Linearization-based methods for the calibration of bonded-particle models

Abstract

In the work at hand, two methods for the calibration of the elastic material parameters of bonded-particle models (BPMs) are proposed. These methods are based on concepts of classical mechanics and enable a faster calibration compared to the conventional trial and error strategy. Moreover, they can be used to counter-check the consistency of the BPM. In the first method, the mathematical model is linearized and solved in a classical matrix-vector formulation similar to a finite element scheme. Further linearization in the second approach enables the direct calculation of the elastic stiffness tensor, reducing computational costs massively. To analyze the capabilities and limitations of both methods, they have been applied in three different case studies. Obtained results have shown that the new strategy allows us to significantly reduce the calculation time.

Modeling the devolatilization and fragmentation of biomass pellets with the bonded particle method for fluidized bed applications

“…Especially in the case of a coarsening approach, they are determined by calibrating the bonded particle model with experimental data. An in-depth explanation of how the calibration can be efficiently realized is shown by [19]. The proposed linearization methods for a faster calibration were also applied in the work at hand.…”

Discrete Element Modeling and Electron Microscopy Investigation of Fatigue-Induced Microstructural Changes in Ultra-High-Performance Concrete

“…Here, the strategy based on the direct stiffness method has been applied. The detailed description of this technique is provided in [ 44 ].…”

Mesh-free micromechanical modeling of inverse opal structures

“…The most widely used calibration strategies are based on inverse analysis principle with application of different methods for design of experiments [ 14 , 23 , 60 , 72 ]. More advanced strategies, like proposed by Estay et al [19] or the linearizationbased method used by Jarolin et al [31] , allow to estimate the model parameters directly based on the structural model. However, since the developed BPM model has a relatively small number of unknown parameters, the relatively simple parameter identification procedure was applied in this work.…”