The following paper presents a novel FE simulation technique (KBC-FE), which reduces computational cost by performing simulations on a cloud computing environment, through the application of individual modules. Moreover, it establishes a seamless collaborative network between world leading scientists, enabling the integration of cutting edge knowledge modules into FE simulations.
The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques.
This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material’s forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.
Finite Element (FE) simulations have become a powerful tool for optimizing process parameters in the metal forming industry. The reliability of FE simulation results is dependent on the accuracy of the material definition, input in the form of flow stress data or constitutive equations, and the assignment of the boundary conditions, such as the friction coefficient and the heat transfer coefficient. In the past few years, advanced FE simulations have been developed via the implementation of user-defined subroutines, which have significantly broadened the capability of FE software.
The use of such advanced FE simulations in the design of forming processes for structural components has been investigated by both the aviation and automotive industries, with the intention of producing lightweight structures that reduces operating costs and CO2 emissions. Particular focus has been placed on the replacement of steel components with lower density materials, such as aluminum alloys and magnesium alloys. However, these alloys, especially the stronger variants, offer limited formability at room temperature and thus complex-shaped components cannot be manufactured using the conventional cold stamping process. Therefore, advanced high temperature forming technologies, such as warm aluminum forming 1-4, hot stamping of aluminum alloys 5-9 and hot stamping of high strength steels 10, have been developed over the past decades to enable complex-shaped components to be formed. In general, high temperature forming processes involve significant temperature variations, strain rate and loading path changes 11, which would, for instance, cause inevitable viscoplastic and loading history dependent responses from the work piece materials. These are intrinsic features of high temperature forming processes and may be difficult to represent using conventional FE simulation techniques. Another desirable feature would be the ability to predict the tool life over multiple forming cycles in such processes, since they require low friction characteristics achieved through coatings that degrade with each forming operation. To represent all these features via the implementation of user-defined subroutines would be computationally very expensive. Moreover, the development and implementation of multiple subroutines would require excessive multi-disciplinary knowledge from an engineer conducting the simulations.
In the present work, a novel Knowledge Based Cloud FE (KBC-FE) simulation technique is proposed, based on the application of modules on a cloud computing environment, that enables an efficient and effective method of modeling advanced forming features in conjunction with conventional FE simulations. In this technique, data from the FE software is processed at each cloud module, and then imported back into the FE software in the relevant consistent format, for further processing and analysis. The development of these modules and their implementation in the KBC-FE is detailed.
该KBC-FE模拟技术实现先进的模拟,以使用专用的模块进行场外。它可以运行于云环境的功能模块,即从不同的特化连接起来的节点,以确保过程仿真尽可能准确地进行。在KBC-FE模拟关键方面可能涉及有限码的独立性,计算的效率和功能模块的准确度。每个高级功能的一个模块中实现将依赖于一个新的模型和/或一个新的实验技术的发展。例如,成形极限模块是基于新的统一的成形极限预测模型11开发的,摩擦刀具寿命预测模块目前已经被互动式摩擦模型20实施开发。该KBC-FE模拟技术也提供了选择性的计算履行选择功能, 也就是说 ,只有元素标准选择用于各个模块进一步的评估。例如,工具寿命预测模块自动选择其中硬涂层倾向于破裂,由排名第1的所有元素的磨损率成形周期的元素,该元素的因而通常小于1%将被选择用于进一步多周期载荷条件下的刀具寿命评估。在本研究中,300形成循环后的工具寿命预测可在5分钟内完成。
通过进行相关试验,并相应地校准,成形极限模型可以适用于形成处理模拟,以从而确定用于成功地产生由这种合金的组分的最佳参数,并且没有缩颈的发生率。成形极限预测模型被开发为,这是独立的有限元软件的被利用云模块,并且可以被应用到任何有限元软件评估过程中的材料的成形性成形,无需复杂的子程序17。通过导入相关数据到模型,计算可以被进行,以确定故障是否发生,在该用户可以指定该组件的区域,从而节省了计算资源。然而,应该指出的是,作为应力 – 应变曲线是输入到通过简单的查表的有限元软件,可能难以在模拟过程中,以充分代表在不同温度和应变率的材料特性。
在刀具寿命预测模块,成型过程中的摩擦行为可以通过导入所需的变形历史数据到验证摩擦模块20,然后再导入为每个元素放回有限元软件的云模块计算出的离散数据点进行预测。这保证了高级摩擦模块可以被所有的FE码被使用,无论其掺入用户子程序能力。此外,国防部ULE可以并行运行,以进一步减少计算时间。交互式摩擦/磨损模型假定没有磨损颗粒的过程中的初始滑动,并作为一个结果,这将是合理的预期摩擦系数0.17 20的恒定初始值。尽管该模型揭示摩擦分布的演变,在成形过程中的摩擦行为是非常复杂的,并且难以从云模块的复合摩擦行为完全融入有限元模拟。
作为未来的技术,KBC-FE模拟将依靠专用基础和强大的互联网有限元模拟软件包开发,这需要一个高利润,但完全不同的商业模式,由软件开发商建立。此外,专用的内部网络需要在合作各方内部建立确保数据安全和工业系统的控制可靠性。 </p>
The authors have nothing to disclose.
The financial support from Innovate UK, Ultra-light Car Bodies (UlCab, reference 101568) and Make it lighter, with less (LightBlank, reference 131818) are gratefully acknowledged. The research leading to these results has received funding from the European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement No. 604240, project title ‘An industrial system enabling the use of a patented, lab-proven materials processing technology for Low Cost forming of Lightweight structures for transportation industries (LoCoLite)’. Significant support was also received from the AVIC Centre for Structural Design and Manufacture at Imperial College London, which is funded by Aviation Industry Corporation of China (AVIC).
AA6082-T6 | AMAG | Material | |
AA5754-H111 | AMAG | Material | |
1000 kN high-speed press | ESH | Forming press | |
ARGUS | GOM | Optical forming analysis | |
PAM-STAMP 2015 | ESI | FE simulation software | |
Matlab | MathWorks | Numerical calculation software | |
Gleeble 3800 | DSI | Uniaxial tensile test | |
High Temperature Tribometer (THT) | Anton Paar | Friction property test | |
NewViewTM 7100 | ZYGO | Surface profilometer | |
Magnetron sputtering equipment | Coating deposition | ||
Microhardness tester | Wolpert Wilson Instruments | ||
Nano-hardness indenter | MTS |