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I have the two-dimensional Laplacian $(\nabla^2 T(x,y)=0)$ coupled with another equation. The Laplacian is defined over $x\in[0,L], y\in[0,l]$. On manipulating the second equation (which I have described in the Origins section of my question) I have managed to reduce the problem to a boundary value problem on the Laplacian subjected to the following boundary conditions

$$\frac{\partial T(0,y)}{\partial x}=\frac{\partial T(L,y)}{\partial x}=0 \tag 1$$

$$\frac{\partial T(x,0)}{\partial y}=\gamma \tag 2$$

$$\frac{\partial T(x,l)}{\partial y}=\zeta \Bigg[T(x,l)-\Bigg\{\alpha e^{-\alpha x}\Bigg(\int_0^x e^{\alpha s }T(s,y)\mathrm{d}s+\frac{t_{i}}{\alpha}\Bigg)\Bigg\}\Bigg] \tag 3$$

$\gamma, \alpha, \zeta, t_i$ are all constants $>0$. Can anyone suggest a way to solve this problem ?


Origins

The 3rd boundary condition is actually of the following form:

$$\frac{\partial T(x,l)}{\partial y}=\zeta \Bigg[T(x,l)-t\Bigg] \tag 4$$ The $t$ in $(4)$ is governed by the following equation (this is the other equation I mentioned earlier):

$$\frac{\partial t}{\partial x}+\alpha(t-T(x,l))=0 \tag 5$$

where it is known that $t(x=0)=t_i$. To derive $(3)$, I solved $(5)$ using the method of integrating factor and substituted in $(4)$.

My original problem is the Laplacian coupled with $(5)$.


Is there a way to solve this analytically in Mathematica considering the integral type boundary conditions at play? I will include the equations in the form of Mathematica code

eq = Laplacian[T[x, y], {x, y}] == 0
bcx = {D[T[x, y], x] == 0 /. x -> 0, D[T[x, y], x] == 0 /. x -> L}
bcy1 = D[T[x, y], y] == γ /. y -> 0
bcy2 = D[T[x, y], y] == ζ (T[x, l] - α E^(-α x) (Integrate[E^(α s) T[s, y], {s, 0, x}] + ti/α))/. y -> l

Physical meaning

The problem describes the flow of a fluid (with temperature $t$ and described by $(5)$) over a rectangular plate (at $y=l$) heated from the bottom (at $y=0$). The fluid is thermally coupled to the plate temperature $T$ through boundary condition $(3)$ which is the convection or Robin type condition.


Attempt using Finite Fourier transform

I tired using the finite Fourier sine transform about which I learned from this answer. The definitions required to run the code below can be obtained from xzczd's this post.

eq = Laplacian[T[x, y], {x, y}] == 0
bcx = {D[T[x, y], x] == 0 /. x -> 0, D[T[x, y], x] == 0 /. x -> L}
bcy = {D[T[x, y], y] == γ /. y -> 0, D[T[x, y], y] == ζ (T[x, l] - α E^(-α x) (Integrate[E^(α s) T[s, y], {s, 0, x}] + ti/α)) /. y -> l}
rule = finiteFourierSinTransform[a_, __] :> a;
teq = finiteFourierSinTransform[eq, {y, 0, l}, n] /. Rule @@@ Flatten@{bcy, D[bcy, x]} /. rule
tbcx = finiteFourierSinTransform[bcx, {y, 0, l}, n] /. rule
tsol = T[x, y] /. First@DSolve[Simplify[#, n] &@{teq, tbcx}, T[x, y], x]
sol = inverseFiniteFourierSinTransform[tsol, n, {y, 0, l}]

The output for tsol gives a weird answer: enter image description here which can be inverted but won't evaluate on substituting the value of the constants because of the presence of True terms

Some practical values of the constants are

γ=15.8346, α=574.866, ζ=4.633, ti=300, L=0.06, l=0.001

Attempt 2 Using Bill Watt's answer here which desccribes a similar problem but in cylindrical coordinates

NOTE The constant $\beta$ used in the code below is the same as $\zeta$ in the preceding part of this question.

