Skip to main content

differential equations - Stiff coupled system of ODE's


I am having trouble with a possible stiff nonlinear system of ODE's.


Eqn1 = 
D[Psi[r], {r, 4}] - XX1*D[D[Psi[r], {r, 2}]^3, {r, 2}] +
D[P[r], {r, 1}] - D[Psi[r], {r, 2}] == 0;


Eqn2 = D[P[r], {r, 2}] + D[Psi[r], {r, 2}]*(1 - XX1*D[Psi[r], {r, 2}]^2) == 0;

Eqns =
{Eqn1, Eqn2,
Psi[1.5] == 0.75,
Psi[-1.] == -0.75,
Psi'[1.5] == -1,
Psi'[-1.] == -1,
P[1.5] == 0,

P[-1.] == 1}

XX1 = 1;

sol = NDSolve[Eqns, {Psi, P}, {r, -1, 1.5}]

XX1 is the one parameter which is causing the problems. Because this XX1 is the coefficient of the nonlinear term in the ODE's. If I choose this XX1 to be something other than zero, the system becomes nonlinear and then NDSolve does not converge.



Answer



An alternative approach, more accurate and efficient, is as follows. Consider the two ODEs in the question, slightly restructured.


eqn1 = D[D[psi[r], {r, 2}] (1 - xx1*D[psi[r], {r, 2}]^2), {r, 2}] + 

D[p[r], {r, 1}] - D[psi[r], {r, 2}] == 0
eqn2 = D[p[r], {r, 2}] + D[psi[r], {r, 2}] (1 - xx1*D[psi[r], {r, 2}]^2) == 0

psi[r], psi'[r], and p[r] do not enter explicitly into these equations. Therefore, define qsi[r] as Sqrt[xx1] psi''[r] and q[r] as p'[r], so that the equations become


qn1 = D[qsi[r] (1 - qsi[r]^2), {r, 2}] + q[r] - qsi[r] == 0
qn2 = D[q[r], {r, 1}] + qsi[r]*(1 - qsi[r]^2) == 0

A modest amount of algebra shows that the boundary conditions become


NIntegrate[q[r], {r, -1, 3/2}] + Sqrt[xx1] == 0
NIntegrate[qsi[r], {r, -1, 3/2}] == 0

NIntegrate[r qsi[r], {r, -1, 3/2}] + 4 Sqrt[xx1] == 0

Next, define t[r] as qsi[r] - qsi[r]^3 to eliminate the singularity in qn1 at qsi[r] = 1.


qsi /. FullSimplify[Solve[t == qsi - qsi^3, qsi, Reals], 
-(2/(3 Sqrt[3])) < t < 2/(3 Sqrt[3])]
(* {Root[t - #1 + #1^3 &, 1], Root[t - #1 + #1^3 &, 2], Root[t - #1 + #1^3 &, 3]} *)
Plot[%, {t, -(2/(3 Sqrt[3])), 2/(3 Sqrt[3])}, AxesLabel -> {t, qsi},
PlotLegends -> "Expressions"]

enter image description here



With the second branch of this final transformation, the equations and boundary conditions become


qn1 = D[t[r], {r, 2}] + q[r] - Root[t[r] - #1 + #1^3 &, 2] == 0
qn2 = D[q[r], {r, 1}] + t[r] == 0
NIntegrate[q[r], {r, -1, 3/2}] + Sqrt[xx1] == 0
NIntegrate[Root[t[r] - #1 + #1^3 &, 2], {r, -1, 3/2}] == 0
NIntegrate[r Root[t[r] - #1 + #1^3 &, 2], {r, -1, 3/2}] +4 Sqrt[xx1] == 0

The second and third integrals are real only for -(2/(3 Sqrt[3])) < t < 2/(3 Sqrt[3]). The absence of answers to 110534 suggests that this requirement cannot be imposed using NDSolve with Method -> "Shooting". Instead, use FindRoot directly.


