5.5 problem Problem 5

5.5.1 Solving as exact ode
5.5.2 Maple step by step solution

Internal problem ID [2717]
Internal file name [OUTPUT/2209_Sunday_June_05_2022_02_54_54_AM_50811869/index.tex]

Book: Differential equations and linear algebra, Stephen W. Goode and Scott A Annin. Fourth edition, 2015
Section: Chapter 1, First-Order Differential Equations. Section 1.9, Exact Differential Equations. page 91
Problem number: Problem 5.
ODE order: 1.
ODE degree: 1.

The type(s) of ODE detected by this program : "exact"

Maple gives the following as the ode type

[_separable]

\[ \boxed {2 y x +\left (x^{2}+1\right ) y^{\prime }=0} \]

5.5.1 Solving as exact ode

Entering Exact first order ODE solver. (Form one type)

To solve an ode of the form\begin {equation} M\left ( x,y\right ) +N\left ( x,y\right ) \frac {dy}{dx}=0\tag {A} \end {equation} We assume there exists a function \(\phi \left ( x,y\right ) =c\) where \(c\) is constant, that satisfies the ode. Taking derivative of \(\phi \) w.r.t. \(x\) gives\[ \frac {d}{dx}\phi \left ( x,y\right ) =0 \] Hence\begin {equation} \frac {\partial \phi }{\partial x}+\frac {\partial \phi }{\partial y}\frac {dy}{dx}=0\tag {B} \end {equation} Comparing (A,B) shows that\begin {align*} \frac {\partial \phi }{\partial x} & =M\\ \frac {\partial \phi }{\partial y} & =N \end {align*}

But since \(\frac {\partial ^{2}\phi }{\partial x\partial y}=\frac {\partial ^{2}\phi }{\partial y\partial x}\) then for the above to be valid, we require that\[ \frac {\partial M}{\partial y}=\frac {\partial N}{\partial x}\] If the above condition is satisfied, then the original ode is called exact. We still need to determine \(\phi \left ( x,y\right ) \) but at least we know now that we can do that since the condition \(\frac {\partial ^{2}\phi }{\partial x\partial y}=\frac {\partial ^{2}\phi }{\partial y\partial x}\) is satisfied. If this condition is not satisfied then this method will not work and we have to now look for an integrating factor to force this condition, which might or might not exist. The first step is to write the ODE in standard form to check for exactness, which is \[ M(x,y) \mathop {\mathrm {d}x}+ N(x,y) \mathop {\mathrm {d}y}=0 \tag {1A} \] Therefore \begin {align*} \left (-\frac {1}{2 y}\right )\mathop {\mathrm {d}y} &= \left (\frac {x}{x^{2}+1}\right )\mathop {\mathrm {d}x}\\ \left (-\frac {x}{x^{2}+1}\right )\mathop {\mathrm {d}x} + \left (-\frac {1}{2 y}\right )\mathop {\mathrm {d}y} &= 0 \tag {2A} \end {align*}

Comparing (1A) and (2A) shows that \begin {align*} M(x,y) &= -\frac {x}{x^{2}+1}\\ N(x,y) &= -\frac {1}{2 y} \end {align*}

The next step is to determine if the ODE is is exact or not. The ODE is exact when the following condition is satisfied \[ \frac {\partial M}{\partial y} = \frac {\partial N}{\partial x} \] Using result found above gives \begin {align*} \frac {\partial M}{\partial y} &= \frac {\partial }{\partial y} \left (-\frac {x}{x^{2}+1}\right )\\ &= 0 \end {align*}

And \begin {align*} \frac {\partial N}{\partial x} &= \frac {\partial }{\partial x} \left (-\frac {1}{2 y}\right )\\ &= 0 \end {align*}

Since \(\frac {\partial M}{\partial y}= \frac {\partial N}{\partial x}\), then the ODE is exact The following equations are now set up to solve for the function \(\phi \left (x,y\right )\) \begin {align*} \frac {\partial \phi }{\partial x } &= M\tag {1} \\ \frac {\partial \phi }{\partial y } &= N\tag {2} \end {align*}

