In addition to eating the bulbs of the radishes, the leaves are also edible. I heartily endorse Clotilde Dusoulier’s Radish Leaf Pesto. The slight spiciness of the leaves gives it a delightful frisson.
Radish leaf pesto.
Pesto recipes are pretty flexible. I added some fresh cilantro from the garden, some frozen basil leaves, used ground almonds for the nut component, a bit of Manchego for the cheese, and doubled the garlic. I also added a little white wine to reduce the viscosity. I quite liked the end result — we had it on pasta — even if some others though it was a little too adventurous.
I punched a small hole (about 1mm radius) in a one gallon plastic bottle and had my students measure the rate at which water drained. Even though the apparatus and measurement technique was fairly rough, we were able to, with a little calculus, determine the equation for the height of the water in the bottle as a function of time.
Figure 1. A student uses a stopwatch to measure the outflow rate of water from the plastic bottle.
Introduction
Questions about water draining from a tank are a pretty common in calculus textbooks, but there is a significant difference between seeing the problem written down, and having to figure it out from a physical example. The latter is much more challenging because it does not presuppose any relationships for the change in the height of water with time; students must determine the relationship from the data they collect.
The experimental approach mimics the challenges faced by scientists such as Henry Darcy who first determined the formulas for groundwater flow (Darcy, 1733) almost 300 years ago, not long after the development of modern calculus by Newton and Leibniz (O’Conner and Robertson, 1996).
Procedure
Figure 2. The apparatus.
I punched a small hole, about 1mm in radius, in the base of a plastic, one-gallon bottle. I chose this particular type of bottle because the bulk of it was cylindrical in shape.
Students were instructed to figure out how the rate at which water flowed out (outflow rate) changed with time, and how the height of the water (h) in the bottle changed with time. These relationships would allow me to predict the outflow rate at any time, as well as how much water was left in the container at any time.
Data collection:
To measure height versus time, we marked the side of the bottle (within the cylindrical region) in one centimeter increments and recorded the time it took for the water level to drop from one mark to the next. There were a total of 11 marks.
To measure the outflow rate, we intercepted the outflow using a 25 ml beaker (not shown in Figure 2), and measured the time it took to fill to the 25 ml mark.
Results
Time elapsed since last measurement
Height of water in container
Time to fill 25ml beaker
Δt (s)
h (cm)
tf (s)
0.0
11
6.4
45.5
10
7.1
52.3
9
8.5
43.1
8
7.1
56.1
7
7.8
60.6
6
8.3
57.6
5
8.9
65.0
4
9.9
72.8
3
11.2
76.7
2
13.0
91.1
1
14.8
122.0
0
17.3
Table 1: Outflow rate, water height change with time.
To analyze the data, we calculated the total time (the cumulative sum of the elapsed time since the previous measurement) and the outflow rate. The outflow rate is the change in volume with time:
So our data table becomes:
Time
Height of water in container
Outflow rate
t (s)
h (cm)
dV/dt (ml/s)
0.0
11
3.91
45.5
10
3.52
97.8
9
2.94
140.9
8
3.52
197
7
3.21
257
6
3.01
315.1
5
2.81
380.1
4
2.53
452.9
3
2.23
529.6
2
1.92
620.7
1
1.69
742.7
0
1.45
Table 2. Height of water and outflow rate of the bottle.
The graph of the height of the water with time shows a curve, although it is difficult to determine precisely what type of curve. My students started by trying to fit a quadratic equation to it, which should work as we’ll see in a minute.
Figure 3. The decrease in height with time is not a straight line (is non-linear).
The plot of the outflow rate versus time, however, shows a pretty good linear trend. (Note that we do not use the first three datapoints (in Table 2), which we believe are erroneous because we were still sorting out the measuring method.)
Although I’ll note here that the data should ideally be modeled using a square root equation (Torricelli’s Law), that is beyond the present scope of the problem (we’ll try that tomorrow as a follow exercise).
Plotting the data in Excel we could add a linear trendline.
Figure 4. The outflow rate decreases linearly with time.
For the linear trendline, Excel gives the equation:
The y-axis is outflow rate (the change in volume with time), and the x axis is time (t), so the linear equation becomes:
Notice that this is a differential equation.
