How can I use variable transformation to obtain a solution for this ODE?

In summary, The given ODE can be solved using a variable transformation and integration to obtain a solvable form. Differentiating the original ODE and substituting the given solution can also lead to a solvable form. However, finding the constant in the solution requires further algebraic manipulations and the use of hyperbolic identities.
  • #1
Dustinsfl
2,281
5
Given the following ODE
\[
\left(\frac{du}{dx}\right)^2 = \mu u^2 - \frac{2\alpha}{\sigma + 2}u^{\sigma + 2} - \frac{\gamma}{\sigma + 1}u^{2(\sigma + 1)}
\]
How do I obtain
\[
u(x) = \left(\frac{A}{B + \cosh(Dx)}\right)^{1/\sigma}
\]
where
\(A = \frac{(2 + \sigma)B\mu}{\alpha}\), \(B = \text{sgn}(\alpha)\left[1 + \frac{(2 + \sigma)^2\gamma}{(1 + \sigma)\alpha^2}\mu\right]^{-1/2}\), and \(D = \sigma\sqrt{\mu}\) with the variable transformation \(y = u^{-\sigma}\)?
 
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  • #2
Is the power on the second term rhs of the equation correct?
 
  • #3
Jester said:
Is the power on the second term rhs of the equation correct?

It should be \(\sigma + 2\).

I don't see how this variable change makes anything easier.
\(u = y^{-1/\sigma}\) so \(du = -\frac{1}{\sigma}y^{-(1 + 1/\sigma)}dy\) and \(u^{\sigma + 2} = y^{-(1+2/\sigma)}\) and \(u^{2(\sigma + 1)} = y^{-2(1+1/\sigma)}\).
 
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  • #4
You'll notice that each term has $u^{-2/\sigma}$ common so they cancel. So when you simplify your equation you should get

$\left(\dfrac{du}{dx}\right)^2 = au^2 + bu + c$

for some $a, b$ and $c$. This is solvable.
 
  • #5
Jester said:
You'll notice that each term has $u^{-2/\sigma}$ common so they cancel. So when you simplify your equation you should get

$\left(\dfrac{du}{dx}\right)^2 = au^2 + bu + c$

for some $a, b$ and $c$. This is solvable.

What method is used to solve an ODE of this form?
 
  • #6
\(\DeclareMathOperator{\arcsec}{arcsec}\)
\(\DeclareMathOperator{\sech}{sech}\)

How can I get to the final result from (see work below)?

For the moment, let \(\mu\sigma^2 = a\), \(\frac{2\alpha\sigma^2}{\sigma + 2} = b\), and \(\frac{\gamma\sigma^2}{\sigma + 1} = c\).
Then our ODE becomes
\[
\int\frac{du}{\sqrt{au^2 - bu - c}} = \pm x.
\]
For expression inside the square root, we will need to complete the square, make the subtition \(s = u\sqrt{a} - \frac{b}{2\sqrt{a}}\), \(s = i\sec(t)\sqrt{\frac{-b^2 - 4ac}{4a}}\), and \(t = \arcsec\Big(\frac{-2iu\sqrt{a}}{\sqrt{-b^2 - 4ac}}\Big)\).
After completing the square, we will have obtained
\[
\frac{1}{\sqrt{\frac{-b^2 - 4ac}{4a} +
\Big(u\sqrt{a} - \frac{b}{2\sqrt{a}}\Big)^2}}.
\]
Using our \(s\) substitution, \(ds = \sqrt{a}du\) so the integral becomes
\[
\int\frac{ds}{\sqrt{\frac{-b^2 - 4ac}{4a} + s^2}} = \pm x\sqrt{a}.
\]
Using our final substitution for \(s\), we have \(ds = i\tan(t)\sec(t)\sqrt{\frac{-b^2 - 4ac}{4a}}dt\), and then using our \(t\) substitution, we now have
\begin{align*}
\int\sec(t)dt &= \pm x\sqrt{a}\\
\ln(\tan(t) + \sec(t)) &= \pm x\sqrt{a}\\
\tan(t) + \sec(t) &= \big\{e^{x\sqrt{a}}, e^{-x\sqrt{a}}\big\}\\
2\sqrt{a}\sqrt{au^2 - bu - c} + 2au - b &=
\big\{\cosh\big(x\sqrt{a}\big), \sinh\big(x\sqrt{a}\big)\big\}
\end{align*}
Then when I keep the \(\cosh\) term and solve for \(u\), I have
\[
u(x) = \frac{2b + \cosh(Dx) + (b^2 + 4ac)\sech(Dx)}{4a}
\]
I have not idea how to back sub in the definitions of \(a\), \(b\), and \(c\) to get the correct form of \(u\).
 
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  • #7
You can do what you did but try differentiating. In doing so we obtain

$2 u' u'' = (2 a u +b) u' $

giving $u ' = 0$ or $u'' = au + b/a$. I think the latter is easier to solve than your approach.
 
  • #8
Jester said:
You can do what you did but try differentiating. In doing so we obtain

$2 u' u'' = (2 a u +b) u' $

giving $u ' = 0$ or $u'' = au + b/a$. I think the latter is easier to solve then your approach.

This should be $u'' = au + b/2$, correct?

