Article(id=1241686761538113635, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241686759470329942, articleNumber=null, orderNo=null, doi=10.16579/j.issn.1001.9669.2025.09.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745683200000, receivedDateStr=2025-04-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773970793374, onlineDateStr=2026-03-20, pubDate=1757865600000, pubDateStr=2025-09-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773970793374, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773970793374, creator=13701087609, updateTime=1773970793374, updator=13701087609, issue=Issue{id=1241686759470329942, tenantId=1146029695717560320, journalId=1227999626482147330, year='2025', volume='47', issue='9', pageStart='1', pageEnd='249', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773970792882, creator=13701087609, updateTime=1773970911747, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241687258093375901, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241686759470329942, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241687258093375902, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241686759470329942, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=54, endPage=61, ext={EN=ArticleExt(id=1241686761785577577, articleId=1241686761538113635, tenantId=1146029695717560320, journalId=1227999626482147330, language=EN, title=Layered inversion method for dynamic constitutive model of the 18CrNiMo7-6 alloy steel surface-modified layer, columnId=null, journalTitle=Journal of Mechanical Strength, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address the issue of characterizing static and dynamic mechanical behaviors of the surface-modified layer (SML) in 18CrNiMo7-6 alloy steel, a layered inversion method for the Johnson-Cook (J-C) constitutive model of SML was proposed. The SML was subjected to layered processing, and dynamic compression tests were conducted on cylindrical specimens with different SML thicknesses. Through progressive parameter inversion, the strain rate sensitivity coefficient C at each depth of the SML was determined. Combined with quasi-static thin plate tensile tests at different temperatures for each depth of the SML, the corresponding yield strength A, strain hardening coefficient B, strain hardening index n, and thermal softening exponent m were determined. Test results show that the SML of 18CrNiMo7-6 alloy steel exhibits significant strain hardening, strain rate strengthening, and temperature softening effects. Additionally, a correlation model between J-C constitutive parameters and dimensionless depth h/hb (distance to SML surface/SML effective depth) was established,providing support for subsequent composite strengthening simulations.

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ZHAO Minghao, E-mail:
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针对18CrNiMo7-6合金钢表面变质层的静、动态力学行为表征问题,提出表面变质层(Surface-Modified Layer,SML)Johnson-Cook(J-C)本构模型分层反演方法。将SML进行分层处理,开展了含有不同表面变质层厚度的圆柱试样动态压缩试验;通过递进式参数反演,分别确定了SML各层深处的应变率敏感系数C;结合SML各层深处不同温度准静态薄板拉伸试验,确定了其对应的屈服强度A、应变硬化系数B、应变硬化指数n及热软化指数m。试验结果表明,18CrNiMo7-6合金钢SML呈明显的应变硬化、应变率强化及温度软化效应。此外,建立了J-C本构模型参数与无量纲深度h/hb(到SML表面的距离/ SML有效深度)的关联模型,为后续的复合强化仿真提供支撑。

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赵明皞,男,1963年生,河南巩义人,博士,教授;主要研究方向为关键零部件的疲劳、断裂及可靠性;E-mail:
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徐广涛,男,1983年生,河南漯河人,博士,教授;主要研究方向为抗疲劳制造研究;E-mail:

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徐广涛,男,1983年生,河南漯河人,博士,教授;主要研究方向为抗疲劳制造研究;E-mail:

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figureFileBig=i583EG8pnTLCnV8XHirK+w==, tableContent=null), ArticleFig(id=1241810817918763630, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=EN, label=Tab.1, caption=

Yield strength, strain hardening coefficient and strain hardening index

, figureFileSmall=null, figureFileBig=null, tableContent=
层号
Number of layers
深度
Depth/mm
Ak/MPaBk/MPank
第1层
1st lager
0~<0.41 577.3347 098.670.94
第2层
2nd lager
0.4~<0.81 456.5232 859.630.89
第3层
3rd stlager
0.8~<1.21 358.8118 958.350.83
第4层
4th lager
1.2~1.61 287.494 315.640.62
), ArticleFig(id=1241810818057175665, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=CN, label=表1, caption=

