Solving System x'' + αx = 0: An Eigenform Approach

In summary, the system given is an mdof system with two equations and two unknowns. Using the eigenvalue method, the solutions are y1 = 0 and y2 = Acosh(sqrt(2a)x) + Bsinh(sqrt(2a)x). However, this does not satisfy the boundary conditions and therefore a different method or approach may need to be used to solve the system.
  • #1
c0der
54
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Homework Statement



Solve the system x'' + αx = 0

x = [ x1 x2 ]
α constant

Homework Equations



x'' + αx = 0 Where x is a vector [x1 x2]

The Attempt at a Solution



The solution of x'' + αx = 0 is x = Acosh(√α x) + Bsinh(√α x)

Differentiating x

x' = √α*Acosh(√α x) + √α*Bsinh(√α x)
x'' = α*Acosh(√α x) + α*Bsinh(√α x)

Plugging this back into the original ODE

α*Acosh(√α x) + α*Bsinh(√α x) - α(Acosh(√α x) + Bsinh(√α x)) = 0 is satisfied

I can't get this in Eigenform to solve for the system. What do I do in this case?
 
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  • #2
c0der said:

Homework Statement



Solve the system x'' + αx = 0

x = [ x1 x2 ]
α constant

Homework Equations



x'' + αx = 0 Where x is a vector [x1 x2]

The Attempt at a Solution



The solution of x'' + αx = 0 is x = Acosh(√α x) + Bsinh(√α x)
That makes no since at all. x is a two dimensional vector but you have it as both a single function and the independent variable!
IF we were given a single real function, x, satisfying x''+ αx= 0 THEN the solution would be either x= Asinh(√αt)+ Bcosh(√αt), x= Asin(√αt)+ Bcos(√αt), or x= At+ B, depending upon whether α was positive, negative, or 0 and t is the (unnamed in the equation) independent variable.

Are you given that α single real number? If so then the general solution would be
[tex]\begin{bmatrix}x_1(t) \\ x_2(t)\end{bmatrix}= \begin{bmatrix}Asinh(√αt)+ Bcosh(√αt) \\ Csinh(√αt)+ Dcosh(√αt)\end{bmatrix}[/tex]
if α> 0,
[tex]\begin{bmatrix}x_1(t) \\ x_2(t)\end{bmatrix}= \begin{bmatrix}Asin(√αt)+ Bcos(√αt) \\ Csin(√αt)+ D cos(√αt)\end{bmatrix}[/tex]
lf α< 0,
and
[tex]\begin{bmatrix}x_1(t) \\ x_2(t)\end{bmatrix}= \begin{bmatrix}At+ B \\ Ct+ D\end{bmatrix}[/tex]
if α= 0.

Differentiating x

x' = √α*Acosh(√α x) + √α*Bsinh(√α x)
x'' = α*Acosh(√α x) + α*Bsinh(√α x)

Plugging this back into the original ODE

α*Acosh(√α x) + α*Bsinh(√α x) - α(Acosh(√α x) + Bsinh(√α x)) = 0 is satisfied

I can't get this in Eigenform to solve for the system. What do I do in this case?
I'm not sure what you mean by "eigenform" but if α is a single number then the differential equation can be written in matrix form as
[tex]\begin{bmatrix}x_1(t) \\ x_2(t)\end{bmatrix}'= \begin{bmatrix}α & 0 \\ 0 & α\end{bmatrix}\begin{bmatrix}x_1(t)\\ x_2(t)\end{bmatrix}[/tex]
which has α as the only eigenvalue.
 
  • #3
Sorry wasn't clear enough

Apologies, I should have been clear. This is the system:

d^2/dx^2(y1) = α(y1 - y2)
d^2/dx^2(y2) = α(y2 - y1)

Hence, why your set of solutions won't work. This is why I tried to put it into eigenform, like the harmonic oscillator problem, which is easily done to get the frequencies for an mdof system. This method doesn't work for this type of problem
 
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  • #4
c0der said:
Apologies, I should have been clear. This is the system:

d^2/dx^2(y1) = α(y1 - y2)
d^2/dx^2(y2) = α(y2 - y1)

This is why I tried to put it into eigenform, like the harmonic oscillator problem, which is easily done to get the frequencies for an mdof system. This method doesn't work for this type of problem.

It is obvious from inspection that if [itex]u = y_1 + y_2[/itex] and [itex]v = y_1 - y_2[/itex] then
[tex]
\frac{d^2 u}{dx^2} = 0 \\
\frac{d^2 v}{dx^2} = 2av
[/tex]
 
  • #5
Yes but how do you solve it formally? I use the eigenvalue method to get:

y1 = 0
y2 = Acosh(sqrt(2a)x) + Bsinh(sqrt(2a)x) but differentiating this twice and subbing this into the second equation and solving for y1 doesn't satisfy the boundary conditions
 
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FAQ: Solving System x'' + αx = 0: An Eigenform Approach

What is the purpose of "Solving System x'' + αx = 0: An Eigenform Approach"?

The purpose of "Solving System x'' + αx = 0: An Eigenform Approach" is to provide a mathematical method for solving systems of differential equations with the inclusion of the eigenvalues and eigenvectors of the system.

How does the Eigenform Approach differ from other methods of solving systems of differential equations?

The Eigenform Approach differs from other methods of solving systems of differential equations in that it utilizes the eigenvalues and eigenvectors of the system to simplify the problem and find a solution. This method is particularly useful for systems with constant coefficients.

Can the Eigenform Approach be applied to systems with variable coefficients?

Yes, the Eigenform Approach can be applied to systems with variable coefficients. However, it may require more advanced techniques and may not always yield a closed-form solution.

What are the benefits of using the Eigenform Approach?

Using the Eigenform Approach can provide a more elegant and efficient solution to systems of differential equations, as it simplifies the problem by utilizing the eigenvalues and eigenvectors. It can also provide insights into the behavior and stability of the system.

Are there any limitations to the Eigenform Approach?

One limitation of the Eigenform Approach is that it may not always provide a closed-form solution for systems with variable coefficients. Additionally, it may not be applicable to all types of differential equations, such as non-linear systems.

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