Title of article :
Simulation of local material properties based on moving-window GMC
Author/Authors :
Graham ، نويسنده , , L.L. and Baxter، نويسنده , , S.C.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2001
Abstract :
When analyzing the behavior of composite materials under various loading conditions, the assumption is generally made that the behavior due to randomness in the material can be represented by a homogenized, or effective, set of material properties. This assumption may be valid when considering displacement, average strain, or even average stress of structures much larger than the inclusion size. The approach is less valid, however, when considering either behavior of structures of size at the scale of the inclusions or local stress of structures in general. In this paper, Monte Carlo simulation is used to assess the effects of microstructural randomness on the local stress response of composite materials. In order to achieve these stochastic simulations, the mean, variance and spectral density functions describing the randomly varying elastic properties are required as input. These are obtained here by using a technique known as moving-window generalized method of cells (moving-window GMC). This method characterizes a digitized composite material microstructure by developing fields of local effective material properties. Once these fields are generated, it is straightforward to obtain estimates of the associated probabilistic parameters required for simulation. Based on the simulated property fields, a series of local stress fields, associated with the random material sample under uniaxial tension, is calculated using finite element analysis. An estimation of the variability in the local stress response for the given random composite is obtained from consideration of these simulations.
Keywords :
stochastic simulation , Micromechanics , microstructure , generalized method of cells , characterization , Material homogenization , Stochastic mechanics
Journal title :
Probabilistic Engineering Mechanics
Journal title :
Probabilistic Engineering Mechanics