Presentations
Location
Schewel Hall Room 232
Access Type
Event
Event Website
http://www.lynchburg.edu/academics/red-letter-day/student-scholar-showcase/
Entry Number
109
Start Date
4-6-2016 3:45 PM
End Date
4-6-2016 4:00 PM
Abstract
For the past dozen years, our research group has been refining a physical model used to predict the winning time for each stage of the Tour de France. Our model is based upon a series of incline planes and incorporates real stage data and cyclist power output, as well as air and rolling resistances. We report on our most recent model modification in which we utilized allometric scaling to adjust our model cyclist’s power output based upon varied rider masses for different stage types. We also provide a comparison between our model and published power data for top level cyclists and recent Tour de France winners such as Chris Froome and Vincenzo Nibali. This juxtaposition showcases not only how well our model predicts stage-winning times, but also the extent to which our model matches reality. We finally report on how our model performed in predicting the winning time for each stage in the 2015 Tour de France.
Faculty Mentor(s)
Dr. John E. (Eric) Goff
Tour de France Modeling: 2015 Results and Comparisons with Elite Cyclist Power Data
Schewel Hall Room 232
For the past dozen years, our research group has been refining a physical model used to predict the winning time for each stage of the Tour de France. Our model is based upon a series of incline planes and incorporates real stage data and cyclist power output, as well as air and rolling resistances. We report on our most recent model modification in which we utilized allometric scaling to adjust our model cyclist’s power output based upon varied rider masses for different stage types. We also provide a comparison between our model and published power data for top level cyclists and recent Tour de France winners such as Chris Froome and Vincenzo Nibali. This juxtaposition showcases not only how well our model predicts stage-winning times, but also the extent to which our model matches reality. We finally report on how our model performed in predicting the winning time for each stage in the 2015 Tour de France.
https://digitalshowcase.lynchburg.edu/studentshowcase/2018/presentations/102