屈服强度、应变硬化系数和应变硬化指数

, figureFileSmall=null, figureFileBig=null, tableContent=
层号
Number of layers
深度
Depth/mm
Ak/MPaBk/MPank
第1层
1st lager
0~<0.41 577.3347 098.670.94
第2层
2nd lager
0.4~<0.81 456.5232 859.630.89
第3层
3rd stlager
0.8~<1.21 358.8118 958.350.83
第4层
4th lager
1.2~1.61 287.494 315.640.62
), ArticleFig(id=1241810818153644659, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=EN, label=Tab.2, caption=

Values of strain rate sensitivity coefficient

, figureFileSmall=null, figureFileBig=null, tableContent=
层号Number of layers深度Depth/mm
第1层1st layer0~<0.40.010 9
第2层2nd layer0.4~<0.80.012 4
第3层3th layer0.8~<1.20.016 5
第4层4th layer1.2~<1.60.020 0
), ArticleFig(id=1241810818241725046, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=CN, label=表2, caption=

应变率敏感系数值

, figureFileSmall=null, figureFileBig=null, tableContent=
层号Number of layers深度Depth/mm
第1层1st layer0~<0.40.010 9
第2层2nd layer0.4~<0.80.012 4
第3层3th layer0.8~<1.20.016 5
第4层4th layer1.2~<1.60.020 0
), ArticleFig(id=1241810818350776956, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=EN, label=Tab.3, caption=

Values of thermal softening coefficient

, figureFileSmall=null, figureFileBig=null, tableContent=
层号Number of layers深度Depth/mmmk
第1层1st layer0~<0.41.13
第2层2nd layer0.4~<0.81.01
第3层3th layer0.8~<1.20.85
第4层4th layer1.2~<1.60.66
), ArticleFig(id=1241810818447245950, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241686761538113635, language=CN, label=表3, caption=

热软化指数值

, figureFileSmall=null, figureFileBig=null, tableContent=
层号Number of layers深度Depth/mmmk
第1层1st layer0~<0.41.13
第2层2nd layer0.4~<0.81.01
第3层3th layer0.8~<1.20.85
第4层4th layer1.2~<1.60.66
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18CrNiMo7-6合金钢表面变质层动态本构模型的分层反演方法
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徐广涛 1, 2, 3 , 李功 1, 2, 3 , 常晓安 1, 2, 3 , 韩光照 1, 2, 3 , 赵明皞 1, 2, 3
机械强度 | 2025,47(9): 54-61
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机械强度 | 2025, 47(9): 54-61
18CrNiMo7-6合金钢表面变质层动态本构模型的分层反演方法
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徐广涛1, 2, 3 , 李功1, 2, 3, 常晓安1, 2, 3, 韩光照1, 2, 3, 赵明皞1, 2, 3
作者信息
  • 1.郑州大学 机械与动力工程学院,郑州 450001
  • 2.抗疲劳制造产业技术研究院,郑州 450016
  • 3.河南省抗疲劳制造技术工程研究中心,郑州 450001
  • 徐广涛,男,1983年生,河南漯河人,博士,教授;主要研究方向为抗疲劳制造研究;E-mail:

通讯作者:

赵明皞,男,1963年生,河南巩义人,博士,教授;主要研究方向为关键零部件的疲劳、断裂及可靠性;E-mail:
Layered inversion method for dynamic constitutive model of the 18CrNiMo7-6 alloy steel surface-modified layer
Guangtao XU1, 2, 3 , Gong LI1, 2, 3, Xiao’an CHANG1, 2, 3, Guangzhao HAN1, 2, 3, Minghao ZHAO1, 2, 3
Affiliations
  • 1.School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450001, China
  • 2.Industrial Science & Technology Institute for Anti-fatigue Manufacturing, Zhengzhou 450016, China
  • 3.Henan Province Engineering Research Center of Anti-fatigue Manufacturing Technology, Zhengzhou 450001, China
出版时间: 2025-09-15 doi: 10.16579/j.issn.1001.9669.2025.09.004
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针对18CrNiMo7-6合金钢表面变质层的静、动态力学行为表征问题,提出表面变质层(Surface-Modified Layer,SML)Johnson-Cook(J-C)本构模型分层反演方法。将SML进行分层处理,开展了含有不同表面变质层厚度的圆柱试样动态压缩试验;通过递进式参数反演,分别确定了SML各层深处的应变率敏感系数C;结合SML各层深处不同温度准静态薄板拉伸试验,确定了其对应的屈服强度A、应变硬化系数B、应变硬化指数n及热软化指数m。试验结果表明,18CrNiMo7-6合金钢SML呈明显的应变硬化、应变率强化及温度软化效应。此外,建立了J-C本构模型参数与无量纲深度h/hb(到SML表面的距离/ SML有效深度)的关联模型,为后续的复合强化仿真提供支撑。

