Dynamic Recrystallization Behavior of Grinding Surface Based on 40Cr High Temperature Dynamic Mechanical Properties

doi:10.12068/j.issn.1005-3026.2021.08.009

Abstract

Abstract: Through the split Hopkinson pressure bar experiment， the true stress-true strain curves of 40Cr alloy steel at high temperature and high strain rate are obtained. Then， the critical conditions for dynamic recrystallization of 40Cr are determined. An analytical method and experimental method are used to solve the temperature field and plastic strain field distribution of the grinding strengthening layer(GSL). The results show that the GSL has a large temperature and plastic strain gradient in the direction of grinding depth. The austenite transformation occurs within 150μm of the GSL. The maximum temperature of the ground surface can reach 1060℃. The severe plastic deformation can occur within 60μm of the ground subsurface， which reaches the critical condition of the dynamic recrystallization(DRX). With the larger grinding depth， the plastic strain of GSL increases， the DRX behavior is more sufficient， and the degree of microstructure refinement is higher.

Key words: split Hopkinson pressure bar experiment; grinding strengthening; microstructure; dynamic recrystallization; 40Cr

CLC Number:

TH164

YAO Yun-long， XIU Shi-chao， SUN Cong， HONG Yuan. Dynamic Recrystallization Behavior of Grinding Surface Based on 40Cr High Temperature Dynamic Mechanical Properties[J]. Journal of Northeastern University(Natural Science), 2021, 42(8): 1120-1126.

References

[1]Liu J，Suslov S，Ren Z C，et al.Microstructure evolution in Ti64 subjected to laser-assisted ultrasonic nanocrystal surface modification［J］. International Journal of Machine Tools Manufacture，2019，136:19-33.
[2]牛艺静，孙聪，庞刚，等.预应力时效性对磨削强化表面应力的影响［J］.东北大学学报(自然科学版)2020，41(4):546-550.(Niu Yi-jing，Sun Cong，Pang Gang，et al.Effect of pre-stress time-characteristics on grinding strengthened surface stress［J］.Journal of Northeastern University(Natural Science)，2020，41(4):546-550.)
[3]Sun C，Liu Z X，Lan D X，et al.Study on the influence of the grinding chatter on the workpieces microstructure transformation［J］.The International Journal of Advanced Manufacturing Technology，2018，96(9/10/11/12):3861-3879.
[4]Deng Y S，Xiu S C，Shi X L，et al.Study on the effect mechanisms of pre-stress on residual stress and surface roughness in PSHG［J］.The International Journal of Advanced Manufacturing Technology，2016，88(9/10/11/12):3243-3256.
[5]Humphreys F J，Hatherly M.Recrystallization and related annealing phenomena［M/OL］.［S.l.］:Elsevier，2012［2020-11-08］.https://doi.org/10.1016/B978-0-08-044164-1.X5000-2.
[6]Salonitis K.Grind hardening process［M/OL］.［S.l.］:Springer，2015［2020-11-08］.https://www.springer.com/gp/book/9783319193717.DOI:10.1007/978-3-319-19372-4.
[7]Chen L，Sun W Y，Lin J，et al.Modelling of constitutive relationship，dynamic recrystallization and grain size of 40Cr steel during hot deformation process［J］.Results in Physics，2019，12:784-792.
[8]Duan C Z，Zhang F Y，Qin S W，et al.Modeling of dynamic recrystallization in white layer in dry hard cutting by finite element—cellular automaton method［J］.Journal of Mechanical Science and Technology，2018，32(9):4299-4312.
[9]Wang Y S，Xiu S C，Zhang S N.Controlling grain sizes of 42CrMo steel by pre-stress hardening grinding［J/OL］.Materials，2019，12(19):3124［2020-11-10］.https://doi.org/10.3390/ma12193124.
[10]Wei Y J，Li Y Q，Zhu L C，et al.Evading the strength-ductility trade-off dilemma in steel through gradient hierarchical nanotwins［J/OL］.Nature Communications，2014［2020-11-10］.https://www.nature.com/articles/ncomms4580.
[11]Poliak E I，Jonas J J.A one-parameter approach to determining the critical conditions for the initiation of dynamic recrystallization［J］.Acta Materialia，1996，44(1):127-136.
[12]Zener C，Hollomon J H.Effect of strain rate upon plastic flow of steel［J］. Journal of Applied Physics，1944，15(1):22-32.
[13]Foeckerer T，Zaeh M F，Zhang O B.A three-dimensional analytical model to predict the thermo-metallurgical effects within the surface layer during grinding and grind-hardening［J］. International Journal of Heat Mass Transfer，2013，56(1/2):223-237.
[14]Venkataraman B，Sundararajan G.The sliding wear behavior of Al/SiC particulate composites—II.The characterization of subsurface deformation and correlation with wear behavior ［J］.Acta Materialia，1996，44(2):461-473.

