1.10 problem 10
Internal
problem
ID
[7974]
Book
:
First
order
enumerated
odes
Section
:
section
1
Problem
number
:
10
Date
solved
:
Monday, October 21, 2024 at 04:40:08 PM
CAS
classification
:
[_quadrature]
Solve
\begin{align*} y^{\prime }&=b y \end{align*}
1.10.1 Solved as first order quadrature ode
Time used: 0.128 (sec)
Integrating gives
\begin{align*} \int \frac {1}{b y}d y &= dx\\ \frac {\ln \left (y \right )}{b}&= x +c_1 \end{align*}
Singular solutions are found by solving
\begin{align*} b y&= 0 \end{align*}
for \(y\). This is because we had to divide by this in the above step. This gives the following
singular solution(s), which also have to satisfy the given ODE.
\begin{align*} y = 0 \end{align*}
Solving for \(y\) from the above solution(s) gives (after possible removing of solutions that do not
verify)
\begin{align*} y&=0\\ y&={\mathrm e}^{c_1 b +x b} \end{align*}
1.10.2 Solved as first order homogeneous class D2 ode
Time used: 0.112 (sec)
Applying change of variables \(y = u \left (x \right ) x\), then the ode becomes
\begin{align*} u^{\prime }\left (x \right ) x +u \left (x \right ) = b u \left (x \right ) x \end{align*}
Which is now solved The ode \(u^{\prime }\left (x \right ) = \frac {u \left (x \right ) \left (x b -1\right )}{x}\) is separable as it can be written as
\begin{align*} u^{\prime }\left (x \right )&= \frac {u \left (x \right ) \left (x b -1\right )}{x}\\ &= f(x) g(u) \end{align*}
Where
\begin{align*} f(x) &= \frac {x b -1}{x}\\ g(u) &= u \end{align*}
Integrating gives
\begin{align*} \int { \frac {1}{g(u)} \,du} &= \int { f(x) \,dx}\\ \int { \frac {1}{u}\,du} &= \int { \frac {x b -1}{x} \,dx}\\ \ln \left (u \left (x \right )\right )&=x b +\ln \left (\frac {1}{x}\right )+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 \(u=0\) for \(u \left (x \right )\) gives
\begin{align*} u \left (x \right )&=0 \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*} \ln \left (u \left (x \right )\right ) = x b +\ln \left (\frac {1}{x}\right )+c_1\\ u \left (x \right ) = 0 \end{align*}
Solving for \(u \left (x \right )\) from the above solution(s) gives (after possible removing of solutions that do not
verify)
\begin{align*} u \left (x \right )&=0\\ u \left (x \right )&=\frac {{\mathrm e}^{x b +c_1}}{x} \end{align*}
Converting \(u \left (x \right ) = 0\) back to \(y\) gives
\begin{align*} y = 0 \end{align*}
Converting \(u \left (x \right ) = \frac {{\mathrm e}^{x b +c_1}}{x}\) back to \(y\) gives
\begin{align*} y = {\mathrm e}^{x b +c_1} \end{align*}
1.10.3 Solved as first order Exact ode
Time used: 0.102 (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*} \mathop {\mathrm {d}y} &= \left (b y\right )\mathop {\mathrm {d}x}\\ \left (-b y\right ) \mathop {\mathrm {d}x} + \mathop {\mathrm {d}y} &= 0 \tag {2A} \end{align*}
Comparing (1A) and (2A) shows that
\begin{align*} M(x,y) &= -b y\\ N(x,y) &= 1 \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 (-b y\right )\\ &= -b \end{align*}
And
\begin{align*} \frac {\partial N}{\partial x} &= \frac {\partial }{\partial x} \left (1\right )\\ &= 0 \end{align*}
Since \(\frac {\partial M}{\partial y} \neq \frac {\partial N}{\partial x}\), then the ODE is not exact. Since the ODE is not exact, we will try to find an
integrating factor to make it exact. Let
\begin{align*} A &= \frac {1}{N} \left (\frac {\partial M}{\partial y} - \frac {\partial N}{\partial x} \right ) \\ &=1\left ( \left ( -b\right ) - \left (0 \right ) \right ) \\ &=-b \end{align*}
Since \(A\) does not depend on \(y\), then it can be used to find an integrating factor. The integrating
factor \(\mu \) is
\begin{align*} \mu &= e^{ \int A \mathop {\mathrm {d}x} } \\ &= e^{\int -b\mathop {\mathrm {d}x} } \end{align*}
The result of integrating gives
\begin{align*} \mu &= e^{-x b } \\ &= {\mathrm e}^{-x b} \end{align*}
\(M\) and \(N\) are multiplied by this integrating factor, giving new \(M\) and new \(N\) which are called \(\overline {M}\) and \(\overline {N}\)
for now so not to confuse them with the original \(M\) and \(N\).
\begin{align*} \overline {M} &=\mu M \\ &= {\mathrm e}^{-x b}\left (-b y\right ) \\ &= -b y \,{\mathrm e}^{-x b} \end{align*}
And
\begin{align*} \overline {N} &=\mu N \\ &= {\mathrm e}^{-x b}\left (1\right ) \\ &= {\mathrm e}^{-x b} \end{align*}
Now a modified ODE is ontained from the original ODE, which is exact and can be solved.
