首页> 外文期刊>Frattura e Integrita Strutturale >Design of Experiment as a powerful tool when applying Finite Element Method: a case study on prediction of hot rolling process parameters
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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:应用有限元方法时作为强大工具的实验设计:以热轧工艺参数预测为例

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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:热轧道次设计的最终目标是制造具有所需尺寸精度,无缺陷表面和机械性能的轧制产品。正确选择工艺参数对于满足对轧制产品所需的质量和几何性能不断增长的要求至关重要。由于金属流在高温下的复杂行为以及形状轧制中的严重塑性变形,因此迄今为止所做的大多数努力仅依赖于操作员获得的实践经验。涉及到的大量变量以及研究过程特性的困难,使得使用有限元(FE)工具成为全面了解轧制过程的有效且有吸引力的机会。在这项工作中,实验设计(DOE)是提出了一种强大而可行的方法来预测轧制工艺参数,同时减少了计算量。针对大量复杂的横截面形状开发了热轧过程的非线性3D FE模型,并针对真实植物产品在变形序列各个阶段提供的实验证据进行了验证。基于已验证的有限元模型的准确性,DOE被用于研究一系列许多参数和方案下的扁钢轧制过程。分析了主要轧制变量对轧制产品的材料流动行为和几何特征的影响。选择的DOE因素是工件温度,直径大小,直径减小(下沉)和轧辊角速度。所选的DOE响应为工件散布,有效应力,接触应力和滚动反作用载荷。最终,帕累托最优性(一种多准则决策方法)的应用允许检测设计因素的最佳组合,这些因素考虑了响应的期望目标要求。

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