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Statistical Fracture Mechanics — Basic Concepts and Numerical Realization
Abstract The apparent randomness of brittle fracture is closely associated with the distribution of defects on various scales within a solid. The presence of microdefects is modeled by a random field of specific fracture energy γ following the framework of Statistical Fracture Mechanics (SFM). A brief summary of SFM is presented. SFM is the only model which explicitly incorporates the fractographic information, e.g. fractal characterization of fracture surfaces in the probabilistic description of brittle fracture. At the same time, the model has limitations in engineering applications, mainly due to its mathematical complexity. In this paper the Monte Carlo technique is employed to overcome these limitations. It allows one to combine the physical insight and modeling of the fracture mechanisms in SFM with the flexibility of the Monte Carlo method. Probability distributions of the fracture parameters such as a critical load, critical crack length, and fracture toughness are simulated and compared with experimental observations. Dependency of the conventional measure of fracture toughness on roughness of crack profiles, specimen and grain size, as well as load level is discussed. The ambiguity of the concept of fracture toughness in a probabilistic setting is addressed.
Statistical Fracture Mechanics — Basic Concepts and Numerical Realization
Abstract The apparent randomness of brittle fracture is closely associated with the distribution of defects on various scales within a solid. The presence of microdefects is modeled by a random field of specific fracture energy γ following the framework of Statistical Fracture Mechanics (SFM). A brief summary of SFM is presented. SFM is the only model which explicitly incorporates the fractographic information, e.g. fractal characterization of fracture surfaces in the probabilistic description of brittle fracture. At the same time, the model has limitations in engineering applications, mainly due to its mathematical complexity. In this paper the Monte Carlo technique is employed to overcome these limitations. It allows one to combine the physical insight and modeling of the fracture mechanisms in SFM with the flexibility of the Monte Carlo method. Probability distributions of the fracture parameters such as a critical load, critical crack length, and fracture toughness are simulated and compared with experimental observations. Dependency of the conventional measure of fracture toughness on roughness of crack profiles, specimen and grain size, as well as load level is discussed. The ambiguity of the concept of fracture toughness in a probabilistic setting is addressed.
Statistical Fracture Mechanics — Basic Concepts and Numerical Realization
Chudnovsky, A. (author) / Gorelik, M. (author)
1994-01-01
18 pages
Article/Chapter (Book)
Electronic Resource
English
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