pde = D[T[x, y], x, x] + D[T[x, y], y, y] == 0
T[x_, y_] = X[x] Y[y]
pde/T[x, y] // Expand
xeq = X''[x]/X[x] == -a^2
DSolve[xeq, X[x], x] // Flatten
X[x_] = X[x] /. % /. {C[1] -> c1, C[2] -> c2}
yeq = Y''[y]/Y[y] == a^2
DSolve[yeq, Y[y], y] // Flatten
Y[y_] = (Y[y] /. % /. {C[1] -> c3, C[2] -> c4})
T[x_, y_] = Xp[x] + Yp[y]
xpeq = Xp''[x] == b
DSolve[xpeq, Xp[x], x] // Flatten
Xp[x_] = Xp[x] /. % /. {C[1] -> c5, C[2] -> c6}
ypeq = Yp''[y] + b == 0
DSolve[ypeq, Yp[y], y] // Flatten
Yp[y_] = Yp[y] /. % /. {C[1] -> 0, C[2] -> c7}
T[x_, y_] = X[x] Y[y] + Xp[x] + Yp[y]
pde // FullSimplify
(D[T[x, y], x] /. x -> 0) == 0
c6 = 0
c2 = 0
c1 = 1
(D[T[x, y], x] /. x -> L) == 0
b = 0
a = (n π)/L
$Assumptions = n \[Element] Integers
(D[T[x, y], y] /. y -> 0) == γ
c4 = c4 /. Solve[Coefficient[%[[1]], Cos[(π n x)/L]] == 0, c4][[1]]
c7 = c7 /. Solve[c7 == γ, c7][[1]]
T[x, y] // Collect[#, c3] &
T[x, y] /. n -> 0
T0[x_, y_] = % /. c3 -> 0
Tn[x_, y_] = T[x, y] - T0[x, y] // Simplify
pdet = (t'[x] + α (t[x] - T[x, l]) == 0)
pde2 = (tn'[x] + α (tn[x] - Tn[x, l]) == 0)
(DSolve[pde2, tn[x], x] // Flatten)
tn[x_] = (tn[x] /. % /. C[1] -> c8)
pde20 = t0'[x] + α (t0[x] - T0[x, l]) == 0
DSolve[pde20, t0[x], x] // Flatten
t0[x_] = t0[x] /. % /. C[1] -> c80
c8 = c8 /. Solve[tn[0] == 0, c8][[1]]
c80 = c80 /. Solve[t0[0] == tin, c80][[1]]
tn[x_] = tn[x] // Simplify
t[x_] = t0[x] + tn[x]
pdet // Simplify
bcf = (D[T[x, y], y] /. y -> l) == β (T[x, l] - t[x])
bcf[[1]] /. n -> 0
bcf[[2]] /. n -> 0 // Simplify
bcfn0 = % == %% /. {2 c3 + c5 -> c30}
Integrate[bcfn0[[1]], {x, 0, L}] == Integrate[bcfn0[[2]], {x, 0, L}]
c5 = c30 /. Solve[%, c30][[1]] // Simplify
ortheq = Integrate[bcf[[1]]*Cos[(n*Pi*x)/L], {x, 0, L}] == Integrate[bcf[[2]]*Cos[(n*Pi*x)/L], {x, 0, L}]
c3 = c3 /. Solve[%, c3][[1]] // Simplify
t0[x_] = t0[x] // Simplify
tn[x_] = tn[x] // Simplify
T0[x_, y_] = T0[x, y] // Simplify
Tn[x_, y_] = Tn[x, y] // Simplify

Now using values and doing the summation

α = 57.487;
β = 4.6333;
γ = 10.5673;
tin = 300;
L = 0.03;
l = 0.006;
T[x_, y_, mm_] := T0[x, y] + Sum[Tn[x, y], {n, 1, mm}]
t[x_, mm_] := t0[x] + Sum[tn[x], {n, 1, mm}]

On plotting T[x,y] that is the solid temperature along the flow length at different y using mm=20 Fourier terms using

Plot[{Evaluate[T[x, 0, 20]], Evaluate[T[x, l/2, 20]], Evaluate[T[x, l, 20]]}, {x, 0, L}]

, I get the following plot

enter image description here

As can be seen the solid temperature decreases along the length. This is nonphysical since it should increase along the flow length as the wall is getting heated from the bottom ($y=0$). Although interstingly the fluid temperature $t$ shows the correct behaviour as can be seen from the plot below

enter image description here

For a different set of constant values corresponding to a steel plate (the one above is for a copper plate) the T[x,y] plate shows an increase but weirdly oscillates