The solution to this ODE after making the substitution \(u^{-\sigma} = y\) is
\[
u(x) = \left(\frac{1}{\frac{b}{2a} + c_1\cosh(Dx)}\right)^{1/\sigma} = \left(\frac{1}{\frac{\alpha}{(\sigma + 2)\mu} + c_1\cosh(Dx)}\right)^{1/\sigma}
\]
as \(x\to\infty\), \(u\to 0\), and \(u'\to 0\).
\[
u'(x) = -\frac{c_1 D \sinh (D x) \left(\frac{1}{\frac{b}{2 a}+c \cosh (D x)}\right)^{\frac{1}{\sigma }+1}}{\sigma }
\]
I don't see a meaningful way to find \(c_1\). If I assume \(c_1 = 1\), then I can't produce the desired result either. So I think \(c_1\) isn't 1 since then I could factor out something to potential get \(A\) and \(B\).
 
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  • #9
I have determined that \(c_1 = \frac{1}{A} = \frac{\alpha}{(2 + \sigma)\mu B}\).
How do I get this value though?

I just worked through the problem to see what I needed for \(c_1\) without using the BC at infinity.
\[
u(x) = \left(\frac{A}{B + Ac_1\cosh(Dx)}\right)^{1/\sigma}
\]
 
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  • #10
Yes, that was a typo. It should be $b/2$. As for finding the constant. Go back to the original equation after the substitution, namely

$ y'^2 = \mu \sigma^2 y^2 - \dfrac{2 \alpha \sigma^2}{\sigma+2} y - \dfrac{ \gamma \sigma^2}{\sigma+1}$

and substitute your solution.
 
  • #11
Jester said:
Yes, that was a typo. It should be $b/2$. As for finding the constant. Go back to the original equation after the substitution, namely

$ y'^2 = \mu \sigma^2 y^2 - \dfrac{2 \alpha \sigma^2}{\sigma+2} y - \dfrac{ \gamma \sigma^2}{\sigma+1}$

and substitute your solution.

With \(y(x) = \frac{b}{2a} + c_1\cosh(Dx)\), I get
\[
\left\{c\to -\frac{i \sqrt{\alpha ^2 (\sigma +1)+\gamma \mu (\sigma +2)^2}}{\sqrt{\mu } \sqrt{\sigma +1} (\sigma +2) \sqrt{\mu \left(\mu \sigma ^2 \sinh ^2\left(\mu \sigma ^2 x\right)-\cosh ^2\left(\mu \sigma ^2 x\right)\right)}}\right\},\left\{c\to \frac{i \sqrt{\alpha ^2 (\sigma +1)+\gamma \mu (\sigma +2)^2}}{\sqrt{\mu } \sqrt{\sigma +1} (\sigma +2) \sqrt{\mu \left(\mu \sigma ^2 \sinh ^2\left(\mu \sigma ^2 x\right)-\cosh ^2\left(\mu \sigma ^2 x\right)\right)}}\right\}
\]
which isn't \(\frac{1}{A}\) and the solution is complex. I used Mathematica to solve for the coefficient so I doubt there is a mistake.
 
  • #12
First, is it $\dfrac{b}{2a}$ or $- \dfrac{b}{2a}$. It really makes a difference. Second, you can use the hyperbolic sinh-cosh identity. Try that.
 
  • #13
\(\DeclareMathOperator{\sgn}{sgn}\)
Jester said:
First, is it $\dfrac{b}{2a}$ or $- \dfrac{b}{2a}$. It really makes a difference. Second, you can use the hyperbolic sinh-cosh identity. Try that.

If I use \(-\frac{b}{2a}\) and simplify, I get:
\[
\text{c1}\to \pm\frac{\sqrt{\alpha ^2 (\sigma +1)-\gamma \mu (\sigma +2)^2}}{\sqrt{\mu ^2 (\sigma +1) (\sigma +2)^2}}
\]
When I do some algebra, I get
\[
\frac{\alpha\sqrt{1 - \frac{\gamma\mu(2 + \sigma)^2}{\alpha^2(1 + \sigma)}}}{\mu(2 + \sigma)}
\]
but \(\frac{1}{A}\) is
\[
\frac{\alpha\sqrt{1 + \frac{\gamma\mu(2 + \sigma)^2}{\alpha^2(1 + \sigma)}}}{\mu(2 + \sigma)\sgn(\alpha)}
\]
So I have a negative when I need a positive and how do I pick up the \(\sgn(\alpha)\)?

Since \(\alpha^2\) is being factor out through the radical, \(\alpha\) can be both + or - so that is where the \(\sgn(\alpha)\) is picked up, correct? However, I still have a negative issue in the radical.
 
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FAQ: How can I use variable transformation to obtain a solution for this ODE?

What is variable transformation?

Variable transformation is a statistical method used to change the scale or distribution of a variable in order to meet certain assumptions or improve the interpretability of the data. This can involve applying mathematical functions to the original variable or creating new variables based on the original one.

Why is variable transformation necessary?

Variable transformation is necessary in order to meet the assumptions of certain statistical tests or models. For example, if the data is not normally distributed, transforming the variable can make it more suitable for parametric tests. Additionally, variable transformation can help to reduce the impact of outliers and improve the interpretability of the data.

How do you choose which transformation to use?

The choice of transformation depends on the characteristics of the data and the purpose of the analysis. Common transformations include logarithmic, square root, and power transformations. It is important to assess the data before and after transformation to determine which one is most appropriate.

Can variable transformation be applied to categorical variables?

No, variable transformation is typically only applied to continuous variables. Categorical variables do not have a numerical scale and therefore cannot be transformed using mathematical functions. However, categorical variables can be converted into dummy variables or recoded into numerical categories in order to be used in certain models.

Are there any potential drawbacks to variable transformation?

Yes, there can be potential drawbacks to variable transformation. It can alter the interpretation of the data and make it more difficult to communicate results to a non-technical audience. It also requires careful consideration and expertise to choose the most appropriate transformation and to properly interpret the results after transformation.

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