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首页> 外文期刊>鉄と鋼/Journal of the Iron and Steel Institute of Japan. >Statistics of Extremes Analysis of Nonmetallic Inclusions Based on 3D Inspection
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Statistics of Extremes Analysis of Nonmetallic Inclusions Based on 3D Inspection

机译:基于3D检测的非金属夹杂物极限分析的统计数据

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It is well known that the scatter of fatigue strength of high strength steels is caused by nonmetallic inclusions. The lower bound of the scatter of fatigue strength can be predicted by considering the maximum size of nonmetallic inclusions. Thus, it is of practical importance to estimate the maximum size of nonmetallic inclusions by appropriate inclusion rating methods. Most rational and convenient method to predict the maximum size of inclusions is the one based on the statistics of extremes. Therefore, recently the inclusion rating based on the statistics of extremes has been used by many industries, though the rating methods are mostly two-dimensional (2D) optical methods. It is known that the accuracy of the 2D method is lower than the exact 3D method In addition, when multiple type inclusions having different chemical composition are contained in a material, the statistics of extremes distribution does not necessarily become a single straight line but become a bilinear line. The objectives of the present study are (1) to clarify the validity of the 2D method and (2) to establish the method to predict the maximum inclusion size when the statistics extremes distribution becomes bilinear. The results obtained show that the 2D method is basically correct as predicted by the computer simulation. When a bilinear distribution is obtained, it is necessary to determine the minimum inspection area S_(crit) for predicting the maximum size of the larger type inclusions, which become the fatigue fracture origins of components.
机译:众所周知,高强度钢的疲劳强度是由非金属夹杂物引起的。可以通过考虑非金属夹杂物的最大尺寸来预测疲劳强度散布的下限。因此,通过适当的夹杂物评级方法估算非金属夹杂物的最大尺寸具有实际意义。预测夹杂物最大尺寸的最合理,最便捷的方法是基于极端情况的统计数据。因此,尽管许多方法大多是二维(2D)光学方法,但许多行业最近都在使用基于极限统计的夹杂物评级方法。已知2D方法的精度低于精确3D方法。另外,当材料中包含具有不同化学组成的多种类型的夹杂物时,极限分布的统计信息不一定会变成一条直线,而是变成一条直线。双线性线。本研究的目的是(1)阐明2D方法的有效性,以及(2)建立当统计极限分布变为双线性时预测最大夹杂物大小的方法。所得结果表明,二维方法基本上是正确的,正如计算机模拟所预测的那样。当获得双线性分布时,有必要确定最小检查区域S_(crit),以预测较大类型夹杂物的最大尺寸,这些夹杂物将成为组件的疲劳断裂起点。

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