Drag force modeling with induced surface deformation in granular media

Abstract

The real-time modeling of interaction forces is essential for designing and controlling machines that traverse and manipulate granular materials. In a previous study, we analyzed the effects of motion-induced surface deformation at different depths and developed a depth-dependent drag force model based on the principles of resistive force theory (RFT). Through an energy variation analysis, we identified two primary factors that influence environmental changes: the generation of granular piles and changes in the local packing state. However, the role of object orientation has remained unexplored. In this study, we bridge this gap and extend the analysis to account for both depths and orientations, broadening the applicability of the model. To quantify the effect of orientation, we introduce the elastic potential energy as a measure of the packing state of granular media. This consideration contributes to integrating the induced surface deformation into the drag force model, providing physical insights into the prediction process. The model was validated through plate drag experiments and applied to predict the drag force of multi-connected plates, enhancing the accuracy of drag force prediction in scenarios involving significant surface changes. This real-time model offers a practical alternative to time-consuming computational methods, such as the discrete element method, enabling efficient analysis for a broader range of applications.