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Design of Experiment as a powerful tool when applying Finite Element Method: a case study on prediction of hot rolling process parameters

机译:应用有限元方法时,实验设计为强大的工具:采用热轧工艺参数预测的案例研究

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摘要

The ultimate goal in hot roll pass design is to manufacture a rolled product with the required dimensional accuracy, defect free surface, and mechanical properties. The proper selection of process parameters is crucial to meet increasing requirements for desired quality and geometrical properties of rolled products. Due to the complex behavior of the metal flow at high temperatures and the severe plastic deformations in shape rolling, most efforts that have been made so far only rely upon the practical experience gained by operators. The large number of variables involved and the difficulty in investigating the process characteristics, make the use of finite element (FE) tools an effective and attractive opportunity towards a thorough understanding of the rolling process. In this work, Design of Experiment (DOE) is proposed as a powerful and viable method for the prediction of rolling process parameters while reducing the computational effort. Nonlinear 3D FE models of the hot rolling process are developed for a large set of complex cross-section shapes and validated against experimental evidences provided by real plant products at each stage of the deformation sequence. Based on the accuracy of the validated FE models, DOE is applied to investigate the flat rolling process under a series of many parameters and scenarios. Effects of main roll forming variables are analyzed on material flow behavior and geometrical features of a rolled product. The selected DOE factors are the workpiece temperature, diameter size, diameter reduction (draught), and rolls angular velocity. The selected DOE responses are workpiece spread, effective stresses, contact stresses, and rolls reaction loads. Eventually, the application of Pareto optimality (a Multi-Criteria Decision Making method) allows to detect an optimal combination of design factors which respect desired target requirements for the responses.
机译:热轧通道设计的最终目标是制造具有所需尺寸精度,缺陷的自由表面和机械性能的轧制产品。正确选择的工艺参数对于满足轧制产品的所需质量和几何特性的提高要求至关重要。由于金属流动在高温下的复杂行为和形状轧制的严重塑性变形,大多数努力已经依赖于操作员获得的实际经验。涉及的大量变量以及调查过程特征的难度,利用有限元(FE)工具对滚动过程的彻底理解有效和有吸引力的机会。在这项工作中,提出了实验(DOE)的设计作为预测轧制工艺参数的强大而可行的方法,同时降低计算工作。热轧工艺的非线性3D Fe模型是为大量复杂的横截面形状开发,并针对在变形序列的每个阶段提供的真实植物产品提供的实验证据。根据验证的Fe模型的准确性,应用DOE以研究在许多参数和场景中的一系列中的扁平轧制过程。分析了主辊形成变量的影响,对轧制产品的材料流动行为和几何特征进行了分析。所选的DOE因子是工件温度,直径尺寸,直径减少(草稿),并滚动角速度。所选择的DOE响应是工件涂布,有效应力,接触应力,并卷起反应载荷。最终,帕累托最优性的应用(多标准决策方法)允许检测尊重响应所需目标要求的设计因子的最佳组合。

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