A multibody simulation study of alpine ski vibrations caused by random slope roughness

In alpine skiing an athlete's performance or injury mechanisms are strongly influenced by ski vibrations. Ski vibrations are mainly caused by irregularities of the ski-snow interaction (e.g. ripplets and disturbances of the slope, friction between ski and snow). With respect to the ski-snow interaction ski vibrations were not yet considered in computer simulation studies. During this study a planar multibody simulation model of a mono-skier has been developed to investigate transversal vibrations of unedged skis during schussing in the fall line over rough (random) ski slopes. The skis are modelled as dynamic Euler-Bernoulli beams and are incorporated as flexible beams into a multibody skier model. The interaction between skis and snow is modelled by a Kelvin-Voigt constitutive equation for the snow penetration force. The random ripplets and disturbances of the slope are described by random fields, which are generated based on real data obtained from measuring a public ski slope surface with a high resolution laser scanner. By the Monte Carlo simulation method a sequence of runs over random slope surfaces is performed and the ski vibrations of the ski shovel are analysed. The results show that the irregularities on a ski slope contribute considerably to the vibration of a ski and the performance of a skier. Thus, they have to be considered in multibody simulation models of alpine skiing. The developed simulation model will support the understanding of ski vibrations and their causes to improve the run time and to prevent injuries in alpine skiing. The presented simulation model can also be applied to find optimal material parameters to reduce ski vibrations during schussing. This work combines a flexible multibody simulation model and random fields. The implementation of random fields in multibody simulation models admits a more realistic investigation of the mechanical behaviour of complex systems due to random spatial uncertainties in input parameters. (C) 2019 Elsevier Ltd. All rights reserved.