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Relation Between Flight Durations and Wingspans of Paper Airplanes
Transcript of Relation Between Flight Durations and Wingspans of Paper Airplanes
Independent = Wingspan Length (cm)
Dependent = Flight Distance Problem: How does the wingspan length affect the flight distance? By conducting this experiment, we opened a new door to the depths of further advances in the world of aerodynamics. Even though it was a simple and scaled version of a real plane, the experiment was a new insight on this topic. Hopefully, we can make a breakthrough someday using such experiments! Why did this interest my colleagues and I?
It's actually pretty simple: once the advances are made, we want the credit! :)
But on a more serious note, it is important to understand the basics to get a starting comprehension of real aircrafts, especially if one decides to pursue a career in such. If we increase the wingspan, then the plane will find a drastic increase in distance flown. Hypothesis: Throughout the process of the experiment, I kept asking myself, “why waste so much effort when I can just find an easier topic and research the results online instead?” The purpose of this whole task was to find out the linearity between two variables, not rip it off of the internet.
Exploring the relation between the two variables was obviously an important part, and was thus emphasized by my colleagues and me when we took up the trouble of creating multiple paper airplanes to replicate the dependence of flight distance on the wingspan.
The problem was, how does the wingspan length affect the flight distance?
Answer: As the wingspan length increases, so does the flight distance.
In the end, the correlation between the variables was quite strong (as stated earlier, 0.98) and definitely positive.
Since this experiment was done on a day with little to no fluctuation in the breeze/wind, our results were quite congruent to the final equation that would give us the approximate flight distance of a paper airplane due to its respective wingspan in slope-intercept form. Figure 1, the table, displays this, and for a more visual appearance, you can look at the graph, which has a somewhat linear body. Unfortunately, Had it been done on a day with different circumstances, the experiment’s outcome would have probably varied quite drastically.
However, my group has had one handicap through the process of analyzing the results: these results would not be able to be directly compared to a real life model of an airplane. As you probably already know, real airplanes are made of much stronger yet lightweight materials. Not all are in their purest forms, so it is common to find planes made of synthetic material. Since paper cannot even come close to being compared to such materials, it was next to impossible for my group to find a way to relate the scaled version to an actual version. BUT...
We cannot forget the fuel factor. Real airplanes are fueled, and do not only depend on the design or the amount of wind.
Overall, the trial was a success, and I can't see how we could have done any better.
Source of data: found through an experiment involving creating a series of paper airplanes that, obviously, varied in wingspan.
Data Points Used: 12
To analyze the data, we compared how the changed wingspans affected the distances, and more importantly, the correlation between the 2 variables. Also, thanks to the use of the internet, my group and I were able to research a little bit further to find how professional aeronautic officials dealt with other factors, such as replicated designs, wind, etc.
After reading a few sites, I decided these would be the best to use:
http://www.grc.nasa.gov/WWW/K-12/airplane/geom.html Conclsion Methods Just another data table I found to conclude/analyze: This is just a starting point, for I guarantee you, there will come a day when the breakthrough will be made! I guess linearity is in the air! THANKS! Results Figure 1 Figure 2 Reason of interest?
I <3 Paper Airplanes For graph:
Linear Regression Line: y = 17.7x + 208.4
Slope = 17.7. This represents the increase in wingspan per unit increase in the x axis, which happens to be wingspan.
Y-intercept = 208.4. This represents the base as to which each plane must fly, starting with a paper airplane with a wingspan of 8 cm. Had we made paper airplanes with smaller wingspans, the y-intercept would be significantly smaller, due to the fact that the base would continuously decrease as the wingspan decreased.
X-intercept: not of interest to us, because of the zero element, which explains that any number multiplied by 0 is 0. SO, 17.7*0 = 0
=> no evident wing
=> no flight.
Now what's a plane without flight?!