表面变质层  /  Johnson-Cook本构模型  /  渗碳  /  18CrNiMo7-6合金钢

To address the issue of characterizing static and dynamic mechanical behaviors of the surface-modified layer (SML) in 18CrNiMo7-6 alloy steel, a layered inversion method for the Johnson-Cook (J-C) constitutive model of SML was proposed. The SML was subjected to layered processing, and dynamic compression tests were conducted on cylindrical specimens with different SML thicknesses. Through progressive parameter inversion, the strain rate sensitivity coefficient C at each depth of the SML was determined. Combined with quasi-static thin plate tensile tests at different temperatures for each depth of the SML, the corresponding yield strength A, strain hardening coefficient B, strain hardening index n, and thermal softening exponent m were determined. Test results show that the SML of 18CrNiMo7-6 alloy steel exhibits significant strain hardening, strain rate strengthening, and temperature softening effects. Additionally, a correlation model between J-C constitutive parameters and dimensionless depth h/hb (distance to SML surface/SML effective depth) was established,providing support for subsequent composite strengthening simulations.

Surface-modified layer  /  Johnson-Cook constitutive model  /  Carburization  /  18CrNiMo7-6 alloy steel
徐广涛, 李功, 常晓安, 韩光照, 赵明皞. 18CrNiMo7-6合金钢表面变质层动态本构模型的分层反演方法. 机械强度, 2025 , 47 (9) : 54 -61 . DOI: 10.16579/j.issn.1001.9669.2025.09.004
Guangtao XU, Gong LI, Xiao’an CHANG, Guangzhao HAN, Minghao ZHAO. Layered inversion method for dynamic constitutive model of the 18CrNiMo7-6 alloy steel surface-modified layer[J]. Journal of Mechanical Strength, 2025 , 47 (9) : 54 -61 . DOI: 10.16579/j.issn.1001.9669.2025.09.004
