Depth prediction of plastic vortex toward vortex flow-based friction stir additive manufacturing

IF 6.1 1区 工程技术 Q1 ENGINEERING, MANUFACTURING
Tao Ye , Xianjun Pei , Xiaochao Liu , Wentao Li , Xincheng Wang , Yongzhe Li , Zhonghua Ni , Lei Shi , Chuansong Wu
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引用次数: 0

Abstract

Vortex flow-based friction stir additive manufacturing (VFSAM) advances conventional FSAM by replacing the stir tool with a plastic vortex, eliminating tool wear in high-melting-point metals. However, the precise control of the vortex depth (which directly affects the deposition layer thickness and bonding quality) still faces the challenge of selecting process parameters. This study used the Order of Magnitude Scaling (OMS) method to establish a one-dimensional (1D) vortex depth analytical model, which enables rapid parameter selection for desired layer thickness. The core of the OMS method is to ignore the influence of secondary physical quantities and only retain the magnitude relationship of dominant factors, thereby achieving efficient parameter screening within the allowable error range. The 1D analytical model was applied to Ti-6Al-4V titanium alloy, with an objective function f (N, R) = NR identifying optimal parameters for maximum vortex depth. For Ti-6Al-4V, the optimal solution is f (N, R) = 6000, providing ideal parameters for achieving maximum depth. This streamlines the process optimization, enhancing VFSAM efficiency for high-performance applications.
基于涡流搅拌摩擦增材制造的塑料涡流深度预测
基于涡流流动的搅拌摩擦增材制造(VFSAM)是传统搅拌摩擦增材制造的进步,它用塑料涡流代替了搅拌工具,消除了高熔点金属中工具的磨损。然而,旋涡深度的精确控制(直接影响沉积层厚度和键合质量)仍然面临着工艺参数选择的挑战。本研究采用数量级缩放(Order of Magnitude Scaling, OMS)方法建立了一维(1D)涡深分析模型,实现了所需层厚参数的快速选择。OMS方法的核心是忽略二次物理量的影响,只保留主导因素的大小关系,从而在允许误差范围内实现有效的参数筛选。将一维解析模型应用于Ti-6Al-4V钛合金,以f (N, R) = NR为目标函数确定最大涡流深度的最优参数。对于Ti-6Al-4V,最优解为f (N, R) = 6000,为实现最大深度提供了理想参数。这简化了流程优化,提高了VFSAM在高性能应用中的效率。
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来源期刊
Journal of Manufacturing Processes
Journal of Manufacturing Processes ENGINEERING, MANUFACTURING-
CiteScore
10.20
自引率
11.30%
发文量
833
审稿时长
50 days
期刊介绍: The aim of the Journal of Manufacturing Processes (JMP) is to exchange current and future directions of manufacturing processes research, development and implementation, and to publish archival scholarly literature with a view to advancing state-of-the-art manufacturing processes and encouraging innovation for developing new and efficient processes. The journal will also publish from other research communities for rapid communication of innovative new concepts. Special-topic issues on emerging technologies and invited papers will also be published.
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