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Author:

Du, Xiu-Li (Du, Xiu-Li.) (Scholars:杜修力) | Jin, Liu (Jin, Liu.) (Scholars:金浏)

Indexed by:

EI Scopus PKU CSCD

Abstract:

A new method, meso-element equivalent model, was proposed in the paper to analyze the macro mechanical properties of concrete materials. The method was described to start with the meso-scale of concrete; the Monte Carlo method was used to generate the random aggregate model of concrete composed of the aggregate particles and the mortar matrix. And then, the finite element grid was meshed based on characteristic element scale of concrete materials, and the mesh grid was projected onto the established random aggregate model. The mechanical properties of every element were determined by equivalence method of composite-materials. The proposed approach reflected the recognition of the macro-scopic mechanical properties of material nonlinearity due to their inherent heterogeneity. While the meso mesh whether affecting the macroscopic mechanical properties of concrete, was taken as the criterion for the non-uniformity description. Hence, comparing with the meso-mechanical method, the excellent advantages of the method was that the system reduced the number of degrees of freedom greatly, which improved the computational efficiency, especially for 3D problems. The examples analysis in the paper confirmed the high efficiency of this method.

Keyword:

Glass ceramics Efficiency Aggregates Degrees of freedom (mechanics) Computational efficiency Mechanical properties Mesh generation Concrete aggregates Concretes Monte Carlo methods

Author Community:

  • [ 1 ] [Du, Xiu-Li]The Key Laboratory of Urban Security and Disaster Engineering (Ministry of Education), Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Jin, Liu]The Key Laboratory of Urban Security and Disaster Engineering (Ministry of Education), Beijing University of Technology, Beijing 100124, China

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Source :

Chinese Journal of Computational Mechanics

ISSN: 1007-4708

Year: 2012

Issue: 5

Volume: 29

Page: 654-661

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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