18CrNiMo7-6合金钢具有优良的加工性能和抗疲劳性能,常用于传动轴、齿轮和其他关键部件制造。渗碳热处理后的18CrNiMo7-6合金钢在表层产生具有梯度微观结构和硬度的表面变质层(Surface-Modified Layer, SML),可实现整体材料强度与韧性两者兼顾[1-2]。表面变质层对提高材料的抗疲劳性能具有至关重要的作用[3],精确表征表面变质层的静、动态力学性能是在宏观力学层面揭示其抗疲劳机制的基础。
本构模型是构建材料本征特性与宏观变形响应的核心。学者提出不同的经验本构模型,如Johnson-Cook(J-C)[4]本构模型、Steinberg-Cochran-Guinan(SCG)[5]本构模型和Zerili-Armstrong(Z-A)本构模型[6]。其中,J-C本构模型形式简单,能够同时反映塑性应变、应变率和温度的影响,且参数易于解耦和确定,广泛应用于描述金属材料在高速率和高温下的动态力学行为。
近年来,学者针对基体材料J-C本构模型的构建与修正展开了系统性探索。ZHAO等[7]获得了EA4T的J-C本构模型和J-C损伤模型。ZOU等[8]、祝效华等[9]聚焦于求解方法,分别基于简化的三维车削有限元模型与自适应粒子群权重法,获得了304不锈钢和J55材料的J-C本构模型参数。王亮等[10]获得了考虑应变、应变率和温度耦合效应的修正J-C本构模型。目前,针对强化处理后表面变质层的本构模型的研究仍存在局限。徐广涛等[11]获得了18CrNiMo7-6合金钢SML的准静态本构参数。在此基础上,ZHANG等[12]对18CrNiMo7-6合金钢SML的应变率强化参数和热软化参数进行补充试验研究,然而并未结合SML梯度特性建立参数与深度的连续关联模型。
本研究对18CrNiMo7-6合金钢渗碳形成的SML进行分层处理,通过直接剥离SML和逐层减薄相结合的方法对其进行制样,开展准静态拉伸试验和动态压缩试验,确定了不同深度处的J-C本构模型参数。最后,建立了各参数沿渗碳方向的连续变化函数。
本研究采用J-C本构模型描述18CrNiMo7-6合金钢SML的弹塑性变形行为,即
式中,σεp分别为等效应力、等效塑性应变;ABn分别为屈服强度、应变硬化系数、应变硬化指数;C为应变率敏感系数;为无量纲应变率,且,其中,为试验应变率;为参考应变率;m为热软化指数;无量纲温度T=(T-Tr)/Tm-T,其中,T为试验温度;Tr为参考温度;Tm为材料熔化温度。
对于力学性能呈梯度变化的SML,假设将其分成k层,每层厚度相等,且每层都是均匀的。对制成的薄板拉伸试样(k)开展室温、高温拉伸试验,确定准静态参数和热软化参数,对包含不同SML厚度的圆柱形试样(K)开展动态压缩试验,确定应变率敏感系数。试样SML的分层示意图如图1所示。
基于上述分层方法,分别在室温和高温下对薄板试样进行准静态拉伸试验,得到不同温度下SML各层深处的应力-应变曲线。在室温和参考应变率下,表面变质层第k层试样的J-C本构模型为
式中,σkAkBknk分别为第k层试样的等效应力、屈服强度、应变硬化系数、应变硬化指数。
通过分析SML各层深处室温准静态拉伸试验的数据,确定SML各层深处J-C本构模型的准静态参数AkBknk
动态压缩试验在室温下进行,忽略温度项的影响。含有不同SML厚度试样的J-C动态本构模型为
式中,σKAKBKnKCK分别为试样K的等效应力、屈服强度、应变硬化系数、应变硬化指数和应变率敏感系数。
由于动态压缩试样为圆柱形,包含不同厚度的SML,故无法直接求出各层深处的应变率敏感系数CK。所以在冲击压缩过程中,假设试样变化均匀,试样K的受力分析如图2所示。
试样K的轴向压力等于试样K+1的轴向压力与第k*层SML的轴向压力之和,即
式中,FK为试样K的轴向压力;FK+1为试样K+1的轴向压力;为第k*层SML的轴向压力。由试样的轴向压力、轴向平均应力与截面积的关系,得
式中,σK+1分别为试样Kk*层SML和试样K+1的轴向平均应力;SKSK+1分别为试样Kk*层SML、试样K和试样K+1的横截面积。在式(6)中引入试样K的第k*层静态参数,且对应于得到的。因此,式(6)可改写为
SML各层深处的准静态参数已由室温准静态拉伸试验获得。根据得到的圆柱试样K和试样K+1在塑性变形阶段的数据,结合式(5),可得到SML各层深处的应变率敏感系数
