文章基本信息

标题：Mechanics-based statistics of failure risk of quasibrittle structures and size effect on safety factors
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作者：Zdeněk P. Bažant ; Sze-Dai Pang
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2006
卷号：103
期号：25
页码：9434-9439
DOI：10.1073/pnas.0602684103
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：In mechanical design as well as protection from various natural hazards, one must ensure an extremely low failure probability such as 10-6. How to achieve that goal is adequately understood only for the limiting cases of brittle or ductile structures. Here we present a theory to do that for the transitional class of quasibrittle structures, having brittle constituents and characterized by nonnegligible size of material inhomogeneities. We show that the probability distribution of strength of the representative volume element of material is governed by the Maxwell-Boltzmann distribution of atomic energies and the stress dependence of activation energy barriers; that it is statistically modeled by a hierarchy of series and parallel couplings; and that it consists of a broad Gaussian core having a grafted far-left power-law tail with zero threshold and amplitude depending on temperature and load duration. With increasing structure size, the Gaussian core shrinks and Weibull tail expands according to the weakest-link model for a finite chain of representative volume elements. The model captures experimentally observed deviations of the strength distribution from Weibull distribution and of the mean strength scaling law from a power law. These deviations can be exploited for verification and calibration. The proposed theory will increase the safety of concrete structures, composite parts of aircraft or ships, microelectronic components, microelectromechanical systems, prosthetic devices, etc. It also will improve protection against hazards such as landslides, avalanches, ice breaks, and rock or soil failures.
关键词：cohesive fracture ; extreme value statistics ; activation energy ; Maxwell–Boltzmann ; scaling