Solving a system of two nonlinear second order ODEs (Mechanical vibrations)

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Discussion Overview

The discussion revolves around methods for solving a system of two nonlinear second order ordinary differential equations (ODEs) related to mechanical vibrations. Participants explore both analytical and numerical approaches, as well as the implications of assumptions made during the solution process.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant inquires about common methods for solving a specific system of nonlinear second order ODEs.
  • Another participant suggests the assumption of small angles, noting that this allows for simplifications such as \(\sin(\theta) \approx \theta\) and neglecting certain terms.
  • A different participant proposes that while an analytic solution may be desired, simulating the system using numerical integration could be beneficial.
  • There is a discussion about the neglect of the term \(\theta \cdot \ddot{\theta}\) and the need for more information regarding the order of \(\ddot{\theta}\) before making such assumptions.
  • One participant expresses a need for resources or explanations on numerical solutions, indicating a lack of experience with numerical methods.
  • Another participant explains the basic idea behind numerical schemes, including the use of Taylor series expansions and the trade-offs between computational cost and stability.
  • There is a clarification that numerical methods are applicable to nonlinear ODEs, countering the misconception that they are only for linear cases.
  • It is noted that numerical methods may sometimes be preferred even when an analytic solution exists due to computational efficiency.

Areas of Agreement / Disagreement

Participants express varying opinions on the applicability of numerical methods to nonlinear ODEs and the assumptions made in the context of small angle approximations. There is no clear consensus on the best approach to take, and multiple viewpoints remain regarding the solution methods.

Contextual Notes

Participants highlight the importance of understanding the stability and accuracy of numerical methods, as well as the implications of neglecting certain terms in the equations. The discussion reflects a range of experiences with numerical analysis, indicating varying levels of familiarity with the concepts involved.

Bartok
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I was wondering what the common methods for solving such a system are:

[itex]2 m \ddot{x} - m l \ddot{θ} θ + k x = 0[/itex]
[itex]m l^{2} \ddot{θ} - m l \ddot{x} θ + m g l θ = 0[/itex]
 
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You have probably already used the assumption of small angles: [itex]\sin(\theta)\approx\theta[/itex]
Since theta is small, you can neglect all products like [itex]\theta^{2}[/itex] but also [itex]\theta\cdot\ddot{\theta}[/itex]
 
Hey Bartok and welcome to the forums.

Do you need an analytic solution? Even if this is required, it would be beneficial if you simulated the system of equations using a numerical integration scheme. Have you come across these?
 
bigfooted said:
You have probably already used the assumption of small angles: [itex]\sin(\theta)\approx\theta[/itex]
Since theta is small, you can neglect all products like [itex]\theta^{2}[/itex] but also [itex]\theta\cdot\ddot{\theta}[/itex]

Yes, I have used the [itex]\sin(\theta)\approx\theta[/itex] assumption but I don't think the [itex]\theta\cdot\ddot{\theta}[/itex] could also be neglected without prior info about the order of [itex]\ddot{\theta}[/itex].

chiro said:
Hey Bartok and welcome to the forums.

Do you need an analytic solution? Even if this is required, it would be beneficial if you simulated the system of equations using a numerical integration scheme. Have you come across these?

Thank you.

Not necessarily looking for an analytic solution. Just wanted to know about the available options. Got a deadline coming up and got to solve this somehow!
Could you explain a bit about the numerical solution as how to approach a system like this or link me to some resources? I derived it in a nonlinear vibrations problem which I'm quite new to.
 
Bartok said:
Not necessarily looking for an analytic solution. Just wanted to know about the available options. Got a deadline coming up and got to solve this somehow!
Could you explain a bit about the numerical solution as how to approach a system like this or link me to some resources? I derived it in a nonlinear vibrations problem which I'm quite new to.

The basic idea for a lot of the schemes is that you make use of more terms corresponding to those of the taylor series expansion of the function. It's not exactly using these but what happens is that the scheme tries to eliminate so many lower order terms so that the error term is higher than all these terms. For example O(x^5) means that all the powers of x < 5 have been handled by the scheme and the lowest error term relates to the fifth power of your independent variable (this is a 1D example, but the same idea holds in more dimensions).

The taylor series gives a way to represent a function as a series in term of the evaluation of derivatives at a certain point: basically if we know every derivative at one point we can represent the entire function.

So what a lot of schemes do is they evaluate so many terms to get a specific order. The euler method evaluates one derivative term, and things like Runge-Kutta evaluate more terms (and thus cost more computation time). The tradeoff is usually more stable scheme = more computation time.

But it has to be done to get specific constraints on the errors: the goal of numeric analysis is to introduce schemes with known properties particular of local and global errors. These both help analyze the stability of the scheme with respect to classes of DE's.

Here are some links to some methods: The Euler one is very simple but I would look at the other ones first considering you have a non-linear DE:

http://en.wikipedia.org/wiki/Euler_method

http://en.wikipedia.org/wiki/Runge–Kutta_methods
 
Thanks chiro. I don't have much numerical experience and I was under the impression that the well-known methods are applicable only to linear DEs.
 
Bartok said:
Thanks chiro. I don't have much numerical experience and I was under the impression that the well-known methods are applicable only to linear DEs.

The applications are mainly for non-linear DE's as these are the ones where the analytic solution can't be figured out. That's the power of numerical methods in that if the solution is stable and accurate enough it doesn't matter what the system of DE's corresponds to.

In fact there are some situations where numerical schemes are used even when an analytic solution exists due to that it may be computationally better to do the numerical scheme over the analytic scheme (it sounds crazy, but these situations do exist).
 

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