α = 57.487;
β = 257.313;
γ = 263.643;
tin = 300;
L = 0.06;
l = 0.001;

enter image description here

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  • 1
    $\begingroup$ You're using finite Fourier transform in wrong way. To understand which type of problem can be solved with finite Fourier transform, please check the properties of finite Fourier transform carefully. However, even if you've used finite Fourier transform correctly, I doubt if the technique will help in this case. In short, eq $(5)$ is on the way. $\endgroup$
    – xzczd
    Commented Jul 18, 2020 at 2:41
  • $\begingroup$ @xzczd Appreciate the input. However, I could not understand the last line of your comment. Do you mean to say that due to presence of Eq. $(5)$, Fin.FT cannot be used ? If so, can you suggest a different way to solve the Laplacian coupled with $(5)$ subjected to bcs $(1), (2), (4)$. $\endgroup$
    – Avrana
    Commented Jul 18, 2020 at 3:49
  • 1
    $\begingroup$ To be precise, finite FT can be used to eliminate derivatives, but the result will be a system consists of 2 equations involving summations and integrals, which is almost useless. Sadly I can't think out a way to solve this problem analytically. $\endgroup$
    – xzczd
    Commented Jul 18, 2020 at 4:36
  • $\begingroup$ @xzczd Thanks anyway. $\endgroup$
    – Avrana
    Commented Jul 18, 2020 at 4:56
  • $\begingroup$ @IndrasisMitra I don't understand why are you talking about analytical solution while using numerical method with series? $\endgroup$ Commented Jul 22, 2020 at 17:11

2 Answers 2

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To verifier analytical solution we use numerical model:

reg = Rectangle[{0, 0}, {L, l}]; \[Alpha] = 57.487;
\[Zeta] = \[Beta] = 4.6333;
\[Gamma] = 10.5673;
ti = 300;
L = 0.03;
l = 0.006;

Ti[0][x_] := ti;
Do[U[i] = 
  NDSolveValue[-Laplacian[u[x, y], {x, y}] == 
    NeumannValue[- \[Zeta] (u[x, y] - Ti[i - 1][x]) y/
        l + \[Gamma] (1 - y/l), y == 0 || y == l], 
   u, {x, y} \[Element] reg];
 Ti[i] = NDSolveValue[{t'[x] + \[Alpha] (t[x] - U[i][x, l]) == 0, 
    t[0] == ti}, t, {x, 0, L}];
 , {i, 1, 50}]

The fluid temperature visualization on last 11 iterations and on 50 iterations in one point x=L/2

{Plot[Evaluate[Table[Ti[i][x], {i, 40, 50}]], {x, 0, L}, 
  PlotLegends -> Automatic, PlotRange -> All], 
 ListPlot[Evaluate[Table[Ti[i][L/2], {i, 1, 50}]], PlotRange -> All]}

So 20 iteration could be good to solve this problem. We can check that fluid temperature behaves as an analytical solution. Figure 1

Plate temperature visualization

{DensityPlot[U[50][x, y], {x, y} \[Element] reg, 
  ColorFunction -> "Rainbow", PlotLegends -> Automatic, 
  FrameLabel -> Automatic], 
 Plot[{U[50][x, l], U[50][x, l/2], U[50][x, 0]}, {x, 0, L}, 
  PlotRange -> All, AxesLabel -> Automatic], 
 Plot[{U[50][0, y], U[50][L/2, y], U[50][L, y]}, {y, 0, l}, 
  AxesLabel -> Automatic]} 

Figure 2

For second set of data we need some mesh and 10 iterations only:

Needs["NDSolve`FEM`"];
reg = Rectangle[{0, 0}, {L, l}];


\[Alpha] = 57.487;
\[Zeta] = \[Beta] = 257.313;
\[Gamma] = 263.643;
tin = 300;
L = 0.06;
l = 0.001;

Ti[0][x_] := ti;
Do[U[i] = 
  NDSolveValue[-Laplacian[u[x, y], {x, y}] == 
    NeumannValue[- \[Zeta] (u[x, y] - Ti[i - 1][x]) y/
        l + \[Gamma] (1 - y/l), y == 0 || y == l], 
   u, {x, y} \[Element] reg];
 Ti[i] = NDSolveValue[{t'[x] + \[Alpha] (t[x] - U[i][x, l]) == 0, 
    t[0] == ti}, t, {x, 0, L}];
 , {i, 1, 10}]

{Plot[Evaluate[Table[Ti[i][x], {i, 1, 10}]], {x, 0, L}, 
  PlotLegends -> Automatic, PlotRange -> All], 
 ListPlot[Evaluate[Table[Ti[i][L/2], {i, 1, 10}]], PlotRange -> All]}

Figure 3

{DensityPlot[U[10][x, y], {x, y} \[Element] reg, 
  ColorFunction -> "Rainbow", PlotLegends -> Automatic, 
  FrameLabel -> Automatic], 
 Plot[{U[10][x, l], U[10][x, l/2], U[10][x, 0]}, {x, 0, L}, 
  PlotRange -> All, AxesLabel -> Automatic], 
 Plot[{U[10][0, y], U[10][L/2, y], U[10][L, y]}, {y, 0, l}, 
  AxesLabel -> Automatic]}

