首页> 外文会议>ASME Pressure Vessels and Piping conference >A MONTE CARLO IMPLEMENTATION OF THE JAMES-FORD-JIVKOV MICRO-STRUCTURALLY INFORMED LOCAL APPROACH APPLIED TO PREDICT FRACTURE TOUGHNESS INCLUDING LOW CONSTRAINT CONDITIONS
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A MONTE CARLO IMPLEMENTATION OF THE JAMES-FORD-JIVKOV MICRO-STRUCTURALLY INFORMED LOCAL APPROACH APPLIED TO PREDICT FRACTURE TOUGHNESS INCLUDING LOW CONSTRAINT CONDITIONS

机译:James-FORD-JIVKOV微结构知悉的局部方法的蒙特卡罗实施方法,用于预测包括低约束条件在内的断裂韧性

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The need to predict changes in fracture toughness for materials where the tensile properties change through life, such as with irradiation, whilst accounting for geometric constraint effects, such as crack size, are clearly important. Currently one of the most likely approaches by which to develop such ability are through application of local approach models. These approaches appear to be sufficient in predicting lower shelf toughness under high constraint conditions, but may fail when attempting to predict toughness in the transition region or for low constraint geometries when using the same parameters, making predictions impossible. Cleavage toughness predictions in the transition regime that are then extended to low constraint conditions are here made with a stochastic, Monte Carlo implementation of the recently proposed James-Ford-Jivkov model. This implementation is based around the creation of individual initiators following the experimentally observed distribution for specific RPV steel, and determining if these initiators form voids or cause cleavage failure using the model's improved criterion for particle failure. The model has shown to predict experimentally measured locations of cleavage initiators. Further, initial results from the Monte Carlo implementation of the model predicts the fracture toughness in a large part of the transition region, demonstrates an ability to predict the constraint shift and shows a level of scatter similar to that observed experimentally. All results presented, for a given material, are obtained without changes in the model parameters. This suggests that the model can be used predicatively for assessing toughness changes due to constraint-and temperature-driven plasticity changes.
机译:预测材料的断裂韧性的变化非常重要,因为材料的抗拉性能会随着寿命的变化而变化,例如随着辐射的变化,同时考虑到几何约束效应(例如裂纹尺寸)的重要性。当前,开发这种能力的最可能方法之一是通过局部方法模型的应用。这些方法似乎足以在高约束条件下预测较低的货架韧性,但在尝试预测过渡区域的韧性时或在使用相同参数的情况下针对低约束几何形状时可能会失败,从而无法进行预测。在过渡态中的断裂韧性预测随后扩展到低约束条件,这是使用最近提出的James-Ford-Jivkov模型的随机蒙特卡洛实现方法进行的。此实现是基于遵循特定RPV钢的实验观察到的分布创建单个引发剂,并使用模型的改进的颗粒破坏准则确定这些引发剂是否形成空隙或引起解理破坏。该模型已显示预测裂解引发剂的实验测量位置。此外,该模型的蒙特卡洛实现的初始结果可预测过渡区域大部分的断裂韧性,具有预测约束位移的能力,并显示出与实验观察到的相似的散射水平。对于给定的材料,给出的所有结果均无需更改模型参数即可获得。这表明该模型可用于评估由于约束和温度驱动的塑性变化而引起的韧性变化。

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