| Reference : A Discrete Approach to Describe the Kinematics between Snow and a Tire Tread |
| Dissertations and theses : Doctoral thesis | |||
| Engineering, computing & technology : Materials science & engineering | |||
| http://hdl.handle.net/10993/18160 | |||
| A Discrete Approach to Describe the Kinematics between Snow and a Tire Tread | |
| English | |
Michael, Mark  [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >] | |
| 30-Jun-2014 | |
| University of Luxembourg, Luxembourg | |
| Docteur en Sciences de l'Ingénieur | |
| 228 | |
| Peters, Bernhard | |
| Fülöp, Tibor | |
| Nicot, Francios | |
| Van Baars, Stefan | |
| Džiugys, Algis | |
| Schneebeli, Martin | |
| [en] Tire Tread ; Snow ; Traction ; DEM - FEM Coupling ; Finite Element Method (FEM) ; eXtended Discrete Element Method (XDEM) ; Discrete Element Method (DEM) | |
| [en] The objective of this study is to develop a simulation technique that enables
to describe the interactions between snow and a moving surface. The develop- ments of this study are focused on the application of the interactions between a tire tread and a snow-covered road. Contrary to a continuum mechanics approach snow is considered to exist of discrete grains which are allowed to bond and collide with each other. There- fore, a discrete approach based on the extended Discrete Element Method is applied to the snow. Micro-mechanical models are developed to describe the deformational behaviour of snow. The micro-mechanical models describe the deformation and growth of the bonds between grains as well as the contact behaviour of snow grains on the grain-scale. Further, the age of a snow sample, the temperature and deformation rate applied are taken into account by the de- veloped models. The deformational behaviour of snow under brittle and ductile loading rates is validated with experimental data of common measurements in the field of snow mechanics. The simulation results successfully recapture the macro- and micro-scale deformation behaviour of snow and enable to identify the primary deformation mechanism in charge at the different loading rates, densities and temperatures. However, this approach allows treating individual snow grains during loading due to a rolling tire and predicting both position and orientation of grains. The micro-mechanical response of each snow grain in contact with the structure of the tire surface generates a global impact that defines the interaction forces be- tween the snow and the tire surface, which simultaneously indicate the strength of traction. In order to predict the elastic deformation of the tire surface the Finite Element Method is employed. A coupling method is developed between the discrete approach to characterise snow and the finite element description of the tire tread. The coupling method compensates quite naturally the shortages of both numerical methods. Further, a fast contact detection algorithm has been developed to spare valuable com- putation time. The coupling approach was successfully tested and validated with a small scale application but also with the large scale application of tire - soil interaction. The large-scale simulation results of tire - soil interactions showed to be accurate in comparison to similar traction measurements. Finally, the interaction of snow with rigid and deformable tread parts has been studied in accordance to friction measurements of the field of tire mechanics. The results show the ability of the simulation technique to describe the targeted interactions and give valuable insight into the underlying mechanisms. | |
| University of Luxembourg: High Performance Computing - ULHPC | |
| Fonds National de la Recherche - FnR | |
| Researchers ; Professionals | |
| http://hdl.handle.net/10993/18160 | |
| I would like to acknowledge that the presented research project is financed
by the National Research Fund of Luxembourg (FNR). Therefore, I am very thankful to the FNR for giving me the opportunity to conduct my research work independently. The successful developments of this project were undertaken at the University of Luxembourg. Therefore, I like to acknowledge my thankfulness to Prof. Bernhard Peters. This work is conducted in collaboration with the IRSTEA, the French National Research Institute of Science and Technology for Environment and Agriculture, and Goodyear Innovation Centre Luxembourg, the Innovation Center of one of the world largest tire manufacturer. I like to thank both institutes for the valuable support provided over the project period. In particular, I am thanking Prof. Francois Nicot and Dr. Tibor F ̈l ̈p for the successful engineering work uo conducted together over the span of this project. Further, I like to acknowledge the great work conducted together with the entire LuXDEM and Inutech Team of whom I like to thank Dr. Florian Hoffmann in particular. Simulations presented in this study were carried out using the High-Performance- Computing facility (HPC) of the University of Luxembourg, see Varrette et al. (2014), whose staff and administrators I hereby like to thank gratefully. Ac- cording to the UL HPC platform the simulations of this project used CPU hours of total 20 year and 300 days in 2013 only, which are a cost of 12854.42 Euro by the public EC2 computing environment of Amazon. |
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