We know \( y = 5e^{x^4} \) so \( \frac{dy}{dx} = 20x^3e^{x^4} = 20x^3y \). (Chain rule used)
a) If \( P=ce^{\frac{t}{2}} \), then \( \frac{dP}{dt} = \frac{c}{2}e^{\frac{t}{2}} = \frac{P}{2} \).
b) The population of alligators cannot be negative.
c) We know when \( t=0 \), \( P=5 \), so plugging into the equation in (a), we find \( c=5 \).
a) \( y = \int 6x^2 \, dx = 2x^3 + C \)
b) \( y = \int \frac{1}{2x+6} \, dx = \frac{1}{2}\ln{(2x+6)} + C \)
c) \( y = \int \frac{p}{\sqrt{36-p^2}} \, dp \)
We can do a u-substitution here, letting \( u = 36-p^2 \), so \( \frac{du}{dp}=-2p \), and substituting these in:
\begin{align*} y &= \int -\frac{1}{2}\frac{1}{\sqrt{u}} \, du\\ y &= -\frac{1}{2}\left(2\sqrt{u} + C\right)\\ y &= -\sqrt{36-p^2}+C \end{align*}
d) This is a separable differential equation:
\begin{align*} \frac{dy}{y-1} &= \frac{dx}{x+5} \\ \int \frac{dy}{y-1} &= \int \frac{dx}{x+5} \\ \ln{|y-1|} &= \ln{|x+5|} + C\\ \ln{|y-1|} - \ln{|x+5|} &= C \\ \ln{\left|\frac{y-1}{x+5}\right|} &= C \\ \frac{y-1}{x+5} &= e^C \\ y &= e^C(x+5) + 1 \end{align*}
Note: It is common practice to replace \( e^C \) with another constant, \( A \), for aesthetics.
We are told \( \frac{dA}{dt} = k\sqrt[3]{A} \). From here, we can solve the differential equation to get the desired function:
\begin{align*} \frac{1}{\sqrt[3]{A}} dA &= k \, dt \\ \int \frac{dA}{\sqrt[3]{A}} &= \int k \, dt \\ \frac{3}{2} \sqrt[3]{A^2} &= kt + C \end{align*}
We were told that when \( t=0 \), the area was \( 2\sqrt{2} \):
\begin{align*} \frac{3}{2} \sqrt[3]{(2\sqrt{2})^2} &= k(0) + C \\ C &= 3 \end{align*}
When \( t=4 \), we know the area doubled, so it became \( 4\sqrt{2} \):
\begin{align*} \frac{3}{2} \sqrt[3]{(4\sqrt{2})^2} &= k(4) + 3 \\ k &= \frac{-3 + 3\sqrt[3]{4}}{4} \end{align*}
So finally:
\begin{align*} \frac{3}{2} \sqrt[3]{A^2} &= \left(\frac{-3 + 3\sqrt[3]{4}}{4}\right)t + 3 \\ \frac{1}{2} \sqrt[3]{A^2} &= \left(\frac{-1 + 1\sqrt[3]{4}}{4}\right)t + 1 \\ A(t) &= \sqrt{\left( \left(\frac{-1 + 1\sqrt[3]{4}}{2}\right)t + 2 \right)^3} \end{align*}
The easiest way to solve this is by creating a table:
\[ x_{n+1} = x_n + 0.25 \]
\[ y_{n+1} = y_n + 0.25(\frac{x_n^2+y_n^2}{2x_n^2}) \]
n | \(x_n\) | \(y_n\) |
---|---|---|
0 | 1 | 0 |
1 | 1.25 | 0.125 |
2 | 1.50 | 0.251 |
3 | 1.75 | 0.379 |
4 | 2 | 0.641 |
\[ Error = \frac{Actual\:value - Expected\:value}{Expected\:value}\cdot 100 = \frac{0.641-0.515}{0.515} \cdot 100 = 24.5\% \]
a) (i) When \( t=0 \), we have: \(\left(\begin{array}{c} x \\ y \end{array}\right) = \left(\begin{array}{c} 1 \\ 1 \end{array}\right)\) , therefore: \(\mathbf{\dot{x}} = \left(\begin{array}{c} 2 \\ 2 \end{array}\right)\) .
a) (ii) The general solution to a system of this form is: \(\mathbf{x} = Ae^{2t}\left(\begin{array}{c} 1 \\ 1 \end{array}\right) + Be^{3t}\left(\begin{array}{c} 1 \\ 2 \end{array}\right)\) . We know that when \( t=0 \), \( \mathbf{x} = \left(\begin{array}{c} 1 \\ 1 \end{array}\right) \), thus: \(\left(\begin{array}{c} 1 \\ 1 \end{array}\right) = A\left(\begin{array}{c} 1 \\ 1 \end{array}\right) + B\left(\begin{array}{c} 1 \\ 2 \end{array}\right)\) .
Therefore, we can write: \(\left(\begin{array}{c} 1 \\ 1 \end{array}\right) = \left(\begin{array}{cc} 1 & 1\\ 1 & 2 \end{array}\right) \left(\begin{array}{c} A \\ B \end{array}\right)\) .
