Granular damping analysis using an improved discrete element approach

Abstract

Granular damping has promising potential for vibration suppression in harsh environment. Currently, the discrete element method (DEM) is adopted in the granular damping analysis that typically involves a large number of granules. While the discrete element method, which is essentially built upon the direct numerical integration of Newton's equations, has been widely used in various analyses involving granular motion, the granular damping analysis faces unique challenge in several aspects. Unlike many other granular motion analyses, in the granular damping analysis the movements of the granules are strongly coupled with that of the host structure, and the granules experience extremely frequent collisions with each other. Meanwhile, the energy dissipation mechanism is highly nonlinear, and can only be evaluated with sufficiently long simulation time especially for structures vibrating in the low-frequency range. In order to increase the analysis efficiency to enable large-scale parametric studies, in this research we develop a new computational scheme for granular damping analysis using the discrete element approach. The main idea is to enhance the efficiency of contact detection in such analysis. To reduce the number of candidate granular pairs for contact check, an improved link cell (LC) scheme is proposed which takes advantage of the contacting force relation. This is followed by incorporating a Verlet table into the analysis that records all granular pairs whose distances are less than a certain threshold distance. The Verlet table for candidate pairs will be updated in an adaptive manner, corresponding to the dynamic states of the vibrating system. We also study the effect of time step in the numerical simulation, and develop a procedure that can optimize the time-step selection based on the contact mechanics. Collectively, these improvements can increase the computational efficiency of the discrete element method by multiple times as compared to the state-of-the-art. The proposed approach is validated by correlating to benchmark numerical and experimental results. With the new algorithm as basis, case studies are carried out to illustrate the analysis of granular damping mechanisms and the optimization of damping performance.