996 resultados para fracture network


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Concrete is heterogeneous and usually described as a three-phase material, where matrix, aggregate and interface are distinguished. To take this heterogeneity into consideration, the Generalized Beam (GB) lattice model is adopted. The GB lattice model is much more computationally efficient than the beam lattice model. Numerical procedures of both quasi-static method and dynamic method are developed to simulate fracture processes in uniaxial tensile tests conducted on a concrete panel. Cases of different loading rates are compared with the quasi-static case. It is found that the inertia effect due to load increasing becomes less important and can be ignored with the loading rate decreasing, but the inertia effect due to unstable crack propagation remains considerable no matter how low the loading rate is. Therefore, an unrealistic result will be obtained if a fracture process including unstable cracking is simulated by the quasi-static procedure.

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A general analytical model for a composite with an isotropic matrix and two populations of spherical inclusions is proposed. The method is based on the second order moment of stress for evaluating the homogenised effective stress in the matrix and on the secant moduli concept for the plastic deformation. With Webull's statistical law for the strength of SiCp particles, the model can quantitatively predict the influence of particle fracture on the mechanical properties of PMMCs. Application of the proposed model to the particle cluster shows that the particle cluster has neglected influence on the strain and stress curves of the composite. (C) 1998 Elsevier Science B.V.

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The fit of fracture strength data of brittle materials (Si3N4, SiC, and ZnO) to the Weibull and normal distributions is compared in terms of the Akaike information criterion. For Si3N4, the Weibull distribution fits the data better than the normal distribution, but for ZnO the result is just the opposite. In the case of SiC, the difference is not large enough to make a clear distinction between the two distributions. There is not sufficient evidence to show that the Weibull distribution is always preferred to other distributions, and the uncritical use of the Weibull distribution for strength data is questioned.