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566 results on '"Cheng, Xiaonong"'

1. Effects of LB/M Duplex Phase Heat Treatment on Microstructure and Mechanical Properties of Cold Working Die Steel DC53

Author

Yuan Zhizhong, Chen Lu, Zhang Bocheng, Liu Haiming, Niu Zongran , Wang Zhiyuan, Ju Yulin, Cheng Xiaonong

Subjects
cold working die steel； dc53； heat treatment； microstructure； mechanical property, Materials of engineering and construction. Mechanics of materials, TA401-492, Technology
Abstract

The effects of Quenching-Tempering-Austempering （QTA） duplex phase heat treatment process （Q 1 030 ℃， 30 min； T 520 ℃， 2 h； A 250 ℃， 3 h） at different prequenching temperatures on the microstructure， mechanical properties and the friction and wear properties of cold working die steel DC53 were investigated and the results were compared with those of the conventional Quenching-Tempering （QT） heat treatment process （Q 1 030 ℃， 30 min； T 520 ℃， 2 h）. The results show that the microstructure obtained by QT process is mainly tempered martensite and the microstructure mainly composing Lower Bainite/Martensite （LB/M） duplex phase can be resulted from the QTA process. The strength reduction due to the LB and the retained austenite （AR） can be partly offset by the grain refinement strengthening from the refinement of original austenite grain by duplex phases， and the impact toughness of DC53 can be greatly improved by this complex microstructure. Compared with the mechanical properties of the QT process， the hardness of the QTA at prequenching temperature 100 ℃ is only 1.4 HRC lower but the impact absorption energy is 2.44 times higher. Therefore， superior combination of strength and toughness can be obtained by the QTA process.

Published
2024
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18. Hot working processing and microstructure characterisation of as-cast high manganese TWIP steel.

Author

Mikombe, Forthan Umba, Yuan, Zhizhong, Peng, Ching-Tun, Luo, Rui, Cheng, Xiaonong, Chen, Leli, Duan, Xubin, and Maouche, Chanez

Subjects
MANGANESE steel, STRAIN rate, TWIN boundaries, CRYSTAL grain boundaries, HOT working
Abstract

The hot compression of the as-cast Fe-21Mn-0.7C–0.1Si twinning induced plasticity (TWIP) steel was investigated at the deformation temperature range of 950–1100 °C and strain rates of 0.01–5 s−1, using a GleebleTM thermo-mechanical simulator, to determine the hot deformation behaviour and analyse the recrystallisation mechanism. The results showed that the flow curves were characterised by yield-point-elongation (YPE) and dynamic recrystallisation (DRX) as the principal restoration mechanisms. The activation energy (Q) was calculated to be 394.975 KJ mol−1, which implies that the recrystallisation is sluggish in the whole range of the deformation conditions. Furthermore, the processing maps were generated according to the dynamic material model (DMM). The processing map was subdivided into different domains for the microstructural observations. The ideal hot deformation parameters of as-cast high Mn TWIP steel were obtained in the deformation condition range of 1087–1098 °C/10−1.2-10−0.17 s−1. Moreover, the microstructure analysis revealed that the DRX grains were twinned and nucleated through the bulging mechanism at the serrated grain boundaries, accompanied by twin boundaries migration created in the DRX grains by growth accidents, which contributed significantly to the growth of the DRX. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network

Author

LUO Rui, CAO Yun, QIU Yu, CUI Shugang, ZHOU Haotian, ZHOU Yiming, YUAN Fei, ZHANG Xiaopeipei, and CHENG Xiaonong

Subjects
spray forming, 7055 aluminum alloy, constitutive model, neural network, hot deformation, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Abstract

Gleeble physical simulation technique was employed to investigate the high-temperature flow stress characteristics of the studied spray forming 7055 aluminum alloy. Simultaneously, the Arrhenius constitutive model which couples the parameter of true strain and the BP artificial neural network constitutive model were contrastingly utilized to predict the flow stress behavior of the experimental alloy. The result shows that the flow stress of spray forming 7075 aluminum alloy is significantly affected by deformation parameter, which is negative correlated with deformation temperature and positively correlated with strain rate. Through the comparison of the two models, the average relative error of the Arrhenius constitutive model lies over 2%. And the error of the model tends to increase with the rising temperature. Moreover, the average absolute error and the average relative error reach the maximum at hot processing temperature (around 450 ℃). It is difficult to precisely predict the flow stress characteristics of the alloy. However, BP artificial neural network constitutive model has higher prediction accuracy, the average relative error δ value is only 0.813% and has higher temperature stability.

Published
2021
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