Experimental investigation and modeling of local resistance coefficient of reducing pipe using selective laser melting

被引:1
作者
Li, Dingbo [1 ]
Liu, Xiaochao [1 ,3 ]
Hou, Peiyao [1 ]
Liao, Honghui [2 ,4 ]
Nie, Rui [3 ,5 ,6 ]
Jiao, Zongxia [1 ,5 ,6 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, 37 Xueyuan Rd, Beijing 100191, Peoples R China
[2] Beihang Univ, Large Aircraft Adv Training Ctr, Beijing, Peoples R China
[3] Beihang Univ, Ningbo Inst Technol, Ningbo 315800, Peoples R China
[4] Tianmushan Lab, Hangzhou 310023, Peoples R China
[5] Beihang Univ, Sci & Technol Aircraft Control Lab, Beijing 100191, Peoples R China
[6] Beihang Univ, Key Lab Adv Airborne Syst, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Local resistance coefficient; Selective laser melting; Reducing pipe; Transitional flow; ROUGHNESS; SURFACE; FLOW;
D O I
10.1016/j.aej.2025.01.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Selective laser melting (SLM) technology is widely utilized in various industries such as aerospace, engineering machinery, and medical sectors due to its benefits in lightweight construction, rapid manufacturing cycles, and design adaptability. However, reducing pipes produced via SLM often exhibit significant and irregular surface roughness, posing challenges inaccurately predicting their local resistance coefficients using conventional hydrodynamic theories. Aiming at resolving this problem, the present study fabricates numerous Ti6Al4V reducing pipes with varying cone angles using SLM technology. The internal surface roughness distribution of these pipes is characterized and quantified. Through extensive experiments and numerical simulations, the local resistance coefficients of SLM reducing pipes are investigated, leading to the development of a novel prediction model. The study identifies several influencing factors on the local resistance coefficient, including cone angle, area ratio, Reynolds number, and surface roughness. It is observed that SLM reducing pipes encompass two distinct flow regions: the smooth region and the rough region, with the Reynolds numbers in the latter increasing with surface roughness. Moreover, a model incorporating critical values for both regions is established. The predicted local resistance coefficient model demonstrates a maximum error of only 10.96% when compared to experimental data, highlighting a substantial enhancement in prediction accuracy over traditional models.
引用
收藏
页码:391 / 402
页数:12
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