Reduction of differential equations then numerical methods

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Homework Help Overview

The discussion revolves around the numerical approximation of a system of differential equations modeling the internal forces of a bungee cord. The original poster is tasked with using the Euler forward method, a first-order Runge-Kutta approach, to solve the equations represented by matrices and vectors.

Discussion Character

  • Exploratory, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • The original poster attempts to reduce the second-order differential equation into a system of first-order equations. They express concerns about applying matrix data in their numerical method. Other participants provide insights into the formulation of the system and the implications of the chosen numerical method.

Discussion Status

Some participants have noted the importance of the stability of the numerical method and the impact of step size on the results. The original poster has indicated that adjustments to their method and step size resolved their issues, although there remains a lack of consensus on the initial question regarding data application.

Contextual Notes

The discussion includes references to specific matrices and vectors, as well as the requirement to implement the solution in a spreadsheet format. There are indications of challenges with visualizing the results of the numerical method.

danielL
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Homework Statement



I have a function that attempts to imitate the internal forces of the cord used for bungee jumping. I have been told to resolve it using Runge-Kutta 1st order numerical aproximation, therefore i have to reduce it to a system of equations. The preffered Runge-Kutta method is euler forward: y1 = y0 + k1 where k1 = h*f(y0). Plus I have to do this in a spreadsheet.

Homework Equations



M*q''(t)+K*q(t)=b(t)

Where M and K are 3x3 matrix and k and b are vectors with 3 components

The Attempt at a Solution



If I make q'(t) = v(t)
then v'(t) = M^(-1)*[b(t)-K*q(t)]

i can divide v'(t) = M^(-1)*b(t)+[-M^(-1)*K*q(t)]
and then obtain a vector plus matriz to solve it. My problem is that i don't know how to take the data from the matriz and apply it.

Thanks
 
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Your differential system (written as a system of first order differential equations) is:

[tex] \left[ \begin{array}{1c}<br /> q' \\<br /> v' \\<br /> \end{array} \right] = \left[ \begin{array}{1c} v(t) \\ M^{-1}b(t)-M^{-1}Kq(t) \\\end{array} \right]<br /> [/tex]And so your Runge-Kutta numerical method is:

[tex] \left[ \begin{array}{1c}<br /> q_{n+1} \\<br /> v_{n+1} \\<br /> \end{array} \right] = \left[ \begin{array}{1c} v_{n} \\ M^{-1}b(t_{n})-M^{-1}Kq_{n} \\\end{array} \right]<br /> [/tex]

supposedly you have the intial values vo, qo, so you go on generating the solution at the mesh points ti=i*h, where h is your step-size. The matrix M is constant so all you have to do is invert it and use it as I've indicated above to generate your numerical solution . . . in your spreadsheet go on generating the solution for each time step in a new row of cells based on the value of the previous time step which you take from the previous row of cells and the values of the components of K, M^(-1) and b which you store in a separate set of cells (you can evaluate b(tn) in a separate cell at each time step) , . . . um, I'm not sure if I understand your question altogether lol.
 
Yeah actually i read my message back, and it was kind of funny, my problem was that the graph didn't end up the way i was told it was supposed to look like. Ended up being a problem of both the method selected and the step i had chosen, fixed those and it fell into place.

I'll attach it when i get home in case anyone else was pondering the problem, thanks for responding
 
Oh I see, okay:) yes, the numerical method you chose is an explicit one and has a certain region of absolute stability that limits the step-size you can use for it to work well . . .
glad you sorted it out :)
 
yeah that was exactly the problem, function went haywire
thanks for the support
 

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