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International Journal for Multiscale Computational Engineering
Factor de Impacto: 1.016 Factor de Impacto de 5 años: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Imprimir: 1543-1649
ISSN En Línea: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.2014006142
pages 1-21

INVESTIGATION OF MICRO-MACROSCALE INTERACTION OF HETEROGENEOUS MATERIALS BY A PARALLEL-BONDED PARTICLE MODEL AND INTRODUCTION OF NEW MICROPARAMETER DETERMINATION FORMULATIONS

Serkan Nohut
Zirve University, Faculty of Engineering, Kizilhisar Kampusu, 27260, Gaziantep, Turkey
Abdulkadir Cevik
University of Gaziantep, Department of Civil Engineering, 27310, Gaziantep, Turkey

SINOPSIS

The distinct element method (DEM) is becoming an effective method of investigating engineering problems in granular and heterogeneous materials, especially in granular flows, powder mechanics, advanced ceramics, and rock mechanics. Creation of a DEM model requires some microscale material parameters, unable to be physically measured in laboratories; a calibration process is typically used in order to select the proper microparameters using DEM simulations. The calibration process is basically trial and error, which depends on the experience of the modeler. Therefore such a process may be complicated and time consuming for the user. In this study, a parametric study is performed in order to determine the relations of microparameters used in three dimensional DEM model and the macroscale material parameters (i.e., Young's modulus, Poisson's ratio, compressive strength). According to dependencies and independencies between microparameters and macroparameters, empirical fitting functions are obtained by using a stepwise regression method. The macroparameters calculated by empirical fitting functions reveal a good agreement with DEM results. The predictive ability of fitting functions is confirmed with the creation of further data sets in DEM simulations. Comparison of the fitting values with the literature shows that the fitting functions may also be used two dimensional DEM simulations. The micro-macro scale interactions and empirical fitting functions provided in this study would be very helpful for the user in order to observe the relationship between micro- and macroparameters and determine the approximate proper microparameters.

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