Solving for \( \left(\begin{array}{c} A \\ B \end{array}\right) \) \( = \left(\begin{array}{cc} 1 & 1\\ 1 & 2 \end{array}\right)^{-1} \left(\begin{array}{c} 1 \\ 1 \end{array}\right) = \left(\begin{array}{c} 1 \\ 0 \end{array}\right)\) , so the particular solution is: \(\mathbf{x} = e^{2t}\left(\begin{array}{c} 1 \\ 1 \end{array}\right)\) .
b) The system will asymptotically approach the line: \(k\left(\begin{array}{c} 1 \\ 1 \end{array}\right)\) , as that is the only term in the particular solution.
a) If we let \( y = \frac{dx}{dt} \), then we have: \( \frac{dy}{dt} = \frac{d^2x}{dt^2} \). Thus, the system can be expressed as: \[ \begin{cases} \frac{dx}{dt} = y \\ \frac{dy}{dt} = -\frac{1}{25}y \end{cases} \]
b) We can solve the second equation as follows: \begin{align*} \frac{dy}{dt} &= -\frac{1}{25}y \\ \frac{1}{y}dy &= -\frac{1}{25}dt \\ \int \frac{1}{y}dy &= \int -\frac{1}{25}dt \\ \ln{|y|} &= -\frac{1}{25}t + C\\ y(t) &= e^C \cdot e^{-\frac{1}{25}t} = A \cdot e^{-\frac{1}{25}t} \end{align*}
c) Now we substitute \( y \) back into the equation for \( x \): \begin{align*} \frac{dx}{dt} &= y = A \cdot e^{-\frac{1}{25}t} \\ x(t) &= -25A \cdot e^{-\frac{1}{25}t} + C \end{align*}
a) If we set \( y = \frac{dx}{dt} \), then we have: \( \frac{dy}{dt} = \frac{d^2x}{dt^2} \). Thus, the system can be expressed as: \[ \begin{cases} \frac{dx}{dt} = y \\ \frac{dy}{dt} = 9.8 - 0.5y^2 \end{cases} \]
b) At the start, the ball is stationary. Given the initial conditions \( t_0=0 \), \( x_0=0 \), \( y_0=0 \), we need to make 5 steps over 2 seconds, so each step will be: \( h = 0.4 \) seconds. The updates for \( t \), \( x \), and \( y \) are given by: \begin{align*} t_i &= t_{i-1} + 0.4 \\ x_i &= x_{i-1} + 0.4y_{i-1} \\ y_i &= y_{i-1} + 0.4(9.8 - 0.5y_{i-1}^2) \end{align*} The computed values are shown in the table below:
n | \( t_n \) | \( x_n \) | \( y_n \) |
---|---|---|---|
0 | 0 | 0 | 0 |
1 | 0.4 | 0 | 3.924 |
2 | 0.8 | 1.568 | 4.766 |
3 | 1.2 | 3.474 | 4.144 |
4 | 1.6 | 5.131 | 4.630 |
5 | 2 | 6.983 | 4.262 |
From this table, we can see that \( x_5 = 6.983 \), meaning in the first 5 seconds, it fell approximately 6.983 meters.
c) To find the terminal velocity, we look for the value \( y_n \) approaches as \( n \) goes to infinity. Continuing our table from part (b):
n | \(t_n\) | \(x_n\) | \(y_n\) |
---|---|---|---|
0 | 0 | 0 | 0 |
1 | 0.4 | 0.00 | 3.92 |
2 | 0.8 | 0.16 | 4.77 |
3 | 1.2 | 0.48 | 4.14 |
4 | 1.6 | 0.96 | 4.63 |
5 | 2 | 1.60 | 4.26 |
6 | 2.4 | 2.40 | 4.55 |
7 | 2.8 | 3.36 | 4.33 |
8 | 3.2 | 4.48 | 4.50 |
9 | 3.6 | 5.76 | 4.37 |
10 | 4 | 7.20 | 4.47 |
11 | 4.4 | 8.80 | 4.39 |
12 | 4.8 | 10.56 | 4.45 |
13 | 5.2 | 12.48 | 4.41 |
14 | 5.6 | 14.56 | 4.44 |
15 | 6 | 16.80 | 4.42 |
16 | 6.4 | 19.20 | 4.44 |
17 | 6.8 | 21.76 | 4.42 |
18 | 7.2 | 24.48 | 4.43 |
19 | 7.6 | 27.36 | 4.42 |
20 | 8 | 30.4 | 4.43 |
We can see \( y_n \) is approaching 4.43, hence that is our terminal speed.
d) When we reach the terminal speed, the acceleration of the ball becomes 0. Meaning, \( \frac{d^2x}{dt^2} = 0 \), and so,
\[ 0 = 9.81 - 0.5\left(\frac{dx}{dt}\right)^2 \]
\[ \frac{dx}{dt} = \sqrt{\frac{9.8}{0.5}} \approx 4.427\]
This is very close to the solution in part (c).