Some months ago, I solved a problem that required an approximate solution to the non-linear, second order, ordinary differential equation:
x" = x^2, (1)
but I have since forgotten how to approach this, and am a little confused as to which method, or methods, I should use.
I seem to remember writing the equation as:
x" = (x + k)^2, (2)
where k is a very small perturbation from the trajectory.
The aim is to determine whether or not the trajectory, orbit, or path, is stable, and I am also aware that one can even write u as a truncated series expansion, depending on the accuracy of the solution required, as follows:
x = x_0 + kx_1 + (k^2)x_2 + (k^3)x_3 + . . .
and
d(x)/dt = d(x_0 + kx_1 + (k^2)x_2 + (k^3)x_3 + . . .)/dt
where at t = 0, x(0) = a,
and then substitute at least one of these expansions into equation (1).
I have made many attempts to solve this problem recently (including multiplying both sides of equation (1) by the derivative of x with respect to t, and then integrating - which only partially helps, as I only then get half way to the solution – and I have also attempted using matrices, the Jacobian, its associated eigenvalues, and eigenvectors amongst other techniques), but I am really getting nowhere, and I cannot even find a remotely similar solution in any of my books, nor anywhere at all on the Internet.
I also seem to remember that the original question, up to six months ago, possibly required calculation of the zeros, prior to solution (which I think, in this case would be the two repeated values of x = - k, unless this was related to another question), so I wondered if anyone could suggest one or more appropriate methods of solution to adopt – along with the name of equation (1) and any texts that may highlight this particular ODE, along with further details of solution. I also think that it is related to the ODE, known as the equation of path, in Newtonian Mechanics, perturbation theory and non-linear dynamics, as follows:
u” + u = a + bu^2, (3)
but would certainly appreciate any suggestions for equation (1).
Thanks. SWM