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Micro-Mechanical Studies on Graphite Strength Prediction Models

机译:石墨强度预测模型的微机械研究

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The influence of type of loading and size-effects on the failure strength of graphite were studied using Weibull model. It was observed that this model over-predicts size effect in tension. However, incorporation of grain size effect in Weibull model, allows a more realistic simulation of size effects. Numerical prediction of strength of four-point bend specimen was made using the Weibull parameters obtained from tensile test data. Effective volume calculations were carried out and subsequently predicted strength was compared with experimental data. It was found that Weibull model can predict mean flexural strength with reasonable accuracy even when grain size effect was not incorporated. In addition, the effects of microstructural parameters on failure strength were analyzed using Rose and Tucker model. Uniaxial tensile, three-point bend and four-point bend strengths were predicted using this model and compared with the experimental data. It was found that this model predicts flexural strength within 10%. For uni-axial tensile strength, difference was 22% which can be attributed to less number of tests on tensile specimens. In order to develop failure surface of graphite under multi-axial state of stress, an open ended hollow tube of graphite was subjected to internal pressure and axial load and Batdorf model was employed to calculate failure probability of the tube. Bi-axial failure surface was generated in the first and fourth quadrant for 50% failure probability by varying both internal pressure and axial load.
机译:使用Weibull模型研究了载荷和尺寸效应类型对石墨故障强度的影响。观察到这一模型过度预测尺寸效果。但是,在威布尔模型中纳入晶粒尺寸效应,允许更现实的尺寸效应模拟。使用从拉伸试验数据获得的威布尔参数进行四点弯曲标本强度的数值预测。进行有效的体积计算,随后将预测的强度与实验数据进行比较。结果发现,即使未结合晶粒尺寸效应,Weibull模型也可以采用合理的准确性预测平均弯曲强度。此外,使用玫瑰和塔克模型分析了微观结构参数对故障强度的影响。使用该模型预测单轴拉伸,三点弯曲和四点弯曲强度,并与实验数据进行比较。发现该模型在10%以内预测弯曲强度。对于单轴拉伸强度,差异为22%,其可归因于少量的拉伸试样上的测试。为了在多轴应力状态下产生石墨的故障表面,将石墨的开放式中空管进行内部压力,采用轴向载荷和Batdorf模型来计算管的故障概率。通过改变内部压力和轴向载荷,在第一和第四象限中在第一和第四象限中产生双轴故障表面,以50%的故障概率。

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