chingel said:
Do I understand it correctly, if I say that the string does divide itself into two parts, three parts, four parts etc, and these parts vibrate and the sum of these movements of the string (since they are vibrating at the same time and in some places add, in some places interfere) creates the overall triangular kinky wave seen on the string, that moves back and forth on the string and was discussed in the pdf linked beforehand?
You are correct, however that's not really a good way of looking at it. It's true that the spatial 'modes' (i.e. the dividing the string into even parts and making sinusoids) affect the output, but it's not nearly as direct as it would seem. Like you said, thanks to Fourier analysis, we can indeed take the shape of the string at any time and turn it into a sum of sinusoidal terms based on some frequency omega, which is directly related to dividing the length of the string into even parts. So if f(x,t) is the displacement of the string at position x at time t, then we can say, for any t:
f(x,t)=\sum_{k=0}^{\infty} A_k(t) \cdot \sin (k\omega_0 x)
Where A
k are some functions of time, which we can find with Fourier analysis. In fact, the solution to the simple 1D wave equation comes exactly in a form like this. However, notice that the sin term is a function of x, and
not t. This means that any time-variance has to come from the A
k(t) term. It is these terms that will determine the frequency output at any point x, not the sine terms, yet it's the sine terms that generate the shape profile. From what I've said here, there's not even a guarantee that the A
k(t) oscillate at predictable frequencies, yet the sine terms have predictable frequencies. It so happens that they do in most cases, but just looking at the shape of the string doesn't guarantee that. It's a much more finicky relationship. So yes, you can always break the string shape down into a sum of sinusoid-shaped strings, but this isn't as closely related to the frequency output as it might seem. What determines the frequency output is the way in which these 'sinusoidal strings' oscillate back and forth, which, while related, is a different story.
In response to your question about the displacement of the string at one point being the output: that is actually a fairly reasonable assumption, especially in the case of an electric guitar. In the case of acoustic instruments like an acoustic guitar or piano, such an assumption can't be made as easily, but even then, just summing the displacements of a couple points on the string can be a pretty good approximation. In that case, actually, a Fourier analysis of the shape can be useful because you can look at the sinusoids in the spatial domain to see where each frequency component is strongest (peaks of the spatial sinusoid) and weakest (nodes of the spatial sinusoid). Analysis like that explains why if you listen at the edge of a string, it sounds more 'tinny' than if you listen at the middle. However, this is only helping you find information about how those frequencies change as you move along the string, and not about the frequencies themselves.
At the moment of initial release, the string is not moving and hence KE = 0. All the energy in the system resides in PE (the stretch of the string). Immediately after t = 0, the displacement at every point on the string decreases toward equilibrium, so that PE decreases and KE increases. The phases of all Fourier modes are necessarily such that the initial condition is fulfilled.
(I'm kind of responding to the conversation you've been having with sophiecentaur rather than this particular post) The statement that a Fourier analysis of the string shape does not correspond to an analysis of the frequency output is true, as I've explained above. When you turn the shape at time t into a Fourier series, you're finding one particular set of A
k values. You can make arguments based on energy analysis and analysis of how the string should respond to draw conclusions about the time-dependence of the A
k(t), however, just from turning the shape profile at anyone time into a Fourier series, you cannot glean any information about the actual frequency output. It's true that the initial shape/velocity will uniquely determine the output, but that's less to do with the spatial frequency characteristic of the shape and more to do with the fact that those are boundary conditions for the PDE model being used. You
must consider other factors in order to get information about the frequency output, as it's not a direct relationship. Particularly if you add non-linearities to the model, Fourier analysis of the shape can become almost meaningless. In that case, you can start with a triangular shape, which can easily be expressed as a sum of sine terms, and yet you might find that the frequency content of the output shifts over time, and the string may go in and out of tune. There would be no reason to believe that just from the shape profile, and yet if you pluck a guitar string really hard, you can hear this frequency distortion.