To determine the rate of at which the height of water in the container is changing, we need to recognize that the container is cylindrical in shape, and the volume (V) of a cylinder depends on its radius (r) and height (h):
which can be substituted into differential in the rate equation:
since π and the radius (r) are constants (since the jug’s shape is a cylinder), they can be pulled out of the differential:
Dividing through by πr2 solves for the rate of change of height:
Isolating the coefficients gives:
This equation should give the rate at which the height changes with time, however, if you look at it carefully you’ll realize that for the time range we’re using (less than 800 seconds) the value of dh/dt will always be positive. We correct this by recognizing that the outflow rate is a loss of water, so a positive outflow should result in a negative change in height, therefore we rewrite the equation as:
which gives:
Now comes the calculus
Now, we can use this rate equation to find the equation for height versus time by integrating with respect to time:
to get:
And all we have to do to the find the constant of integration is substitute in a known point, an initial value. As is often the case, the best point to use is the starting point where t=0 makes the rest of the calculations easier. In our case, when t=0, h=11:
so:
And our final equation becomes:
which is a quadratic equation as my students guessed before we did the calculus.
Does it work?
You will notice that in the math above, we never use the height data in determining equation for height versus time; all the calculations are based on the trendline for the outflow rate versus time.
As a result, we can compare the results of our equation to the actual measurements to see if our calculations are even close. Remarkably, they are.
Figure 5. The results from our equation (modeled) match the measured heights so well, the data points are difficult to distinguish on the graph.
Discussion
Despite all the potential for error, particularly, our relatively crude measurement techniques, and the imperfect cylindrical shape of our plastic bottle, the experiment went remarkably well.
Students found it quite challenging, and required some assistance even though this is a problem they have seen before in their textbook.
The problems in the textbook use Torricelli’s Law, which should much better describe the draining of a tank than the linear equation we find for dV/dt.
Torricelli’s Law:
where a is the area of the outlet hole, and g is the acceleration due to gravity.
In our actual experiment it is difficult to tell that a square root function would work better. Excel does not have an option for matching a square root function, so the calculations would become more involved (although it could be set up using Excel’s iterative solver or Goal Seek function).
Conclusion
Our experiment to use calculus to determine the rate of change of the height of water in a leaking plastic water bottle was a successful exercise even though the roughness of the data collection did not permit identification of the square root law for leakage.
Knap-weed or matfelon and cornflower or bluebottle, by Richard Waller (1689) from The Royal Society's Picture Library.
The Royal Society’s Picture Library is now available online. It contains images from some of the seminal scientific works of the last four centuries. It’s an excellent resource for teachers and students, who, with registration, can get free high-resolution images for presentations and unpublished theses.
I’m particularly attracted to the biological drawings at the moment because I’m trying to get students to practice their scientific drawing and diagramming.
Dr. Klaus Schmitt has some utterly amazing photographs that simulate what bees and butterflies can see. They can see ultra-violet wavelengths of light, which we can’t.
Schmitt maps the ultra-violet in the image to blue to make it visible to our eyes.
Monet's two versions of "The House Seen from the Rose Garden" show the same scene as seen through his left (normal) and right eyes.
The eye’s lens is pretty good at blocking ultra-violet light, so when Claude Monet (whose works we visited earlier this year) had the lens of his eye removed he could see a little into the ultra-violet wavelengths of light.
The images taken by the Hubble Space Telescope are in black and white, but each image only captures a certain wavelength (color) of light.
The Guardian has an excellent video that explains how the images from the Hubble Space Telescope are created.
Each image from most research telescopes only capture certain, specific colors (wavelengths of light). One camera might only capture red light, another blue, and another green. These are captured in black and white, with black indicating no light and white the full intensity of light at that wavelength. Since red, blue and green are the primary colors, they can be mixed to compose the spectacular images of stars, galaxies, and the universe that NASA puts out every day.
Three galaxies. This image is a computer composite that combines the different individual colors taken by the telescope's cameras. Image from the Hubble Space Telescope via NASA.
The process looks something like this:
How images are assembled. Note that the original images don't have to be red, blue and green. They're often other wavelengths of light, like ultra-violet and infra-red, that are not visible to the eye but are common in space. So the images that you see from NASA are not necessarily what these things would look like if you could see them with the naked eye.
Composition of the atmosphere from the formation of the Earth. Image ᔥJoel Cayford ↬Ethan Siegal
Joel Cayford has posted a nice image showing the composition of the atmosphere over time — since the formation of the Earth.
Note that, although the Earth is 4.5 billion years old, and life has been around for over 4 billion years, there has only been oxygen in the atmosphere for about 2 billion years.
Oxygen is an extremely reactive gas, which is why we use it when we “burn” carbohydrates for energy. But it also means that any free oxygen added to the atmosphere would easily react with rocks, water, and other gasses in the atmosphere, so would not be available in the quantities needed for air breathing organisms until it slowly accumulated.
Also, you need a lot of oxygen in the atmosphere to produce enough ozone to form the ozone layer that protects life at the surface from high-energy, cancer-inducing, ultra-violet radiation from the Sun.
