2.1.13 problem 13
Internal
problem
ID
[8673]
Book
:
First
order
enumerated
odes
Section
:
section
1
Problem
number
:
13
Date
solved
:
Tuesday, December 17, 2024 at 12:57:25 PM
CAS
classification
:
[_quadrature]
Solve
\begin{align*} c y^{\prime }&=a \end{align*}
Solved as first order quadrature ode
Time used: 0.038 (sec)
Since the ode has the form \(y^{\prime }=f(x)\), then we only need to integrate \(f(x)\).
\begin{align*} \int {dy} &= \int {\frac {a}{c}\, dx}\\ y &= \frac {a x}{c} + c_1 \end{align*}
Summary of solutions found
\begin{align*}
y &= \frac {a x}{c}+c_1 \\
\end{align*}
Solved as first order homogeneous class D2 ode
Time used: 0.174 (sec)
Applying change of variables \(y = u \left (x \right ) x\), then the ode becomes
\begin{align*} c \left (u^{\prime }\left (x \right ) x +u \left (x \right )\right ) = a \end{align*}
Which is now solved The ode \(u^{\prime }\left (x \right ) = -\frac {c u \left (x \right )-a}{c x}\) is separable as it can be written as
\begin{align*} u^{\prime }\left (x \right )&= -\frac {c u \left (x \right )-a}{c x}\\ &= f(x) g(u) \end{align*}
Where
\begin{align*} f(x) &= -\frac {1}{x c}\\ g(u) &= c u -a \end{align*}
Integrating gives
\begin{align*} \int { \frac {1}{g(u)} \,du} &= \int { f(x) \,dx}\\ \int { \frac {1}{c u -a}\,du} &= \int { -\frac {1}{x c} \,dx}\\ \frac {\ln \left (-c u \left (x \right )+a \right )}{c}&=\frac {\ln \left (\frac {1}{x}\right )}{c}+c_1 \end{align*}
We now need to find the singular solutions, these are found by finding for what values \(g(u)\) is
zero, since we had to divide by this above. Solving \(g(u)=0\) or \(c u -a=0\) for \(u \left (x \right )\) gives
\begin{align*} u \left (x \right )&=\frac {a}{c} \end{align*}
Now we go over each such singular solution and check if it verifies the ode itself and
any initial conditions given. If it does not then the singular solution will not be
used.
Therefore the solutions found are
\begin{align*} \frac {\ln \left (-c u \left (x \right )+a \right )}{c} = \frac {\ln \left (\frac {1}{x}\right )}{c}+c_1\\ u \left (x \right ) = \frac {a}{c} \end{align*}
Solving for \(u \left (x \right )\) gives
\begin{align*}
u \left (x \right ) &= \frac {a}{c} \\
u \left (x \right ) &= \frac {\left ({\mathrm e}^{-c_1 c} a x -1\right ) {\mathrm e}^{c_1 c}}{c x} \\
\end{align*}
Converting \(u \left (x \right ) = \frac {a}{c}\) back to \(y\) gives
\begin{align*} y = \frac {a x}{c} \end{align*}
Converting \(u \left (x \right ) = \frac {\left ({\mathrm e}^{-c_1 c} a x -1\right ) {\mathrm e}^{c_1 c}}{c x}\) back to \(y\) gives
\begin{align*} y = \frac {\left ({\mathrm e}^{-c_1 c} a x -1\right ) {\mathrm e}^{c_1 c}}{c} \end{align*}
Summary of solutions found
\begin{align*}
y &= \frac {a x}{c} \\
y &= \frac {\left ({\mathrm e}^{-c_1 c} a x -1\right ) {\mathrm e}^{c_1 c}}{c} \\
\end{align*}
Solved as first order Exact ode
Time used: 0.066 (sec)
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 (c\right )\mathop {\mathrm {d}y} &= \left (a\right )\mathop {\mathrm {d}x}\\ \left (-a\right )\mathop {\mathrm {d}x} + \left (c\right )\mathop {\mathrm {d}y} &= 0 \tag {2A} \end{align*}
Comparing (1A) and (2A) shows that
\begin{align*} M(x,y) &= -a\\ N(x,y) &= c \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 (-a\right )\\ &= 0 \end{align*}
And
\begin{align*} \frac {\partial N}{\partial x} &= \frac {\partial }{\partial x} \left (c\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 -a\mathop {\mathrm {d}x} \\
\tag{3} \phi &= -a x+ 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 \(\frac {\partial \phi }{\partial y} = c\).
Therefore equation (4) becomes
\begin{equation}
\tag{5} c = 0+f'(y)
\end{equation}
Solving equation (5) for \( f'(y)\) gives
\[
f'(y) = c
\]
Integrating the above w.r.t \(y\)
gives
\begin{align*}
\int f'(y) \mathop {\mathrm {d}y} &= \int \left ( c\right ) \mathop {\mathrm {d}y} \\
f(y) &= c y+ c_1 \\
\end{align*}
Where \(c_1\) is constant of integration. Substituting result found above for \(f(y)\) into equation
(3) gives \(\phi \)
\[
\phi = -a x +c y+ c_1
\]
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 the constant \(c_1\) gives the solution as
\[
c_1 = -a x +c y
\]
Solving for \(y\) gives
\begin{align*}
y &= \frac {a x +c_1}{c} \\
\end{align*}
Summary of solutions found
\begin{align*}
y &= \frac {a x +c_1}{c} \\
\end{align*}
Maple step by step solution
\[ \begin {array}{lll} & {} & \textrm {Let's solve}\hspace {3pt} \\ {} & {} & c \left (\frac {d}{d x}y \left (x \right )\right )=a \\ \bullet & {} & \textrm {Highest derivative means the order of the ODE is}\hspace {3pt} 1 \\ {} & {} & \frac {d}{d x}y \left (x \right ) \\ \bullet & {} & \textrm {Separate variables}\hspace {3pt} \\ {} & {} & \frac {d}{d x}y \left (x \right )=\frac {a}{c} \\ \bullet & {} & \textrm {Integrate both sides with respect to}\hspace {3pt} x \\ {} & {} & \int \left (\frac {d}{d x}y \left (x \right )\right )d x =\int \frac {a}{c}d x +\mathit {C1} \\ \bullet & {} & \textrm {Evaluate integral}\hspace {3pt} \\ {} & {} & y \left (x \right )=\frac {a x}{c}+\mathit {C1} \\ \bullet & {} & \textrm {Solve for}\hspace {3pt} y \left (x \right ) \\ {} & {} & y \left (x \right )=\frac {\mathit {C1} c +x a}{c} \end {array} \]
Maple trace
`Methods for first order ODEs:
--- Trying classification methods ---
trying a quadrature
trying 1st order linear
<- 1st order linear successful`
Maple dsolve solution
Solving time : 0.001
(sec)
Leaf size : 12
dsolve(c*diff(y(x),x) = a,
y(x),singsol=all)
\[
y = \frac {a x}{c}+c_{1}
\]
Mathematica DSolve solution
Solving time : 0.002
(sec)
Leaf size : 14
DSolve[{c*D[y[x],x]==a,{}},
y[x],x,IncludeSingularSolutions->True]
\[
y(x)\to \frac {a x}{c}+c_1
\]