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首页> 外文期刊>Journal of Materials Engineering and Performance >Statistical Modeling of Strain-Hardening Exponent and Grain Size of Nb-Microalloyed Steels Using a Two-Level Factorial Design of Experiment
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Statistical Modeling of Strain-Hardening Exponent and Grain Size of Nb-Microalloyed Steels Using a Two-Level Factorial Design of Experiment

机译：基于二级因子设计的铌微合金钢应变强化指数和晶粒尺寸的统计模型

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摘要

A factorial design of experiment (DOE) was used to statistically model the strain-hardening exponent and grain size of Nb-microalloyed steel sheets following hot rolling. The objective of the statistical model was to develop a method to simultaneously increase the strain-hardening exponent and refine the grain size of Nb-microalloyed steels by controlling three hot rolling process parameters: roughing temperature (RT), finishing temperature (FT), and coiling temperature (CT). The factorial DOE used two levels for the above temperatures and three replicates to obtain a reliable and precise estimate of the strain-hardening exponent and grain size. Analysis of variance was used to determine the most significant factors (individual parameters and their interactions) affecting the responses and develop appropriate regression equations. The regression equations predicted that optimal formability is obtained under the following conditions: RT = 1150℃, FT = 800℃, and CT = 700℃. Validation of the statistical model using microstructural characterization showed that the predicted value of the grain size was close to the experimental value.
机译：实验的析因设计（DOE）用于对Nb微合金化钢板在热轧后的应变硬化指数和晶粒尺寸进行统计建模。统计模型的目的是开发一种方法，该方法通过控制三个热轧工艺参数同时提高应变硬化指数和细化Nb微合金钢的晶粒尺寸：粗轧温度（RT），终轧温度（FT）和卷取温度（CT）。阶乘DOE在上述温度下使用了两个水平，并进行了三个重复，以获得应变硬化指数和晶粒尺寸的可靠而精确的估计。方差分析用于确定影响响应的最重要因素（各个参数及其相互作用），并开发适当的回归方程。回归方程预测在以下条件下可获得最佳成形性：RT = 1150℃，FT = 800℃，CT = 700℃。使用微结构表征对统计模型进行验证表明，晶粒尺寸的预测值接近于实验值。

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