The episode that will air next Wednesday, May 6th is called "Swimming in Syrup." I guess they got Cal Bear and Olympian Nathan Adrian to help out with the episode. Not much info available, but presumably they will test out how greatly increasing the viscosity of water affects swimming speed. I remember someone did a test like this a few years ago. If I recall correctly it was at the U of Minnesota. In that test they only made the water something like twice as thick and their results were that it did not affect swimming speed. Obviously there's more drag, but you also generate more propulsion because you have a thicker substance to apply force against.
edit: yeah, here's a story about the Minnesota experiment www.it.umn.edu/.../goingforthegoo.html
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This episode was aired on Thursday night in Taiwan. I got to see almost the entire programme, but unfortunately missed the part where they confirm or bust the myth.
Seeing as you guys haven't watched it yet, I won't spoil it for you, but I will be interested to hear your comments.
It did, however, get me thinking about how difficult it is to attribute an increase or a decrease in speed to any specific factor when a human is involved. It is not that we can just dial in the speed and execute the exact same stroke mechanics every time. Hardly anything we humans do can be repeated exactly the same again. There are just too many variables that could skew the results.
This episode was aired on Thursday night in Taiwan. I got to see almost the entire programme, but unfortunately missed the part where they confirm or bust the myth.
Seeing as you guys haven't watched it yet, I won't spoil it for you, but I will be interested to hear your comments.
It did, however, get me thinking about how difficult it is to attribute an increase or a decrease in speed to any specific factor when a human is involved. It is not that we can just dial in the speed and execute the exact same stroke mechanics every time. Hardly anything we humans do can be repeated exactly the same again. There are just too many variables that could skew the results.
