期刊
JOURNAL OF TERRAMECHANICS
卷 55, 期 -, 页码 1-16出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jterra.2014.05.002
关键词
Snow; Drawbar pull; Traction; Slip angle; Validation metrics; Calibration; Bayesian; Metamodel; Stochastic; Gaussian process
资金
- U.S. Army TACOM Life Cycle Command through Mississippi State University [W56HZV-08-C-0236]
- HPC resources from the Arctic Region Supercomputing Center
General operations of a vehicle involve simultaneous slip in the longitudinal and lateral directions, the combination of which is much more complicated than purely longitudinal or lateral motions. During vehicle snow interactions, additional complexities arise due to uncertainties of snow material properties and of interfacial properties between the tire and snow, calling for the stochastic modeling of the interactions to validate the model. For validation, a statistical framework was formed with several components: a deterministic, physically-based tire snow interaction model, a stochastic metamodel based on the physical model, a statistical model for calibration, prediction using the models, validation metrics, and new test data using an instrumented vehicle. The longitudinal and lateral drawbar pulls, and the torque and overturning moment, were used simultaneously to calibrate model parameters for a front and a rear tire. Four local and global validation metrics and extensive summary statistics were used to assess the quality of the models, with good results. (C) 2014 ISTVS. Published by Elsevier Ltd. All rights reserved.
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