Simulation of Load–Sinkage Relationship and Parameter Inversion of Snow Based on Coupled Eulerian–Lagrangian Method

The accurate calibration of snow parameters is necessary to establish an accurate simulation model of snow, which is generally used to study tire–snow interaction. In this paper, an innovative parameter inversion method based on in situ test results is proposed to calibrate the snow parameters, which avoids the damage to the mechanical properties of snow when making test samples using traditional test methods. A coupled Eulerian–Lagrangian (CEL) model of plate loading in snow was established; the sensitivity of snow parameters to the macroscopic load–sinkage relationship was studied; a plate-loading experiment was carried out; and the parameters of snow at the experimental site were inverted. The parameter inversion results from the snow model were verified by the experimental test results of different snow depths and different plate sizes. The results show the following: (1) The material cohesive, angle of friction, and hardening law of snow have great influence on the load–sinkage relationship of snow, the elastic modulus has a great influence on the unloading/reloading stiffness of snow, and the influence of density and Poisson’s ratio on the load–sinkage relationship can be ignored. (2) The correlation coefficient between the inversion result and the matching test data is 0.979, which is 0.304 higher than that of the initial inversion curve. (3) The load–sinkage relationship of snow with different snow depths and plate diameters was simulated by using the model parameter of inversion, and the results were compared with the experimental results. The minimum correlation coefficient was 0.87, indicating that the snow parameter inversion method in this paper can calibrate the snow parameters of the test site accurately.