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首页> 外文期刊>Procedia Manufacturing >Determination of Johnson-Cook material model parameters for AISI 1045 from orthogonal cutting tests using the Downhill-Simplex algorithm
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Determination of Johnson-Cook material model parameters for AISI 1045 from orthogonal cutting tests using the Downhill-Simplex algorithm

机译:使用下坡滑动算法从正交切削测试确定AISI 1045的Johnson-Cook材料模型参数

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Despite the increasing digitalization of manufacturing processes in the context of Industry 4.0, the process design and development of machining processes poses major challenges for today’s manufacturing technology. Compared to the conventional process design, which is influenced by an empirical "trial-and-error" principle, the simulative process design offers the possibility of reducing development time and costs while at the same time improving the process understanding. A possible simulation technique to achieve these goals is the Finite Element Method (FEM). The FEM enables the calculation of the thermo-mechanical load spectrum underlying the machining process. Therefore, different input models are required. One of the most critical input models is the material model, which describes the constitutive material behavior. To determine the material model parameters, either (conventional) material tests, which require an extrapolation into the regime of metal cutting, or inverse techniques are used, where the process itself is used as a material test. Using the inverse technique, the model parameters are modified iteratively until a predefined agreement between simulations and experiments is achieved. The evaluation of the agreement bases on integral process variables, such as the cutting force, and their simulative counterparts. However, the procedure of the inverse determination requires high computational efforts and is not robust. This paper presents a novel approach to enhance the robustness of the inverse material model parameter determination from the cutting process. Orthogonal cutting tests on AISI 1045 steel have been conducted on a broaching machine tool over a range of different cutting speeds and undeformed chip thicknesses to set an experimental database. Thereby, the workpiece material was investigated in the two different heat treatments: normalized and coarse-grain annealed. The machining experiments showed differences in terms of the integral process results when comparing the two heat treatments. These results motivated for the development of a methodology capable to determine material model parameters robust and inversely from the machining process, which can be used with lower computational effort. To simulate the machining process, a Coupled-Eulerian-Lagrangian (CEL) model of the orthogonal cutting process has been set up. The material model parameters have been inversely determined using the Downhill-Simplex-Algorithm, which has been modified for this case. By using the Downhill-Simplex-Algorithm, it was possible to determine material model parameters within 17 iterations and achieving an average deviation between the experiment and the simulations below 10 %. Thereby, different process observables such as temperature, forces, and chip form have been used for the evaluation. Through this method, it is possible to determine material model parameters, which enable a good match between experiments and simulations with a low computational effort.
机译:尽管在行业背景下的制造过程中规模越来越多,但加工过程的过程设计和开发为当今的制造技术带来了重大挑战。与传统的过程设计相比,受实验“试验和误差”原则的影响,模拟过程设计提供了降低开发时间和成本的可能性,同时提高过程理解。实现这些目标的可能模拟技术是有限元方法(FEM)。 FEM使得能够计算加工过程的热机械负载光谱。因此,需要不同的输入模型。最关键的输入模型之一是材料模型,其描述了本构体行为。为了确定材料模型参数,使用(常规)材料测试,其需要推断到金属切割的制度或逆技术中,其中该方法本身用作材料测试。使用逆技术,迭代地修改模型参数,直到实现了模拟与实验之间的预定协议。评估协议基础对整体过程变量,如切割力,以及它们的模拟对应物。但是,逆确定的程序需要高计算工作,并且不是强大的。本文介绍了一种新的方法来增强切割过程中逆材料模型参数测定的鲁棒性。 AISI 1045钢上的正交切削测试已经在一系列不同的切割速度和未变形的芯片厚度范围内进行了在拉削机床上,以设定实验数据库。由此,在两种不同的热处理中研究了工件材料:归一化和粗晶退火。加工实验在比较两个热处理时,在整体过程结果方面表现出差异。这些结果对于开发一种能够从加工过程中稳健地确定材料模型参数的方法,可以使用较低的计算工作。为了模拟加工过程,已经建立了耦合的eulerian-lagrangian(CEL)模型的正交切割过程。材料模型参数已经使用下坡 - 单面算法反转,该算法已被修改为这种情况。通过使用下坡单简单算法,可以在17次迭代中确定材料模型参数,并在实验之间实现平均偏差和低于10%的模拟。因此,已经使用了不同的过程可观察能量,例如温度,力和芯片形式。通过这种方法,可以确定材料模型参数,该参数能够在具有低计算工作的实验和模拟之间实现良好的匹配。

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