The recipe for the perfect snow

Published: 21 January 2019

The increased interest in snow production in the ski industry and the car and tire testing business has made researchers at Luleå University of Technology, wanting to start to classify snow varieties. To scientifically find explanations for why snow and manufactured snow have different properties or how a car tire responds to different winter roads, saves the environment and money.


–  We want to understand the mechanics behind the snow, Johan Casselgren, says, assistant professor of Experimental Mechanics at Luleå University of Technology and one of the leaders behind the University's Snow Academy, whose goal is to scientifically understand snow better.

Snow that looks like sugar

In the snow industry, "dead snow" is a known fact, while making artificial snow. Suddenly, the snow grains do not stick together. The same phenomenon has been experienced by companies that manufacture snow for car and tire testing activities. The snow becomes unusable, like sugar. When the snow gets older, the crystals become larger and rounder, which makes them more difficult to hold together. The question, these researchers ask themselves is how the phenomenon of sugar snow can be measured, so you do not have to test car tires or piste ski slopes, unnecessarily with snow that suddenly just does not work no more. The researchers at the Snow Academy also want to understand what measures can be implemented so that the snow lasts longer, in order to save the environment, time and money.

– Moisture acts as an adhesive for snow grains and snow crystals. When manufacturing snow, the amount of water, the pressure and the temperature are parameters that affect the snow, by being able to measure the snow produced and how it changes when it is used, we can find the recipe for the perfect snow for the ski resorts' slopes and be able to anticipate the winter road during, for example, car driving, Johan Casselgren, says.

A new instrument measuring snow

Researchers at Luleå University of Technology have now succeeded in developing a new instrument that, in just a few seconds, is able to appreciate both moisture and grain size in snow. The hope of the researchers is that the equipment will, in the near future, also be able to measure the density of the snow. Then the durability of the snow can be calculated. When the snow's density, moisture and grain size can be obtained, yes then it is also possible to produce a recipe collection for various snow types and purposes. It is the goal of Luleå researchers. Then it is easier to both manufacture the snow and to remove unwanted snow. The latter can be of great importance for winter road maintenance, removal of snow from sensors on autonomous cars and wind turbines.

– We have already started to document and systematize different types of snow in order to eventually make mechanical classification of snow. Perhaps not exactly as Linné did when it comes to plants, but at least a little like it, Johan Casselgren, says.

Gives a better picture of snow types

The measuring equipment used by the researchers consists of photodetectors that measure how the light from three light sources with different wavelengths is reflected from the snow surface. The measurement is based on being able to measure at several angles and for different wavelengths. The composition of the snow then determines how the different wavelengths are absorbed relative to each other and how the light is scattered in different directions. By being able to measure the reflections, snow can then be characterized. With this measuring instrument, the researchers want to create a better picture of different snow types, and how they occur. This knowledge should then be linked to the mechanical properties. The dome is a unique instrument considering the advantages such as mobility, data acquisition and accuracy. Further the dome is a viable option and focus on applications such as winter road and ski track maintenance. However, developing machine learning algorithms would definitely give research possibilities for more applications within snow research.

Johan Casselgren

Johan Casselgren, Associate Professor

Phone: +46 (0)920 491409
Organisation: Experimental Mechanics, Fluid and Experimental Mechanics, Department of Engineering Sciences and Mathematics

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