Integrating (1) w.r.t. \(x\) gives \begin{align*} \int \frac {\partial \phi }{\partial x} \mathop {\mathrm {d}x} &= \int M\mathop {\mathrm {d}x} \\ \int \frac {\partial \phi }{\partial x} \mathop {\mathrm {d}x} &= \int -\frac {x}{x^{2}+1}\mathop {\mathrm {d}x} \\ \tag{3} \phi &= -\frac {\ln \left (x^{2}+1\right )}{2}+ f(y) \\ \end{align*} Where \(f(y)\) is used for the constant of integration since \(\phi \) is a function of both \(x\) and \(y\). Taking derivative of equation (3) w.r.t \(y\) gives \begin{equation} \tag{4} \frac {\partial \phi }{\partial y} = 0+f'(y) \end{equation} But equation (2) says that \(\frac {\partial \phi }{\partial y} = -\frac {1}{2 y}\). Therefore equation (4) becomes \begin{equation} \tag{5} -\frac {1}{2 y} = 0+f'(y) \end{equation} Solving equation (5) for \( f'(y)\) gives \[ f'(y) = -\frac {1}{2 y} \] Integrating the above w.r.t \(y\) gives \begin{align*} \int f'(y) \mathop {\mathrm {d}y} &= \int \left ( -\frac {1}{2 y}\right ) \mathop {\mathrm {d}y} \\ f(y) &= -\frac {\ln \left (y \right )}{2}+ c_{1} \\ \end{align*} Where \(c_{1}\) is constant of integration. Substituting result found above for \(f(y)\) into equation (3) gives \(\phi \) \[ \phi = -\frac {\ln \left (x^{2}+1\right )}{2}-\frac {\ln \left (y \right )}{2}+ c_{1} \] But since \(\phi \) itself is a constant function, then let \(\phi =c_{2}\) where \(c_{2}\) is new constant and combining \(c_{1}\) and \(c_{2}\) constants into new constant \(c_{1}\) gives the solution as \[ c_{1} = -\frac {\ln \left (x^{2}+1\right )}{2}-\frac {\ln \left (y \right )}{2} \] The solution becomes\[ y = \frac {{\mathrm e}^{-2 c_{1}}}{x^{2}+1} \]

Summary

The solution(s) found are the following \begin{align*} \tag{1} y &= \frac {{\mathrm e}^{-2 c_{1}}}{x^{2}+1} \\ \end{align*}

Figure 153: Slope field plot

Verification of solutions

\[ y = \frac {{\mathrm e}^{-2 c_{1}}}{x^{2}+1} \] Verified OK.

5.5.2 Maple step by step solution

\[ \begin {array}{lll} & {} & \textrm {Let's solve}\hspace {3pt} \\ {} & {} & 2 y x +\left (x^{2}+1\right ) y^{\prime }=0 \\ \bullet & {} & \textrm {Highest derivative means the order of the ODE is}\hspace {3pt} 1 \\ {} & {} & y^{\prime } \\ \bullet & {} & \textrm {Separate variables}\hspace {3pt} \\ {} & {} & \frac {y^{\prime }}{y}=-\frac {2 x}{x^{2}+1} \\ \bullet & {} & \textrm {Integrate both sides with respect to}\hspace {3pt} x \\ {} & {} & \int \frac {y^{\prime }}{y}d x =\int -\frac {2 x}{x^{2}+1}d x +c_{1} \\ \bullet & {} & \textrm {Evaluate integral}\hspace {3pt} \\ {} & {} & \ln \left (y\right )=-\ln \left (x^{2}+1\right )+c_{1} \\ \bullet & {} & \textrm {Solve for}\hspace {3pt} y \\ {} & {} & y=\frac {{\mathrm e}^{c_{1}}}{x^{2}+1} \end {array} \]

Maple trace

`Methods for first order ODEs: 
--- Trying classification methods --- 
trying a quadrature 
trying 1st order linear 
<- 1st order linear successful`
 

Solution by Maple

Time used: 0.0 (sec). Leaf size: 13

dsolve(2*x*y(x)+(x^2+1)*diff(y(x),x)=0,y(x), singsol=all)
 

\[ y \left (x \right ) = \frac {c_{1}}{x^{2}+1} \]

Solution by Mathematica

Time used: 0.028 (sec). Leaf size: 20

DSolve[2*x*y[x]+(x^2+1)*y'[x]==0,y[x],x,IncludeSingularSolutions -> True]
 

\begin{align*} y(x)\to \frac {c_1}{x^2+1} \\ y(x)\to 0 \\ \end{align*}