# Skydiving - part 2¶

In part 1 we created a program to solve the equations of motion for skydiving. We began with Newton’s second law, and we looked at the forces acting on the jumper. This gave us a formula for the acceleration as a function of the velocity. Then we used the equations of motion that we know hold for constant acceleration to find the velocity at small steps forward in time.

In this part we will do the same for the position, and we will use a bungee jumper as an example. The only thing that differs between skydiving and bungee jumping is the formula for acceleration. Everything else is exactly the same. But because the forces acting on the bungee jumper is dependent on the position of the jumper, we have to solve for the position as well.

After this we will plot the g-forces for both the skydiver and the bungee jumper. Then we can compare skydiving and bungee jumping based on the g-forces experienced by the jumper. We will also look at how the parachute deploys and the effect it has on the g-forces.

In part 1, we began by finding the following expression for the acceleration of a skydiver:

Then we used the equations of motion for constant acceleration

to take short steps in time of length \(\Delta t\), which gave us

But there is a corresponding equation for constant acceleration which we can use to find the position:

We can use this to take short ‘steps in time’ in the same way as we did for the velocity:

## Bungee jump¶

Let us examine a bungee jumper and the forces acting on her. We can regard the elastic cord as similar to a stretched spring. But unlike a spring, the cord does not exert any force when it is compressed, only when it is stretched. When the jumper jumps from the top of a bridge, the cord is not stretched, and so it does not affect the jumper until she has fallen far enough for the cord to begin to stretch. This point, right before the elastic cord starts to stretch, is known as the point of equilibrium.

Now, let us create a reference that fits the problem we are examining. We place \(x=0\) at the point of equilibrium, and we decide that the cord is 20 meters long, so our jumper jumps from a point 20 meters above the the point of equilibrium, that is at \(x_0 = 20\)m. Let us add a river 60 meters below the bridge.

We can tell that if the jumper’s position is above the point of equilibrium, then the cord will not be stretched, and it will not act on the jumper with any force. And because we have placed the point of equilibrium at \(x=0\), the force exerted by the cord \(S\) equals \(0\) for \(x>0\).

If, instead, we have \(x<0\), we can see that the cord is stretched, and so it will pull the jumper upwards with a spring force. We can model this force with the help of a principle known as Hooke’s law. Hooke’s law states that the force from a spring that is stretched a length of \(x\) is given by:

where \(k\) is a constant dependent on the stiffness of the spring.

Now we can express the force from the cord as a function of the position \(x\)

In addition to \(S(x)\), the jumper experiences both gravity \(mg\), and air resistance \(Dv\). From Newtons 2nd law:

so then

if we solve this for the acceleration, we get a function dependent on both the velocity and position of the jumper.

This means that we have to solve for both velocity and position at the same time, like this

## The Code¶

- Import Pylab, we do not need anything else
- Declare all the parameters we need. Use \(m=60\), \(v_0=0\), \(x_0=20\), \(D=10\). You can just guess the value of \(k\), we will adjust it later.
- Define the ‘cord force’ \(S(x)\). You will need to use \(\verb+def+\) to define a function, and an \(\verb+if+\)-test inside the function to check if \(x\) is above or below zero.
- Define the acceleration as a function of both position and velocity. \(\verb+def a(x,v):+\).
- Define \(\Delta t = 0.01\) (
**Hint:**name the variable \(\verb+dt+\)), \(T=60\) and \(n=T/dt\) - Declare three arrays, one for the velocity \(v\) , one for the position \(x\) and one for the time \(t\). We want the arrays to be empty and have room for N+1 elements, so use the \(\verb+zeros+\) command.
- Set the first element in the x-array to \(x_0\), i.e. \(\verb+x[0] = x0+\).
- Create a \(\verb+for+\) loop that that iterates over \(n =0,1,2,..,N\)
(
**Hint:**use \(\verb+range+\)) - Inside the loop, calculate \(\verb!t[n+1]!\), \(\verb!v[n+1]!\) and \(\verb!x[n+1]!\). Use the following formulas

You should have something similar to

```
for n in range(N):
t[n+1] = t[n] + ...
v[n+1] = v[n] + ...
x[n+1] = x[n] + ...
```

10. Plot the result to see if everything is correct (**Hint:**
\(\verb!plot(t, x)!\)).

We encourage you to solve the exercises independently before you have a look at the solutions we have provided in “Bungee code”.

## Exercises¶

- Make the plot look nicer. Label the axes, etc.
- By examining the plot, try to adjust \(k\) to a value that makes the jumper barely touch the water. That is, the bottom of the curve reaches exactly \(-40\).
- Print out the maximum velocity experienced by the jumper.
**Hint:**\(\verb!max(v)!\). How does this compare to the skydivers maximum velocity?

