I've waited for this question for a long time :)
Fully NDSolve-based Numerical Solution
There actually exist 2 issues here:
NDSolve
can't handle unsmooth i.c. very well by default.
NDSolve
can't add proper artificial b.c. for the initial value problem (Cauchy problem) for the 1-dimensional wave equation.
The first issue is easy to solve: just make the spatial grid dense enough and fix its size to avoid NDSolve
trying using too much points to handle those roughness. I guess finite element method in and after v10 can handle this issue in a even better way, but since I'm still in v9, I'd like not to explore this more.
What's really… big is the second issue. It's easy to solve the initial value problem for the 1-D wave equation analytically, we just need to use DSolve
in and after v10.3 or d´Alembert's formula or do a Fourier transform, but when solving it numerically, we need to add proper artificial b.c., which NDSolve
doesn't know how to. (NDSolve
does add artificial b.c. when b.c. isn't enough, but as far as I know, it seldom works well, actually it's even unclear that what artificial b.c. is added, see this post for more information. )
Adding proper artificial b.c. for wave equation can be troublesome when the equation becomes more complicated (2D, 3D, nonlinear, etc.), but luckily, what you want to solve is just a simple 1D wave equation, then the corresponding artificial b.c. (usually called absorbing boundary condition) is quite simple:
{lb, rb} = {-10, 10};
(* absorbing boundary condition *)
abc = D[y[x, t], x] + direction D[y[x, t], t] == 0 /.
{{x -> lb, direction -> -1}, {x -> rb, direction -> 1}}
mol[n_Integer, o_: "Pseudospectral"] := {"MethodOfLines",
"SpatialDiscretization" -> {"TensorProductGrid", "MaxPoints" -> n,
"MinPoints" -> n, "DifferenceOrder" -> o}}
WaveEquation = D[y[x, t], {x, 2}] - D[y[x, t], {t, 2}] == 0;
cond1 = Piecewise[{{1 - Abs[x - 1], Abs[x - 1] < 1}, {0, Abs[x - 1] > 1}}];
cond2 = Piecewise[{{1, 3 < x < 4}}, 0];
ic = {y[x, 0] == cond1, Derivative[0, 1][y][x, 0] == cond2};
nsol = NDSolveValue[{WaveEquation, ic, abc}, y, {x, lb, rb}, {t, 0, 10},
Method -> mol[600, 4](* fix the spatial grid and make it dense enough *)]
Animate[Plot[nsol[x, t], {x, lb, rb}, PlotRange -> {0, 2}], {t, 0, 10}]
NDSolve
still spits out eerri
and eerr
warning, but it's not a big deal in this case:
Fourier-transform-based Analytical Solution
As shown by rewi, DSolve
can solve the problem after v10.3. Here I just want to show how to solve it with Fourier transform (the ft
function is from here):
teqn = ft[{WaveEquation, ic}, x, w] /. HoldPattern@FourierTransform[a_, __] :> a
tsol = y[x, t] /. First@DSolve[teqn, y[x, t], t]
asol[x_, t_] = InverseFourierTransform[tsol, w, x]
(* 1/4 ((2 + t - x) Sign[2 + t - x] + (4 + t - x) Sign[
4 + t - x] + (3 + t - x) Sign[-3 - t + x] +
2 (1 + t - x) Sign[-1 - t + x] + (-t + x) Sign[-t + x] - (-4 + t + x) Sign[-4 + t +
x] + (-3 + t + x) Sign[-3 + t + x] + (-2 + t + x) Sign[-2 + t + x] -
2 (-1 + t + x) Sign[-1 + t + x] + (t + x) Sign[t + x]) *)
Compared to the solution given by DSolve
, this solution doesn't involve Integrate
so it's more suitable for numeric evaluation.