The modified ODE is
\begin{align*} \overline {M} + \overline {N} \frac { \mathop {\mathrm {d}y}}{\mathop {\mathrm {d}x}} &= 0 \\ \left (-b y \,{\mathrm e}^{-x b}\right ) + \left ({\mathrm e}^{-x b}\right ) \frac { \mathop {\mathrm {d}y}}{\mathop {\mathrm {d}x}} &= 0 \end{align*}
The following equations are now set up to solve for the function \(\phi \left (x,y\right )\)
\begin{align*} \frac {\partial \phi }{\partial x } &= \overline {M}\tag {1} \\ \frac {\partial \phi }{\partial y } &= \overline {N}\tag {2} \end{align*}
Integrating (2) w.r.t. \(y\) gives
\begin{align*}
\int \frac {\partial \phi }{\partial y} \mathop {\mathrm {d}y} &= \int \overline {N}\mathop {\mathrm {d}y} \\
\int \frac {\partial \phi }{\partial y} \mathop {\mathrm {d}y} &= \int {\mathrm e}^{-x b}\mathop {\mathrm {d}y} \\
\tag{3} \phi &= {\mathrm e}^{-x b} y+ f(x) \\
\end{align*}
Where \(f(x)\) 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 \(x\) gives
\begin{equation}
\tag{4} \frac {\partial \phi }{\partial x} = -b y \,{\mathrm e}^{-x b}+f'(x)
\end{equation}
But equation (1) says that \(\frac {\partial \phi }{\partial x} = -b y \,{\mathrm e}^{-x b}\).
Therefore equation (4) becomes
\begin{equation}
\tag{5} -b y \,{\mathrm e}^{-x b} = -b y \,{\mathrm e}^{-x b}+f'(x)
\end{equation}
Solving equation (5) for \( f'(x)\) gives
\[ f'(x) = 0 \]
Therefore
\[ f(x) = c_1 \]
Where \(c_1\) is
constant of integration. Substituting this result for \(f(x)\) into equation (3) gives \(\phi \)
\[
\phi = {\mathrm e}^{-x b} y+ c_1
\]
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
\[
c_1 = {\mathrm e}^{-x b} y
\]
Solving for \(y\) from the
above solution(s) gives (after possible removing of solutions that do not verify)
\begin{align*} y = c_1 \,{\mathrm e}^{x b} \end{align*}
1.10.4 Maple step by step solution
\[ \begin {array}{lll} & {} & \textrm {Let's solve}\hspace {3pt} \\ {} & {} & y^{\prime }=b y \\ \bullet & {} & \textrm {Highest derivative means the order of the ODE is}\hspace {3pt} 1 \\ {} & {} & y^{\prime } \\ \bullet & {} & \textrm {Solve for the highest derivative}\hspace {3pt} \\ {} & {} & y^{\prime }=b y \\ \bullet & {} & \textrm {Separate variables}\hspace {3pt} \\ {} & {} & \frac {y^{\prime }}{y}=b \\ \bullet & {} & \textrm {Integrate both sides with respect to}\hspace {3pt} x \\ {} & {} & \int \frac {y^{\prime }}{y}d x =\int b d x +\mathit {C1} \\ \bullet & {} & \textrm {Evaluate integral}\hspace {3pt} \\ {} & {} & \ln \left (y\right )=x b +\mathit {C1} \\ \bullet & {} & \textrm {Solve for}\hspace {3pt} y \\ {} & {} & y={\mathrm e}^{x b +\mathit {C1}} \end {array} \]
1.10.5 Maple trace
Methods for first order ODEs:
1.10.6 Maple dsolve solution
Solving time : 0.000
(sec)
Leaf size : 10
dsolve(diff(y(x),x) = b*y(x),
y(x),singsol=all)
\[
y = c_1 \,{\mathrm e}^{x b}
\]
1.10.7 Mathematica DSolve solution
Solving time : 0.024
(sec)
Leaf size : 18
DSolve[{D[y[x],x]==b*y[x],{}},
y[x],x,IncludeSingularSolutions->True]
\begin{align*}
y(x)\to c_1 e^{b x} \\
y(x)\to 0 \\
\end{align*}