Fascinating stuff outta Sweden where researchers at Luleå University of Technology have developed a unique AI-based method to optimize the glide of cross-country skis under various conditions. Thanks to the researchers AI methods, skiers can now select their skis and grindings based on the prevailing snow and weather to optimize the contact zone and pressure against the snow based on the prevailing snow and weather conditions. Tip of the cap to Ph.D. Student of Ski Technology, Kalle Kalliorinne for this groundbreaking work. Cheers!

Here’s the press release from Luleå University of Technology:

“Combining the right ski, structure, and waxing method according to different weather conditions is crucial for the success of an elite skier. We have developed a method for calculating the glide and provide fast skis. Collaboration to implement the methods at the national team level is already underway,” says Kalle Kalliorinne, who recently defended his dissertation on the glide of cross-country skis in the field of Machine Elements, with a specialization in Sports Technology.

Friction plays a significant role in skiing, and everyone searching for the best solution to minimize it. At the elite level, even a very small reduction in the resistance between the ski and snow can considerably impact the race outcome. Selecting and preparing cross-country skis to minimize friction requires careful control of several details regarding the ski’s camber, base material, grinding texture, and waxing methods. These choices should be tailored to the prevailing snow and weather conditions to ensure optimal performance, for which minimal friction is essential.

To better understand the complex nature of ski-snow friction, the researchers have developed a multi-scale AI-based modeling method that couples the micro- and macroscopic properties of the ski. Field tests in the ski track show that the computational method works in practice, something that sparks interest within the skiing community. Using this method, the researchers have successfully determined and minimised the ski-snow friction at some typical weather conditions. The snow temperatures investigated are -3, -9, and -13 °C in groomed ski tracks without any precipitation.

At the macro scale, the researchers measured the entire geometry of the ski under varying loading conditions and developed AI that generates input data into a numerical model. Using the numerical model, the researchers can characterize the ski’s mechanical properties in terms of how it distributes the skier’s weight to the glide zones at the front and back of the ski. In the microscale model, the ski-base texture is analyized in contact with snow grains, which are several times stiffer than the more porous snow used in the macro-scale model.

It is the micro-scale calculations that provide the real contact area and the average distance between the ski and the snow, which are used to characterize the ski-base texture. The results are crucial for the development of a full-scale ski tribometer, which is a type of sled equipped with real skis as runners, that can be loaded in various ways to mimic the conditions skiers experience on the track.

Using this ski tribometer, one can calibrate the model and thereby appreciate the friction between the ski and the snow, hence determining the glide. During field measurements, the sled is accelerated on a downhill slope, and its velocity and position in all directions are precisely measured with an advanced and very accurate satellite-based positioning system, a so-called RTK-GNSS.

“Our research results assist in selecting combinations of the type of ski and ski-base texture that provide the best glide on competition skis for different weather conditions. These results are already being used in the development of new ski grinding textures in collaboration with the Swedish Olympic Committee”, says Kalle Kalliorinne.

The research was carried out in collaboration with The Swedish Olympic Committee, Svenska Skidskytteförbundet och Svenska skidförbundet längdskidor.

Journals with published sub-results: Proceedings of the Institution of Mechanical Engineers Part P, Journal of Sports Engineering and Technology, Lubricants.

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