Dynamic Calibration of DEM Simulations Using Rotating Drum Experiments Using the Mean Absolute Error

ABSTRACT The discrete element method (DEM) is widely used, but its predictive capability strongly depends on microscopic contact parameters that are difficult to measure directly. This work presents a systematic calibration approach using rotating drum experiments combined with image‐based analysis. Two macroscopic flow properties, the dynamic angle of repose and the roughness index, are extracted from experimental and simulated image sequences with a unified workflow. Individual metrics often agree only partially between experiment and simulation. Therefore, a new area‐based comparison method is introduced: the mean absolute error (MAE) between sequence matrices of particle occurrence. The MAE integrates differences in surface structure and dynamic flow behavior, providing a more robust calibration metric. First results demonstrate that the MAE enables a more reliable identification of suitable DEM parameter combinations.