用萤火虫算法优化汽车尾盖断裂

IF 0.8 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Swarm Intelligence Research Pub Date : 2020-03-20 DOI:10.1504/ijsi.2020.106396
G. Kakandikar, Omkar Kulkarni, Sujata L. Patekar, Trupti Bhoskar
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引用次数: 2

摘要

拉深是一种制造过程,其中钣金板是逐步形成一个三维形状,通过机械作用的冲压成形金属内部模具。金属的流动是一种复杂的机制。用于烹饪的锅、锅、容器、水槽、汽车车身部件(如面板和油箱)都是通过深拉深制造的少数产品。在成形过程中,均匀的应变分布可以得到高质量的零件。板料零件的主要失效形式是回弹、起皱和断裂。在拉伸载荷过大的情况下,拉伸件发生断裂或颈缩。断裂的预测和预防取决于刀具的设计和工艺参数的选择。萤火虫算法是一种受自然界萤火虫行为启发的优化算法。提出了一种优化汽车零部件尾盖断裂的新方法。优化问题被定义为在模具半径、冲床半径和压边力约束下对断裂进行优化。采用萤火虫算法求解最优工艺参数。并进行了数值实验验证。
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Optimising fracture in automotive tail cap by firefly algorithm
Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.
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来源期刊
International Journal of Swarm Intelligence Research
International Journal of Swarm Intelligence Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.50
自引率
0.00%
发文量
76
期刊介绍: The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.
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