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    Statistical Theory for Predicting the Failure of Brittle Materials

    Source: Journal of Applied Mechanics:;1991:;volume( 058 ):;issue: 001::page 43
    Author:
    S. She
    ,
    J. D. Landes
    ,
    J. A. M. Boulet
    ,
    J. E. Stoneking
    DOI: 10.1115/1.2897177
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Statistical models for predicting failure probability of brittle materials are investigated. A formula is derived from a physical consideration for the fracture of microcracks in materials based on the general forms of a fracture criterion and a statistical distribution function incorporating the weakest link principle. The relationships of this model and other statistical models in the literature are discussed; they were found to be equivalent for isotropic materials in which microcracks are randomly distributed in all directions. The statistical model is also used in a failure analysis of the round-notch four-point bending specimen made of an AISI 1008 steel. The grain boundary carbide particles are considered to be microcracks in the plastic zone near the notch tip. The distribution function in the statistical theory is derived from the density and size distribution of carbide particles in the steel. The statistical theory for a triaxial stress state is used to predict the failure probability for any given load on the specimen. The failure loads (loads corresponding to 50 percent of failure probability) are calculated for the specimen at different temperatures. The results are compared with experimental data; good agreement is obtained.
    keyword(s): Brittleness , Failure , Stress , Microcracks , Probability , Fracture (Process) , Steel , Particulate matter , Density , Temperature , Grain boundaries , Statistical distributions , Failure analysis AND Formulas ,
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      Statistical Theory for Predicting the Failure of Brittle Materials

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    http://yetl.yabesh.ir/yetl1/handle/yetl/108084
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    • Journal of Applied Mechanics

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    contributor authorS. She
    contributor authorJ. D. Landes
    contributor authorJ. A. M. Boulet
    contributor authorJ. E. Stoneking
    date accessioned2017-05-08T23:34:42Z
    date available2017-05-08T23:34:42Z
    date copyrightMarch, 1991
    date issued1991
    identifier issn0021-8936
    identifier otherJAMCAV-26330#43_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/108084
    description abstractStatistical models for predicting failure probability of brittle materials are investigated. A formula is derived from a physical consideration for the fracture of microcracks in materials based on the general forms of a fracture criterion and a statistical distribution function incorporating the weakest link principle. The relationships of this model and other statistical models in the literature are discussed; they were found to be equivalent for isotropic materials in which microcracks are randomly distributed in all directions. The statistical model is also used in a failure analysis of the round-notch four-point bending specimen made of an AISI 1008 steel. The grain boundary carbide particles are considered to be microcracks in the plastic zone near the notch tip. The distribution function in the statistical theory is derived from the density and size distribution of carbide particles in the steel. The statistical theory for a triaxial stress state is used to predict the failure probability for any given load on the specimen. The failure loads (loads corresponding to 50 percent of failure probability) are calculated for the specimen at different temperatures. The results are compared with experimental data; good agreement is obtained.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleStatistical Theory for Predicting the Failure of Brittle Materials
    typeJournal Paper
    journal volume58
    journal issue1
    journal titleJournal of Applied Mechanics
    identifier doi10.1115/1.2897177
    journal fristpage43
    journal lastpage49
    identifier eissn1528-9036
    keywordsBrittleness
    keywordsFailure
    keywordsStress
    keywordsMicrocracks
    keywordsProbability
    keywordsFracture (Process)
    keywordsSteel
    keywordsParticulate matter
    keywordsDensity
    keywordsTemperature
    keywordsGrain boundaries
    keywordsStatistical distributions
    keywordsFailure analysis AND Formulas
    treeJournal of Applied Mechanics:;1991:;volume( 058 ):;issue: 001
    contenttypeFulltext
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