[1]	WANG Hai-yan， WANG Jian-yu， TAO Ke-xin. Identification of Instantaneous Cutting Force Coefficients for Helical Milling of Carbon Fiber Composite Materials [J]. Journal of Northeastern University Natural Science, 2020, 41(10): 1432-1437.
[2]	ZHANG Yao-man， LI Wan-peng， YANG Ming-yu. Milling Force Characteristics of Titanium Alloy Parts Machined by Ball-end Milling Cutter [J]. Journal of Northeastern University Natural Science, 2020, 41(6): 852-857.
[3]	NIU Yi-jing， SUN Cong， PANG Gang， XIU Shi-chao. Effect of Pre-stress Time-Characteristics on Grinding Strengthened Surface Stress [J]. Journal of Northeastern University Natural Science, 2020, 41(4): 546-550.
[4]	SUN Cong， LI Qing-liang， XIU Shi-chao， LIU Hong-wei. Workpieces’ Surface Material Removal Mechanism of Disc Grinding [J]. Journal of Northeastern University Natural Science, 2020, 41(3): 393-398.
[5]	LI Bai-chun， WANG Zhen-yu， ZHANG Bin， WANG Wan-shan. Identification of Cutting Force Coefficients in Different Cutting Edges of Ball-End Milling Cutter [J]. Journal of Northeastern University Natural Science, 2019, 40(9): 1316-1322.
[6]	ZHANG Rong-chuang， LI Bai-chun， ZHANG Jing-qiang. Prediction of Cutting Forces in Gear Hobbing of Cylindrical Gears [J]. Journal of Northeastern University Natural Science, 2019, 40(7): 980-985.
[7]	WANG Bo， LI Bai-chun， YANG Jian-yu， WANG Wan-shan. Milling Force Coefcient Identication for Multi-axis and Ball-End Milling Cutter [J]. Journal of Northeastern University Natural Science, 2018, 39(11): 1630-1635.
[8]	WANG Lin， ZHANG Yong-jian， ZHONG Shi-sheng. The Representation of Process Family Information Model Based on UML and XML [J]. Journal of Northeastern University Natural Science, 2016, 37(6): 839-844.
[9]	LI Bai-chun， WANG Zhen-yu， WANG Guo-xun， WANG Wan-shan. Milling Force Coefficient Identification of Ball-End Milling Based on Instantaneous Milling Forces [J]. Journal of Northeastern University Natural Science, 2016, 37(5): 678-682.
[10]	SHENG Zhong-qi， XU Tao， XUAN Jia-yao， SONG Jun-you. Genetic Algorithm-based Service Module Configuration Design of CNC Machine Tools [J]. Journal of Northeastern University Natural Science, 2015, 36(6): 848-852.
[11]	ZHANG Rong-chuang， WANG Wan-shan， WANG Jun. Simulation Calculation of Undeformed Chip Thickness in Gear Hobbing [J]. Journal of Northeastern University Natural Science, 2015, 36(1): 95-99.
[12]	CHEN Yadong， MA Guoqiang， SHANG Dehao， WANG Wanshan. Biomechanical Analysis of Mandible Based on ABAQUS [J]. Journal of Northeastern University Natural Science, 2014, 35(3): 423-428.
[13]	ZHANG Kaifeng， YUAN Huiqun， NIE Peng. Prediction of Tool Wear Based on Generalized Dimensions and Optimized BP Neural Network [J]. Journal of Northeastern University, 2013, 34(9): 1292-1295.
[14]	XIU Shi-chao， LU Yue， SUN Cong， LI Qing-liang. Dynamic Thermal Mechanical Coupling Effect in Disc Grinding and Its Influence on Workpiece Material Removal Process [J]. Journal of Northeastern University(Natural Science), 2021, 42(3): 389-395.
[15]	PAN Wei-ping， FAN Zhi-ping， HUANG Min. Four-Block Layout Algorithm for Two-Dimensional Plate Shearring and Punching of Circular Parts [J]. Journal of Northeastern University(Natural Science), 2021, 42(11): 1650-1655.