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논문 기본 정보

자료유형
학술저널
저자정보
M. Mesbah (University of Malaya) A. Fattahi (University Putra Malaysia) A. R. Bushroa (University of Malaya) G. Faraji (University of Tehran) K. Y. Wong (Universiti Teknologi Malaysia) W. J. Basirun (University of Malaya) A. Fallahpour (Universiti Teknologi Malaysia) B. Nasiri‑Tabrizi (Taylor’s University)
저널정보
대한금속·재료학회 Metals and Materials International Metals and Materials International Vol.27 No.2
발행연도
2021.1
수록면
277 - 297 (21page)

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초록· 키워드

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Ultrafine grained ZK60 magnesium (UFG–ZK60 Mg) tubes were successfully fabricated by a parallel tubular-channel angularpressing (PTCAP) process. The number of pass effects on the phase composition, microstructural features and mechanicalproperties were examined. Also, two types of Artificial Neural Network known as Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) were employed to accurately estimate mechanical behavior of the PTCAP-processed ZK60 Mgalloy. The results showed that all the processed tubes had more refined microstructure with ~ 7 to 0.9 μm grain sizes, whichconsist of an average crystallite size between 68 ± 8 and 51 ± 8 nm, compared to the as-received specimen with a mean grainsize of ~ 90 μm. Similar XRD profiles were achieved following different PTCAP passes, however, some discrepancies wereobserved as the number of passes increased, which corroborated the structural changes during the PTCAP process. Themicroscopic observations also revealed the microstructural changes by increasing the PTCAP passes. The hardness of theprocessed tubes increased with the number of PTCAP passes, from 77 ± 2 HV for the unprocessed alloy to a maximum of111 ± 2 HV at three PTCAP passes. The PTCAP process increased not only mechanical strength but also the ductility of theprocessed tubes, where the highest yield strength (σYS = 320 MPa), ultimate tensile strength (σUTS = 397 MPa) and elongationto failure (δ = 14%) values were obtained at the second pass of PTCAP. However, with increasing number of PTCAPpasses to three, δ reached 4% and σYS and σUTS decreased by 31% and 11%, respectively. Findings from the neural basedpredictivemodels indicated that both RBF and MLP can be employed for accurately estimating the mechanical propertiesof the PTCAP-processed ZK60 Mg alloy.

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