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Vehicle-wet snow interaction: Testing,modeling and validation
Institution:1. College of Engineering, Nanjing Agricultural University, Nanjing 210031, China;2. Faculty of Agricultural Engineering, Sindh Agriculture University, Sindh 70050, Pakistan;1. U.S. Army Tank Automotive Research Development and Engineering Center, Warren, MI 48397-5000, USA;2. Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706-1572, USA;1. Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS 39762, USA;2. Dept. of Civil and Environmental Engineering and Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS 39762, USA;3. Terracon Consultants, Inc., Chattanooga, TN 37406, USA;4. U.S. Army Engineer Research and Development Center (ERDC), 3909 Halls Ferry Road, Vicksburg, MS 39180, USA;1. Department of Structural, Geotechnical and Building Engineering (DISEG), Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129, TORINO, Italy;2. Arctic Research Center, Hokkaido University, Kita-21 Nishi-11 Kita-ku, 001-0021, SAPPORO, Japan;1. Terramechanics, Multibody, and Vehicle Systems (TMVS) Laboratory, Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, United States;2. U. S. Army Engineer Research and Development Center, Vicksburg, MS 39180-6199, United States
Abstract:For a vehicle interacting with snow, whether dry or wet, uncertainties exist in the mechanical properties of snow, and in the interfacial properties between the tires of the vehicle and snow. For dry snow, these uncertainties have been studied recently using methods within a statistical framework employing a simple stochastic tire-snow interaction model and several validation metrics. Wet snow is more complicated and much less studied than dry snow, especially for tire-snow interaction. In this paper, the authors used a physical tire-snow interaction model and a similar statistical framework as was used to analyze dry snow, and presented results of calibration and validation of the interaction model for wet snow in conjunction with new test data based on a single test run with the assumption that it would provide needed sampling points for statistical analysis. Four local and global statistical validation metrics were used to assess the physical and statistical models with good results. Comparison between wet and dry snow, based on a single test run, shows that the former has a lower interfacial coefficient of friction, and a higher drawbar pull than the latter.
Keywords:Wet snow  Dry snow  Drucker–Prager  Drawbar pull  Torque  Validation metrics  Calibration  Stochastic  Uncertainties  Friction
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