Why doesn't this method work? (Re: Simultaneous ODEs)

In summary, the conversation discusses solving simultaneous ordinary differential equations using Fourier transforms. The equations are transformed and rearranged, but the resulting solution is found to be erroneous. The error is believed to be in dividing out a common factor of \nu^2+a^2.
  • #1
Hoplite
51
0
I have been working on a derivation in which the following simultateous ordinary differential equations have appeared:
[tex] f^{(4)}(x)-2 a^2 f''(x)+a^4 f(x)+b(g''(x)-a^2 g(x))=0,[/tex]
[tex] g^{(4)}(x)-2 a^2 g''(x)+a^4 g(x)-b(f''(x)-a^2 f(x))=0,[/tex]
where [tex]a[/tex] and [tex]b[/tex] are constants. I figured that I could solve this using Fourier transforms. First, I transform the above, using [tex]\nu[/tex] as the transform space analogue of [tex]x[/tex], into the following:
[tex] (\nu^2 +a^2 )\hat f(\nu ) -b \hat g(\nu )=0,[/tex]
[tex] (\nu^2 +a^2 )\hat g(\nu ) +b \hat f(\nu )=0.[/tex]
I then rearrange these equations via substitution into
[tex] [(\nu^2 +a^2 )^2 +b^2 ] \hat f(\nu ) =0,[/tex]
[tex] [(\nu^2 +a^2 )^2 +b^2 ] \hat g(\nu )=0.[/tex]
Taking the inverse Fourier transform then results in
[tex] f^{(4)}(x)-2a^2 f''(x)+(a^4 +b^2 )f(x)=0,[/tex]
[tex] g^{(4)}(x)-2a^2 g''(x)+(a^4 +b^2 )g(x)=0.[/tex]

However, after I solve for these two ODEs using the boundary conditions, I find that the resulting answer is erroneous. I can only conclude that the above methodoly doesn't work, although I can't see why.

Could anyone point out the mathematical error in the above steps?
 
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  • #2
can you show your transform... shouldn't you get factors of [itex]nu^4[/itex]?
 
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  • #3
The OP is dividing out a common factor of [itex]\nu^2+a^2[/itex].
 
  • #4
vela said:
The OP is dividing out a common factor of [itex]\nu^2+a^2[/itex].
Yes, that's what I've done.
 

1. Why do my simultaneous ODEs not produce the expected results?

There could be several reasons why your method is not working as expected. One possible reason is that there may be an error in your code or input data. Check for any typos, incorrect variable assignments, or missing values. Another reason could be that your initial conditions are not set correctly. Make sure they are consistent with the problem you are trying to solve. It is also possible that your chosen method is not suitable for the specific ODEs you are trying to solve. Consider trying a different method or adjusting the parameters of your current method.

2. How do I know if my simultaneous ODEs are solvable?

Not all systems of ODEs have analytical solutions, so it is important to check if your simultaneous ODEs are solvable before attempting to solve them. One way to check is by looking at the coefficients of your equations. If they are constants or functions that can be integrated, then your ODEs may be solvable. Another way is to use a computational tool or software to solve the ODEs numerically.

3. My simultaneous ODEs work for some initial conditions but not others. Why is this happening?

This could be due to the sensitivity of the ODEs to the initial conditions. Some systems of ODEs are more sensitive to initial conditions than others, and even a small change in the initial conditions can result in significantly different solutions. This is known as the butterfly effect. To address this issue, try adjusting your initial conditions or using a more robust numerical method that can handle sensitivity to initial conditions.

4. Can I use any method to solve simultaneous ODEs?

No, not all methods are suitable for solving simultaneous ODEs. Some methods are better suited for specific types of ODEs or have certain limitations. It is important to choose a method that is appropriate for your specific system of ODEs and meets your accuracy and efficiency requirements.

5. How can I improve the accuracy of my method for solving simultaneous ODEs?

There are a few ways to improve the accuracy of your method. One way is to use a smaller step size in your numerical solver. This means dividing the interval of integration into smaller subintervals and computing the solution at more points. Another way is to use a higher-order method, which means using a method that uses more information from previous steps to estimate the solution at the next step. You can also try adjusting the tolerance or convergence criteria of your method to achieve a more accurate solution.

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