Characterising and modelling plasma transferred arc for additive manufacturing

被引:2
作者
Chen, Guangyu [1 ]
Sun, Yongle [1 ]
Wang, Chong [1 ]
Ding, Jialuo [1 ]
Suder, Wojciech [1 ]
Li, Zhiyong [1 ]
Williams, Stewart [1 ]
机构
[1] Cranfield Univ, Welding & Addit Mfg Ctr, Wharley End MK43 0AL, Beds, England
关键词
Additive manufacture; Directed energy deposition; Plasma transferred arc; Power density distribution; Heat source model; GAS; EFFICIENCY; HEAT; DISTRIBUTIONS;
D O I
10.1016/j.ijheatmasstransfer.2025.126735
中图分类号
O414.1 [热力学];
学科分类号
摘要
The thermal characteristics of a plasma transferred arc (PTA) and its mathematical representation are primary considerations when designing and modelling PTA-based wire arc additive manufacturing (WAAM). However, most of the currently used PTA thermal characteristics are derived from welding processes, which are not directly applicable to WAAM. In this study, the power density distribution, arc diameter and arc efficiency of PTA in the WAAM process were measured using the split anode calorimetry (SAC) method. The effects of key process parameters, including current intensity, plasma gas composition, plasma gas flow rate, and arc length, on the PTA power profile were systematically examined. The results show that for a typical PTA used in WAAM, the arc diameter ranged from 9.6 mm to 10.8 mm, with an arc efficiency of approximately 60 % within the tested parameter range. The PTA power becomes more concentrated as power density increases with higher current intensity and plasma gas flow rates. Additionally, a softer plasma was achieved by increasing helium content in the plasma gas or by using a longer nozzle-to-workpiece standoff distance, both of which are beneficial for avoiding keyhole defects. To accurately represent PTA power distribution, a binomial Gaussian heat source model was proposed, which captures the details of the arc power profile with a high accuracy of over 99.94 %, outperforming the conventional monomial Gaussian heat source model. The PTA calorimetry characterisation and the proposed binomial Gaussian model can be useful in establishing a better understanding of the PTA power profile and enhancing process control for high-precision WAAM.
引用
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页数:12
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