xx1 = 8.7677 10^-3;
qn1 = D[t[r], {r, 2}] + q[r] - Root[t[r] - #1 + #1^3 &, 2] == 0;

qn2 = D[q[r], {r, 1}] + t[r] == 0;
qns = {qn1, qn2, t[-1] == a, t'[-1] == b, q[-1] == c};
st = ParametricNDSolve[qns, {t, q}, {r, -1, 3/2}, {a, b, c}, MaxStepFraction -> 1/1000];
int1[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[q[a, b, c][r] /. st, {r, -1, 3/2}] + Sqrt[xx1];
int2[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[Root[t[a, b, c][r] - #1 + #1^3 &, 2] /. st, {r, -1, 3/2}];
int3[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[r Root[t[a, b, c][r] - #1 + #1^3 &, 2] /. st, {r, -1, 3/2}] + 4 Sqrt[xx1];
qval = Quiet@FindRoot[{int1[a, b, c], int2[a, b, c], int3[a, b, c]},

{a, 0.3848882573269839`, .3, 2/(3 Sqrt[3]) }, {b, -0.4895029166208631`},
{c, 0.0935952879725864`}, MaxIterations -> 500]
Unevaluated[{int1[a, b, c], int2[a, b, c], int3[a, b, c]}] /. %
Plot[Evaluate[{Root[t[a, b, c][r] - #1 + #1^3 &, 2],
t[a, b, c]'[r]/(1 - 3 Root[t[a, b, c][r] - #1 + #1^3 &, 2]^2),
q[a, b, c][r]} /. st /. %%], {r, -1, 3/2}]
Plot[Evaluate[{t[a, b, c][r], t[a, b, c]'[r], q[a, b, c][r]} /. st /. %%%], {r, -1, 3/2},
AxesLabel -> {r, "qsi, qsi', q"}]
(* {a -> 0.384898, b -> -0.489519, c -> 0.0935965} *)
(* {-9.71445*10^-17, -6.99907*10^-16, -8.88178*10^-16} *)


enter image description here


This particular xx1 has been chosen to yield t[-1] = a = 0.384898, which is very close to 2/(3 Sqrt[3]), indicating that xx1 = 8.7677 10^-3 is a very good approximation to the upper bound on xx1, above which the boundary conditions cannot be satisfied.


psi[r] and p[r] can be obtained by straightforward integration of qsi[r] and q[r].


sp = NDSolve[{D[psi[r], {r, 2}] == Root[t[a, b, c][r] - #1 + #1^3 &, 2]/Sqrt[xx1] /. st 
/. qval, D[p[r], r] == q[a, b, c][r]/Sqrt[xx1] /. st /. qval,
psi[-1] == -3/4, psi'[-1] == -1, p[-1] == 1}, {psi, p}, {r, -1, 3/2}];
Plot[Evaluate[{psi[r], p[r]} /. sp], {r, -1, 3/2}, AxesLabel -> {r, "psi, p"}]

enter image description here



Addendum: Direct calculation of xx1 upper bound


Determining the upper bound on xx1 turns out to be surprisingly easy, given a good initial guess. Set t[-1] == 2/(3 Sqrt[3]), the maximum value it can assume, and vary xx1 with FindRoot


Clear[xx1];
qn1 = D[t[r], {r, 2}] + q[r] - Root[t[r] - #1 + #1^3 &, 2] == 0;
qn2 = D[q[r], {r, 1}] + t[r] == 0;
qns = {qn1, qn2, t[-1] == 2/(3 Sqrt[3]), t'[-1] == b, q[-1] == c};
st = ParametricNDSolve[qns, {t, q}, {r, -1, 3/2}, {b, c}, MaxStepFraction -> 1/1000];
int1[xx1_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[q[b, c][r] /. st, {r, -1, 3/2}] + Sqrt[xx1];
int2[xx1_?NumericQ, b_?NumericQ, c_?NumericQ] :=

