and another arbitrary constant may be
added to it, thus adapting it to quite arbitrary boundary conditions:
T_i := (T_1 - T_N) . T_i + T_N
It is recognized that the condition a + b = 1 plays a rather predominant role
in its relationship to the solutions which are found so far. The meaning of the
condition is that the sum of the row coefficients in the (normed) matrix equals
zero. Things are clarified further by writing the equations in a slightly
different manner:
T_i = b.T_{i-1} + a.T_{i+1}
Knowing that b \ge 0, a \ge 0 and a+b = 1. It is concluded therefrom that
T_i is a {\em weighted mean} of its neighbouring values, which means that it
will always lie in between T_{i-1} and T_{i+1}:
T_{i-1} \le T_{i} \le T_{i+1} \quad \mbox{or} \quad
T_{i+1} \le T_{i} \le T_{i-1}
Hence, irrespective of any boundary conditions, the function behaviour of the
numerical solution will be continuously decreasing or continuously increasing.
It shows no "wiggles". Such a solution T_i is commonly called {\em stable}.
Thus, in fact, we are in search here for Stable Solutions of the tri-diagonal
equations. It is remarked, in addition, that stability conditions, like a+b=1
for the 1-D case, are well known and commonly accepted, as they belong to the
"Four Basic Rules" in Patankar's book (1980).
Having established stability, our Stable numerical Solution is recalled:
T_i = \frac{ (b/a)^{i-1} - (b/a)^{N-1} }{ 1 - (b/a)^{N-1} }
Because, with help of the "Quotient Function", it can be cast now into the
following form:
T_i = \frac{ e^{P.(i-1).dx} - e^{P.(N-1).dx} }{ 1 - e^{P.(N-1).dx} }
\slechts
T(x) = \frac{ e^{P.x} - e^{P.L} }{ 1 - e^{P.L} }
Where x = (i-1).dx is the 1-D coordinate and L is the total length of the
mesh. Herewith, the general Stable (: a+b=1) numerical Solution becomes quite
alike an Analytical one:
T(x) = (T_0 - T_L) \frac{ e^{P.x} - e^{P.L} }{ 1 - e^{P.L} } + T_L
This solution is applicable to 1-D problems of Convection and Diffusion. It is
concluded therefrom that any tri-diagonal system of linear equations, where the
off-diagonal elements are negative and the rows sum up to zero, is actually a
blueprint for Convection and Diffusion.
The number P.L in the exponents is recognized as the {\em P\'echlet number}.
In real life, the dimensionless P\'echlet number has the following
meaning: Pe = \rho.c.v.L/\lambda , where \rho = density (kg/m^3),
c = heat capacity (J/kg/K), v = velocity (m/s) and
\lambda = thermal conductivity (J/s/m/K).
For the problem of 1-D Convection and Diffusion, the off-diagonal coefficients
a and b can be written in a form which will be useful in the subsequent
work. Define \epsilon by:
\epsilon = b - a \qquad \mbox{while knowing} \qquad a + b = 1
By addition and subtraction we find:
b = \half (1 + \epsilon) \quad \mbox{and} \quad a = \half (1 - \epsilon)
\quad \mbox{where} \quad -1 \le \epsilon \le +1
It is remarked that the range of \epsilon is quite restricted in the first
place. Furthermore it can be argued that, as the grid spacing becomes smaller
and smaller with successive refinements of the grid, then \epsilon also must
become smaller and smaller:
\frac{1-\epsilon}{1+\epsilon} = \frac{a}{b}(dx \rightarrow 0) \rightarrow 1
With help of a clever trick, we can express \epsilon solely in quotients of
the off-diagonal coefficients. Divide namely nominator and denominator by
\sqrt{a.b} in:
\epsilon = \frac{b - a}{b + a} =
\frac{\sqrt{b/a} - \sqrt{a/b}}{\sqrt{b/a} + \sqrt{a/b}} =
\frac{e^{+P/2.dx}-e^{-P/2.dx}}{e^{+P/2.dx}+e^{-P/2.dx}}
The latter expression is recognized as a Hyperbolic Tangent: tanh(P/2.dx) ,
as will be seen in one of the subsequent paragraphs. A sketch of the tanh
function reveals that \epsilon will have the following properties:
\lim_{P \rightarrow -\infty} \epsilon(P) = -1 \qquad
\epsilon(0) = 0 \qquad
\lim_{P \rightarrow +\infty} \epsilon(P) = +1
When cast in Finite Element form, the analytical Convection-Diffusion scheme
reads as follows:
\left[ \begin{array}{cc} + a & - a \\
- b & + b \end{array} \right] =
\left[ \begin{array}{cc}
+ \half - \half \epsilon & - \half + \half \epsilon \\
- \half - \half \epsilon & + \half + \half \epsilon
\end{array} \right]
The trace of any such element matrix is 1.
Double check for pure diffusion and for pure convection, respectively:
P = 0 \quad \Longrightarrow \quad
\left[ \begin{array}{cc} + a & - a \\
- b & + b \end{array} \right] =
\left[ \begin{array}{cc} + 1/2 & - 1/2 \\
- 1/2 & + 1/2 \end{array} \right]
P = \infty \quad \Longrightarrow \quad
\left[ \begin{array}{cc} + a & - a \\
- b & + b \end{array} \right] =
\left[ \begin{array}{cc} 0 & 0 \\
- 1 & + 1 \end{array} \right]
P = - \infty \quad \Longrightarrow \quad
\left[ \begin{array}{cc} + a & - a \\
- b & + b \end{array} \right] =
\left[ \begin{array}{cc} + 1 & - 1 \\
0 & 0 \end{array} \right]
The latter expressions are demanding for a boundary condition at the inlets
x=0 and x=L respectively. Otherwise, the temperature T(x) at these places
would be undefined.