The present paper reports results from a computational simulation of probabilistic particulate reinforced composite behavior. The approach consists use of simplified micromechanics of particulate reinforced composites together with a Fast Probability Integration (FPI) technique. Sample results are presented for a Al/SiC(sub p)(silicon carbide particles in aluminum matrix) composite. The probability density functions for composite moduli, thermal expansion coefficient and thermal conductivities along with their sensitivity factors are computed. The effect of different assumed distributions and the effect of reducing scatter in constituent properties on the thermal expansion coefficient are also evaluated. The variations in the constituent properties that directly effect these composite properties are accounted for by assumed probabilistic distributions. The results show that the present technique provides valuable information about the scatter in composite properties and sensitivity factors, which are useful to test or design engineers.
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