NIntegrate[Root[t[b, c][r] - #1 + #1^3 &, 2] /. st, {r, -1, 3/2}];
int3[xx1_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[r Root[t[b, c][r] - #1 + #1^3 &, 2] /. st, {r, -1, 3/2}] + 4 Sqrt[xx1];
qvql = Quiet@FindRoot[{int1[xx1, b, c], int2[xx1, b, c], int3[xx1, b, c]},
{xx1, 8.7677 10^-3}, {b, -0.4895029166208631`}, {c, 0.0935952879725864`},
MaxIterations -> 500]
Unevaluated[{int1[xx1, b, c], int2[xx1, b, c], int3[xx1, b, c]}] /. %
Plot[Evaluate[{Root[t[b, c][r] - #1 + #1^3 &, 2],
t[b, c]'[r]/(1 - 3 Root[t[b, c][r] - #1 + #1^3 &, 2]^2),
q[b, c][r]} /. st /. %%], {r, -1, 3/2}, AxesLabel -> {r, "qsi, qsi', q"}]

(* {xx1 -> 0.00876784, b -> -0.489523, c -> 0.0935967} *)
(* {2.26208*10^-15, 1.27339*10^-13, 1.94289*10^-14} *)

Thus, the upper bound is xx1 = 0.00876784. The corresponding Plot is indistinguishable from the second to the last one above.


Second Addendum: Solutions above the "upper bound"


As suggested by MMM, it is possible - although more difficult - to obtain solutions for xx1 greater than the purported upper bound given in the last section. Doing so requires using branch 3 and often branch 1, as well as branch 2 of the t transform plotted in the first figure. The following code accomplishes this.


Clear[st]; r1 = -1; r2 = 3/2; xx1 = 2.5 10^-2;
qns = {D[q[r], {r, 1}] + t[r] == 0, t[-1] == a, t'[-1] == b,
q[-1] == c, n[-1] == If[xx1 > 0.008767841540390384`, 3, 2],
WhenEvent[t[r] > 2/(3 Sqrt[3]) - 10^-4, {n[r] -> 2, t'[r] -> -t'[r], r1 = r, r2 = 3/2}],

WhenEvent[t[r] < -2/(3 Sqrt[3]) + 10^-4, {n[r] -> 1, t'[r] -> -t'[r], r2 = r}]};
st = ParametricNDSolve[{qns, D[t[r], {r, 2}] + q[r] == Root[t[r] - #1 + #1^3 &, n[r]]},
{t, q, n}, {r, -1, 3/2}, {a, b, c}, MaxStepFraction -> 1/1000,
DiscreteVariables -> {n[r] \[Element] {1, 2, 3}}];
int1[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
Chop@NIntegrate[q[a, b, c][r] /. st, {r, -1, 3/2}] + Sqrt[xx1];
int2[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[Root[t[a, b, c][r] - #1 + #1^3 &, 3] /. st, {r, -1, r1}] +
NIntegrate[Root[t[a, b, c][r] - #1 + #1^3 &, 2] /. st, {r, r1, r2}] +
NIntegrate[Root[t[a, b, c][r] - #1 + #1^3 &, 1] /. st, {r, r2, 3/2}];

int3[a_?NumericQ, b_?NumericQ, c_?NumericQ] :=
NIntegrate[r Root[t[a, b, c][r] - #1 + #1^3 &, 2] /. st, {r, -1, r1}] +
NIntegrate[r Root[t[a, b, c][r] - #1 + #1^3 &, 2] /. st, {r, r1, r2}] +
NIntegrate[r Root[t[a, b, c][r] - #1 + #1^3 &, 1] /. st, {r, r2, 3/2}] + 4 Sqrt[xx1];
qval = Quiet@FindRoot[{int1[a, b, c], int2[a, b, c], int3[a, b, c]},
{a, 0.26367683907672707`, -2/(3 Sqrt[3]), 2/(3 Sqrt[3])},
{b, 0.40781910948554423`}, {c, 0.0918387339602277`}]
Unevaluated[{int1[a, b, c], int2[a, b, c], int3[a, b, c]}] /. %
Plot[Evaluate[{Piecewise[{{Root[t[a, b, c][r] - #1 + #1^3 &, 2],
r1 < r < r2}, {Root[t[a, b, c][r] - #1 + #1^3 &, 3],

