Using Web 2.0 for OUTSIDE INnovation Patricia Seybold, Founder and CEO, Patricia Seybold Group STM - London December 7, 2007
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Semantic Indexing… Author Birth date Death date Birth Place Death Place Nationality Occupation Awards (38 fields) Theater District Location Capacity Style Etc… (18 fields) Company Name Productions Performers Etc… (14 fields) Production Director Theater Cast # of Perfs. Lighting Costumes Etc… (47 fields) Characters Plays Age Author Performer Etc… (30 fields) Scenes Where When Setting Subject Etc… (41 fields) Resources Play Director Theater Production Co. Character Scene Etc… (45 fields) Texts Keyword Author Date Written Date Published Production (67 fields) Give me scenes about AIDS written by South African authors in the past 5 years….
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WHAT IS THE TERMINAL VELOCITY OF A SNOWFLAKE? So as I am watching the snow fly horizontally outside my window, it occured to me that that if 1) I knew the terminal velocity of a snow flake 2) Measured the angle the snow's impact vector with the ground 3) and applied a little trig I could estimate the wind’s speed. So does anyone know the terminal velocity of a snow flake? Ben PS Add a vision system and I could automate the measurement.
Well you will have to watch out when you use vision pattern recognition...because as everyone knows, every snowflake is unique! although looking out my window at a field of now deep snow...I’m doubting that theory. However I would need a lot more free time before I headed outside to search for two identical snowflakes.... Ben the other way to estimate the wind speed is www.theweathernetwork.com As for your question, I would have to say the terminal velocity would be affected quite heavily by snow consistency and flake size. You might also have to compensate for noisy data, since snowflakes 'tumble' (which would mess with your vector). Furthermore since you are looking out of a building, your results would be effected by the updraft from the wind being deflected by the building. (Just a warning in case your results lead you to believe there is a hurricane in progress and you try to convince your coworkers to take cover).
A snowflake vision system would require LV-RT and not be a precise estimate of speed. The feeling of the snow coming to an abrupt stop against you face is a bit more accurate.. How fast your face freezes is another.. Or you could always get one of those turbine thingy that has a speed transducer on it. Your whirly-wind hat with an hall-effect sensor should do the trick! You know the diameter where the sensor is mounted, the rest is simple math. Use a graph to show wind bursts and velocity transitions! Jeff, you could present that project at the next LV User Group meeting!!
Ben wrote: 2) Measured the angle the snow's impact vector with the ground Remember that the wind speed is a 3D vector and you're only measuring the projection perpendicular to the view direction. Not to mention the "ground effects". You need to measure the angle away from any surfaces. You could measure the trajectories with two cameras pointing 90° apart and fit the 3D trajectories to a model function that you then can extrapolate to an infinite distance away from the ground. Maybe you should stick to some doppler radar setup.
After reading Ben’s post, I had to point out that he was really re-inventing Particle Image Velocimetry (PIV), which I used quite a bit in my Artificial Organs past. The snow already exists as a particle in the fluid of study This link support's Altenbach's requirement for a second camera. http:// darwin.bio.uci.edu/~edrucker/home/dpiv.htm Here is the kind of thing I had done, with hearts and arteries and so on: http:// www.ladhyx.polytechnique.fr/activities/bio_en.html Both of these images are 2D, but 3-D reconstruction is also done, it is just MUCH more processor intensive - No real time results as JoeLabView said! It gets really exciting when you have porous media (imagine the snow blowing through a tightly-packed cornfield...): http:// medschool.umaryland.edu/artificial_organs/pump_comp.asp -Mello
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Patricia Seybold CEO, Consultant, and Author [email_address] 617.912.3107 This work is licensed under a Creative Commons License. You may re-use any of these slides or the images on them as long as you attribute them to: 2007 - Patricia Seybold Group, www.psgroup.com Patricia Seybold Group Boston, MA 02129 617.742.5200 www.psgroup.com www.outsideinnovation.blogs.com