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Quantile Regression Model for Impact Toughness Estimation

机译:冲击韧性估计的分位数回归模型

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The purpose of this study was to develop a product design model for estimating the impact toughness of low-alloy steel plates. The rejection probability in a Charpy-V test (CVT) is predicted with process variables and chemical composition. The proposed method is suitable for the whole production line of a steel plate mill, including all grades of steel in production. The quantile regression model was compared to the joint model of mean and dispersion and the constant variance model. The quantile regression model proved out to be the most effective method for modelling a highly complicated property at this extent. Next, the developed model will be implemented into a graphical simulation tool that is in daily use in the product planning department and already contains some other mechanical property models. The model will guide designers in predicting the related risk of rejection and in producing desired properties in the product at lower cost.
机译:这项研究的目的是开发一种产品设计模型,以评估低合金钢板的冲击韧性。用过程变量和化学成分预测夏比-V测试(CVT)中的拒绝概率。所提出的方法适用于钢板轧机的整个生产线,包括生产中所有等级的钢。将分位数回归模型与均值和离差联合模型以及常数方差模型进行了比较。在这种程度上,分位数回归模型被证明是对高度复杂的属性进行建模的最有效方法。接下来,开发的模型将被实现为图形仿真工具,该模型在产品计划部门中日常使用,并且已经包含其他一些机械性能模型。该模型将指导设计人员预测相关的废品风险,并以较低的成本生产所需的产品特性。

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