r <= r1}, {Root[t[a, b, c][r] - #1 + #1^3 &, 1], r2 <= r}}],
t[a, b, c]'[r]/(1 - 3 Piecewise[{{Root[t[a, b, c][r] - #1 + #1^3 &, 2],
r1 < r < r2}, {Root[t[a, b, c][r] - #1 + #1^3 &, 3],
r <= r1}, {Root[t[a, b, c][r] - #1 + #1^3 &, 1], r2 <= r}}]^2),
q[a, b, c][r]} /. st /. %%], {r, -1, 3/2}, AxesLabel -> {r, "qsi, qsi', q"}]
Plot[Evaluate[{t[a, b, c][r], t[a, b, c]'[r], q[a, b, c][r]} /.
st /. %%%], {r, -1, 3/2}, AxesLabel -> {r, "t, t', q"}, Exclusions -> {r1, r2}]
(* {a -> 0.219976, b -> 0.368499, c -> 0.0839676} *)
(* {-1.38255*10^-10, 4.27128*10^-10, 4.16582*10^-10} *)


enter image description here enter image description here


t and t'are included for completeness in the second plot.


The guess a, equal to t[-1], needed to obtain a solution becomes smaller as xx1 becomes larger, and some experimentation is necessary to obtain a sufficiently good value. Even then, computing the curves for a given xx1 takes several minutes on my computer.


Comments

Popular posts from this blog

plotting - How to draw lines between specified dots on ListPlot?

I would like to create a plot where I have unconnected dots and some connected. So far, I have figured out how to draw the dots. My code is the following: ListPlot[{{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4,13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full] I have thought using ListLinePlot command, but I don't know how to specify to the command to draw only selected lines between the dots. Do have any suggestions/hints on how to do that? Thank you. Answer One possibility would be to use Epilog with Line : ListPlot[ {{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4, 13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full, Epilog -> { Line[ ...

equation solving - Invert and fit implicitly defined curve

I need to fit an implicitly defined curve. I thought I could get some data out of Solve , and then using FindFit . Therefore, I would like to find the relation the parametric curve defined by $F(x,y)=0$: Solve[-(1/2) + 1/2 (0.41202 BesselK[0, 0.1 Sqrt[x^2 + y^2]] + (0.101483 x BesselK[1, 0.1 Sqrt[x^2 + y^2]])/Sqrt[x^2 + y^2]) == 0, y] But I can't get an output: Solve was unable to solve the system with inexact coefficients or the system obtained by direct rationalization of inexact numbers present in the system. Since many of the methods used by Solve require exact input, providing Solve with an exact version of the system may help. >> Edit: In particular, I would like to fit the data coming from the curve with the expression of another curve, and not with a function $f(x)$. In particular, since this clearly looks like a cardioid , I would like it to fit to something like it. What other strategies could I try?

dynamic - How can I make a clickable ArrayPlot that returns input?

I would like to create a dynamic ArrayPlot so that the rectangles, when clicked, provide the input. Can I use ArrayPlot for this? Or is there something else I should have to use? Answer ArrayPlot is much more than just a simple array like Grid : it represents a ranged 2D dataset, and its visualization can be finetuned by options like DataReversed and DataRange . These features make it quite complicated to reproduce the same layout and order with Grid . Here I offer AnnotatedArrayPlot which comes in handy when your dataset is more than just a flat 2D array. The dynamic interface allows highlighting individual cells and possibly interacting with them. AnnotatedArrayPlot works the same way as ArrayPlot and accepts the same options plus Enabled , HighlightCoordinates , HighlightStyle and HighlightElementFunction . data = {{Missing["HasSomeMoreData"], GrayLevel[ 1], {RGBColor[0, 1, 1], RGBColor[0, 0, 1], GrayLevel[1]}, RGBColor[0, 1, 0]}, {GrayLevel[0], GrayLevel...