Figure 4

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3
  • $\begingroup$ Thanks for this. It now seems that the boundary conditions are correctly set because the behavior of the temperatures in the numerical solution seem correct. The wall temperatures rise along the flow direction and the highest wall temperatures can be found at the bottom of the plate (y=0). This certainly helped. But I still cannot understand where did I go wrong in my analytical approach as I keep on getting unphysical behaviour there. $\endgroup$
    – Avrana
    Commented Jul 22, 2020 at 4:29
  • $\begingroup$ @IndrasisMitra I used method of iterations . As equivalent method we can use method of false transient with $\partial_t$ in equation (5) to get an analytical solution. $\endgroup$ Commented Jul 22, 2020 at 11:26
  • $\begingroup$ I am afraid I am not aware of the method of false transient. Is there any chance you can solve this problem using it and post a solution. I am sorry if it is too much to ask. $\endgroup$
    – Avrana
    Commented Jul 22, 2020 at 12:08
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I executed your code and used your data and I can find nothing wrong, although I get a different plot for T[x,y].

Plot[{Evaluate[T[x, 0, 50]], Evaluate[T[x, l/2, 50]], 
  Evaluate[T[x, l, 50]]}, {x, 0, L}]

enter image description here

It is different than your post, but it is with your posted code. My plot for t[x] is the same as yours.

Checking your boundary conditions.

at x = 0

D[T0[x, y], x] /. x -> 0
D[Tn[x, y], x] /. x -> 0

both return 0

at x = L

dtn = D[Tn[x, y], x] /. x -> L

Table[dtn /. y -> 0, {n, 1, 10}]
{-1.37357*10^-15, 2.30234*10^-16, -1.13824*10^-16, 
 3.15585*10^-17, -1.93063*10^-17, 5.99123*10^-18, -3.93119*10^-18, 
 1.28056*10^-18, -8.7099*10^-19, 2.91729*10^-19}

Table[dtn /. y -> l/2, {n, 1, 10}]
{-1.44192*10^-15, 2.77195*10^-16, -1.68232*10^-16, 
 5.99327*10^-17, -4.84429*10^-17, 2.01841*10^-17, -1.79418*10^-17, 
 7.95632*10^-18, -7.38651*10^-18, 3.3817*10^-18}

Table[dtn /. y -> l, {n, 1, 10}]
{-1.65374*10^-15, 4.37237*10^-16, -3.83469*10^-16, 
 1.96078*10^-16, -2.23798*10^-16, 1.30007*10^-16, -1.5984*10^-16, 
 9.75869*10^-17, -1.24413*10^-16, 7.81094*10^-17}

All approximately 0 for machine precision.

At y = 0

D[T[x, y, 50], y] /. y -> 0
(*10.5673*)

which returns γ

and finally at y = l

Plot[{D[T[x, y, 50], y] /. 
   y -> l, β (T[x, l, 50] - t[x, 50])}, {x, 0, L}]

enter image description here

Since the two curves almost overlay each other, I would say you have a boundary match here too.

So it looks like the differential equations with their b.c.'s have been solved correctly. If you still think there is something wrong, you may want to check for errors in the boundary conditions themselves.

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6
  • $\begingroup$ Really appreciate this input. It certainly seems now that the equations have been solved correctly given the bc(s) are correct. The constant values I utilized correspond to a copper plate. When I do the same for a steel plate I get a different solid temperature plot which is increasing as expected but shows quite some oscillations. I have added it to my original question, Thanks anyway for taking this effort. You have always been really helpful. $\endgroup$
    – Avrana
    Commented Jul 21, 2020 at 4:11
  • $\begingroup$ I will now take a look at my equations. Probably the fluid equation $(5)$ should not have $T(x,l)$ but instead must have some sort of average solid temperature like $\int_o^l \frac{T(x,y)}{l}\mathrm{d}y$ $\endgroup$
    – Avrana
    Commented Jul 21, 2020 at 4:19
  • $\begingroup$ Looking at Alex Tounev's posted numerical approach, it seems that the bcs and the equations are correctly setup. I think I have made some mistake in my analytical procedure which upends the results $\endgroup$
    – Avrana
    Commented Jul 22, 2020 at 4:43
  • $\begingroup$ When I plot the 4th bc as Plot[{D[U[50][x, y], y] /. y -> l, \[Zeta] (U[50][x, l] - Ti[50][x])}, {x, 0, L}] the two curves don't match. In fact, one is the negative of the other, similar to the two solutions. $\endgroup$
    – Bill Watts
    Commented Jul 25, 2020 at 20:40
  • 1
    $\begingroup$ It still looks like your solution is correct as far as solving the differential equations and the bc's in this case. The calculated behavior is puzzling though. $\endgroup$
    – Bill Watts
    Commented Jul 26, 2020 at 5:34

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