A I need some help with the derivation of fourth order Runge Kutta

AI Thread Summary
The discussion revolves around the derivation of the fourth-order Runge-Kutta scheme, specifically focusing on the confusion regarding equation C.54 and the notation used in the derivation. Participants clarify that the "ordinary" f in C.54 represents the function evaluated at specific points, while f_2, f_3, and f_4 are derived from partial derivatives. The notation t=t^n is explained as a convenience for indicating the evaluation point of the function, with Δt representing the step size. The conversation emphasizes the importance of understanding the Taylor series and intermediate evaluations in the Runge-Kutta method. Overall, the participants guide each other through the complexities of the derivation and notation used in the referenced material.
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Hey guys, I need your help regarding the derivation of the fourth runge kutta scheme.
So, I found http://www.ss.ncu.edu.tw/~lyu/lecture_files_en/lyu_NSSP_Notes/Lyu_NSSP_AppendixC.pdf
this derivation. Maybe you have a clue what tehy are doing in C.54.
So before this they are calculating the taylor expansion series of f_1,f_2,f_3,f_4. This makes somehow sense. But I get confused when they throw everything together in equation C.54.
Why is therre just the "ordinary" f everywhere instead of f_2,f_3,f_4 ? I thougt that they just insert everything into equation C.46, but this seems not to be the case, or they are skipping some steps (like getting f_4 back to f_1 or so...)
I hope that somebody takes a look at the derivation and can tell me what exactly they are doing there
 
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C.51 .. C.53 show how to replace f2, f3, f4 with terms expressions of partial derivatives of f. It says that is what they did.
 
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On the righthand side of 47, 51, 53 there are only ##f##, no ##f_2## etc. ?!

Never mind, FC was faster
 
Thank you for the answer :)
 
Hey guys,
I got one more question. I hope you do not mind it.
I spend some time with the equations but, there is still one thing I do not understand. What do they mean with
t=t^n ?
I wrote an email to the author of the text and got this reply:
fd2366d65d.jpg


But this does not really help me. I do not know what exactly this means. \Delta t is from what I know the step size "h" or (x-a) (this is the notation the english wikipedia uses in the article about the taylor expansion).
I hope that you want to help me one last time.
Have a nice day
 
It's just a notation convenience to write ##t^n## instead of ##t=n\Delta t##. He doesn't use it in lecture 2, but in table 3.1 he does -- in a manner that isn't fully consistent with his convention. But it's readable. Try to master 2nd order first by writing it out in full - if stuck, grab another textbook or pdf.

For you it might be confusing that in section in appendix C.1, ##x## plays the role of ##t## in the Runge Kutta section C.2
 
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Ok. So I will try to go along the Taylor series notation of wikipedia right now:
dadd9a8618.png

so f is the same f as from the appendix.
\Delta t is the step size and is the same as (x-a).
So does this mean, that (f)_{t=t^n} is the same as f(a) ?
This would mean, that t=t^n is the position at which I evaluate my function.
 
Higher order Runge Kutta evaluates the function at intermediate points. E.g. for 4th order in the starting point (C.47), halfway (##\Delta t\over 2##) using ##f_1## (C.48), halfway (##\Delta t\over 2##) using ##f_2## (C.49) and at the end of the step (##\Delta t##) using ##f_3## (C.50). So: yes, in this case ##\Delta t## is the step size. But: no, the function is evaluated not just at ##t^n## but also at ##t^{n+{1\over 2}}##

Compare these to the notation in table 3.1 -- post if there is any doubt whatsoever left over.

BvU said:
in a manner that isn't fully consistent with his convention
I didn't really do him justice there: it's pretty consistent, but he doesn't use it all over, probably for reasons of clarity :smile:
 
Sorry for the confusion by my bad choice of words.
I think I got it, but I just want to be sure:
When we take a look at e.g. C.53
we have f_4 = (f)_{t=t^n}+\Delta t (\frac{\partial f}{\partial t}+f_3 \frac{\partial f}{\partial y})_{t=t^n}.
If we just look at the beginning now; it means that I will take the value of f at the position t^n.
(while the function f_4 get's evaluated at the point t+\Delta t).
Is this now finally correct ?
 
  • #10
I think you've got it !
Perhaps the animation of slide 56 here helps picture what happens in an RK4 routine ?
 
  • #11
Thank you so much :)
 
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