## Point of equilibrium¶

Note that \(x=0\) is the equilibrium point for the cord when there is zero mass on it. If a person is hanging on the cord, the point of equilibrium shifts downwards. This new equilibrium point is the point where the force from gravity, pulling downwards, and the force from the elastic, pulling upwards, cancel each other out. After oscillating up and down for a while, this is the point where the jumper will end up hanging still.

## Exercises¶

- Calculate the new equilibrium point when there is a person of mass
\(m\) hanging from the cord equilibrium.
**Hint:**Use the same approach as we used to find the terminal velocity of the parachute jumper. - Find the equilibrium point by looking at the plot. Compare what you see with the calculation you did by hand.

## Plotting g-forces¶

The term ‘g-force’ is somewhat misleading because it is not really a
‘force’ you experience, but *acceleration*. When the human body is
accelerated, we feel it as weight pulling at us. Like when you are
sitting in a car that drives through a turn. You feel like you are
being pulled to the side. So these accelerations feel like forces
acting on the body, and that is why we call them ‘g-forces’.

The letter ‘g’ in ‘g-force’ stands for gravitation. This is because we compare the force we feel with the gravitational force. When you are standing perfectly still, you feel 1 g from gravity. During a roller coaster ride you will, as the ride progresses, experience a lot of different g-forces when you are accelerating up and down the hills, trough turns and possibly even through loops. You become weightless when there is a quick dive down from a peak in the roller coaster, that is, you experience 0 g or free-fall. An advantage with using g-forces is that they are independent from mass. This means that every person will feel the exact same g-forces during the same roller coaster ride.

To calculate the g-forces experienced by the jumper in both cases, we just need to add an additional array to the loop. For this array, we calculate the acceleration acting on the jumper, divide by \(g\) and add 1. Here is the code:

```
gforces = zeros(N+1)
...
for i in range(N):
t[i+1] = t[i] + ...
v[i+1] = v[i] + ...
x[i+1] = x[i] + ...
gforces[i] = a(x[i],v[i])/g + 1
```

## Exercise¶

Calculate and plot the g-forces that act on both the skydiver and the bungee jumper in your program. Compare the plots, are they different from each other? Try to explain why the two are different.

## Deploying the parachute¶

Finally the time has come to deploy our simulated parachute. As we mentioned previously, we only have to change the drag coefficient \(C\) to \(C_P = 1.8\) and the silhouette area \(A\) to \(A_P = 44\). Earlier we simulated the jump for \(T = 60\) seconds. Now we will increase the time to \(180\) seconds, but let the first loop still iterate only over the first \(60\) seconds. Then we change \(C\) and \(A\), and solve the remaining \(120\) seconds.

```
dt = 0.01
T = 180
n = int(T/dt)
# Simulating the first 60 seconds
for i in range(0, 60/dt):
t[i+1] = t[i] + dt
v[i+1] = v[i] + a(v[i])*dt
gforces[i] = 1 - a(v[i])/g
# Change C and A
C = C_p
A = A_p
# Simulating the last 120 seconds
for i in range(60/dt, 180/dt):
t[i+1] = t[i] + dt
v[i+1] = v[i] + a(v[i])*dt
gforces[i] = 1 - a(v[i])/g
```

Now, we can plot the velocity against time, and the g-forces. What do we see? One problem that has materialized is that the changes in the values of \(C\) and \(A\) happen too suddenly. It is as if the parachute deployed immediately, which would have slowed the jumper extremely fast, causing almost 100 g! Anything above 10g can be fatal, and an average person will start to faint above 5g. It does not look good for our poor parachute jumper!

This is why modern parachutes are made to deploy slower on purpose, so the velocity doesn’t decrease so suddenly. Let us attempt to simulate that the parachute takes 5 seconds to deploy completely, and see how it affects the g-forces. This time, we create three loops. One without the parachute, one where the parachute is in the process of deploying, and one after the parachute is completely deployed.

```
dt = 0.01
T = 180
n = int(T/dt)
# Simulating the first 60 seconds
for i in range(0, 60/dt):
t[i+1] = t[i] + dt
v[i+1] = v[i] + a(v[i])*dt
gforces[i] = 1 - a(v[i])/g
# Simulating the next 5 seconds
for i in range(60/dt, 65/dt):
C += (C_p-C)/(5/dt)
A += (A_p-A)/(5/dt)
t[i+1] = t[i] + dt
v[i+1] = v[i] + a(v[i])*dt
gforces[i] = 1 - a(v[i])/g
# Simulating the last 120 seconds
for i in range(65/dt, 180/dt):
t[i+1] = t[i] + dt
v[i+1] = v[i] + a(v[i])*dt
gforces[i] = 1 - a(v[i])/g
```

## Exercise¶

Update your plot to include deployment of the parachute. First, let the change from free fall to parachute happen immediately. What g-forces does the jumper experience? Change your code so that the deployment of the parachute takes 5 seconds. What are the g-forces now?