path design
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2022 ◽  
pp. 101582
Author(s):  
Lin Yu ◽  
Fahui Wu ◽  
Zhihai Xu ◽  
Zhigang Xie ◽  
Dingcheng Yang

Author(s):  
Adel M. Al Ajmi ◽  
Raoof Gholami ◽  
Ali Shakouri ◽  
Oveis Farzay
Keyword(s):  

2021 ◽  
Author(s):  
Yongdi Wang ◽  
Hongwei Li ◽  
Pengfei Gao ◽  
Mei Zhan ◽  
Xinggang Yan ◽  
...  

Abstract Multi-pass conventional spinning is the preferable forming technology for the forming of thin-walled conical part with curved surface (TCPCS) in aerospace field. In multi-pass conventional spinning, the design of roller path is a critical problem due to its sensitive effect on the deformation mode and forming defect during spinning process. However, at present, the roller path is still mainly designed based on experience and trial-and-error, which seriously restricts the high-performance spinning of TCPCS. In this work, a new quantitative method based on circumferential strain distribution was developed for the roller path design in multi-pass conventional spinning of TCPCS. In this method, the total required circumferential strain for the forming of final TCPCS by conventional spinning was firstly determined. Then, the spinning passes number were obtained through dividing the total required circumferential strain by the ultimate circumferential strain producing the spinning instability ( ε θult ). As for the roller path profile in each pass, it is divided into two sections and determined respectively, i.e. the attaching mandrel section and the performing section. The attaching mandrel section presents the same profile of mandrel. The profile of preforming section is determined point-by-point by distributing the rest of circumferential strain { ε θni } to produce the final TCPCS. The point-by-point distributed circumferential strain is half of the { ε θni } at the initial stage until reaches the half of ε θult , then it will keep the half of ε θult to the end. The proposed new method of roller path design was validated by finite element simulation, where well spinning stability, wall thickness distribution and roundness were obtained. This method provides a quantitative, high-efficient and universal way for the roller path design in conventional spinning of TCPCS.


Materials ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6703
Author(s):  
Guo-Zheng Quan ◽  
Yan-Ze Yu ◽  
Xue Sheng ◽  
Kun Yang ◽  
Wei Xiong

In order to obtain the desired mechanical properties of products, an innovative method of loading parameter designs for acquiring the desired grain refinement is proposed, and it has been applied in the compression process of Ni80A superalloy. The deformation mechanism maps derived from processing maps based on the Dynamic Materials Model (DMM) theory were constructed, since the critical indicator values corresponding to dynamic recrystallization (DRX) and dynamic recovery (DRV) mechanisms were determined. The processing-parameter domains with DRX mechanisms were separated from the deformation mechanism map, while such domains were chaotic and difficult to apply in innovative parameter loading path design. The speed-loading path derived from strain rate-loading path in a compression process was pursued. The grain refinement domains are discretized into a finite series of sub-domains with clear processing parameters, and the optimal strain rate of each sub-domain is determined by step-by-step finite element simulation. A 3D response surface of the innovative optimal loading path of strain rate was fitted by interpolating methods. Finally, the isothermal compression experiments for Ni80A superalloy were conducted, and the microstructure observations indicated that the desired grain refinement was achieved. This innovative method of parameter loading path design contributes to the microstructure adjustment of the alloys with DRX mechanism.


2021 ◽  
Author(s):  
Yendo Hu ◽  
Yiliang Wu ◽  
Xue Bai ◽  
Minghong Chen ◽  
Zhuo Guanglei ◽  
...  
Keyword(s):  

2021 ◽  
Vol 17 (3) ◽  
pp. 1-7
Author(s):  
Yu-Jin Kim ◽  
Ki-Bong Kim ◽  
Euy-Joon Lee ◽  
Eun-Chul Kang
Keyword(s):  

2021 ◽  
Author(s):  
Xiaomeng Lv ◽  
Ao Liao ◽  
Weihua Xu ◽  
Yangzhi Liu ◽  
Yilong Wu ◽  
...  

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