不同温度下拉伸试样的SML力学性能发生变化,为精确预测18CrNiMo7-6合金钢SML高温力学行为,对J-C本构模型中的热软化指数m进行求解,则式(1)化简为
式中,mk为第k层试样的热软化指数。
选取SML各层深处的高温拉伸试验塑性变形阶段数据,得到表面变质层各层深处的热软化指数mk
本文采用的18CrNiMo7-6合金钢渗碳热处理工艺流程如图3所示。
采用维氏硬度计沿渗碳方向,对SML进行硬度梯度测定,每隔0.2 mm记录一次硬度值。测量结果如图4所示,表层硬度为713 HV,而芯部硬度稳定在460 HV左右。
碳含量分布具有互补误差函数(Erfc)分布的解析解[13]。碳含量的分布影响硬度的分布,SML的硬度亦可以用该类型函数表示[14],如式(9)所示。
式中,HV 0=451.40 HV;HV 1=137.70 HV;α=-1.26;β=3.30;HV substrate=477.02 HV;h/hb为无量纲深度;h为到变质层表面的距离;hb为表面变质层有效深度,hb= 1.6 mm。
对18CrNiMo7-6合金钢的表面变质层进行分层处理,在距表面0(SML1)、0.4(SML2)、0.8(SML3)、1.2(SML4) mm处,制备厚度为0.4 mm的准静态拉伸试样,试样尺寸如图5所示。
通过车削的方式对热处理后的圆棒进行逐层减薄,单边分别切除0、0.4、0.8、1.2、1.6 mm厚的表面变质层,得到含有不同表面变质层厚度的圆柱形试样(ϕ8.4、ϕ7.6、ϕ6.8、ϕ6.0、ϕ5.2 mm),压缩试样如图6所示。
采用配有高温箱的MTS809.25型伺服液压系统进行不同温度拉伸试验。设备的位移传感器精度为±0.5%。拉伸试验采用位移控制,拉伸速度设定为0.2 mm/min,试验温度为25、100、200、300 ℃。为避免试样在试验过程中受热不均,达到所需试验温度后,继续保温20 min。
采用Hopkinson压杆装置(JS-SHT/PB-50-4500/3000)进行不同应变率下的动态压缩试验。装置中应变片灵敏度为2 mV/V,撞击杆的发射速度不小于5 m/s,且误差控制在2%以内。在试验中选择1 500 s-1和2 500 s-1这2个应变率进行研究。在相同条件下,重复拉伸与压缩试验各3次,以保证试验的有效性。
表面变质层各层深处室温拉伸真应力-应变曲线如图7所示。由图7可知,18CrNiMo7-6合金钢渗碳热处理后沿着渗碳方向,屈服强度逐渐降低,韧性逐渐增大。
不同温度下拉伸真应力-应变曲线如图8所示。由图8可知,相同表面变质层深度的试样,随着温度的升高,表面变质层发生软化现象,屈服强度呈下降的趋势。
含有不同表面变质层厚度的圆柱试样动态压缩试验结果如图9所示。当应变率升高时,在相同的应变水平下,表面变质层的真应力随之增加,展现出应变率强化效应。同时,随着表面变质层厚度的增加,其屈服强度呈逐渐上升的趋势。表面变质层对18CrNiMo7-6合金钢的力学性能有着显著的影响。
利用蔡司聚焦离子束扫描电子显微镜(Scanning Electron Microscope, SEM)拍摄不同温度下拉伸试样的断口形貌(图10图11)。结果表明,渗碳热处理后的18CrNiMo7-6合金钢试样在不同温度水平下表现出不同的断裂特征。由图10图11可知,表层试样在室温下呈现脆性断裂,断口出现河流花样,并有撕裂边缘,与准解理断口形态相近;在300 ℃时,断口表面有许多小韧窝,呈韧性断裂特征。在室温条件下沿渗碳方向,试样断口形貌表现为从韧窝与撕裂棱的混合态逐步过渡为韧窝形核主导的断裂模式;至第4层试样时,断口出现大尺寸韧窝,且其周围伴随细小韧窝,最终呈典型的韧性断裂特征。
选取表面变质层各层深处准静态拉伸塑性均匀变化段的应力-应变数据,将式(2)转化为对数形式,即
求其斜率和截距,获得的18CrNiMo7-6合金钢渗碳热处理后表面变质层各层深处准静态参数AkBknk(无量纲值),如表1所示。
徐广涛等[15]测定的渗碳前18CrNiMo7-6合金钢的屈服强度为337 MPa,变质层最表层的屈服强度相较于渗碳前的屈服强度提升约3.5倍。表面变质层各层深处的屈服强度如图12所示,沿渗碳方向呈降低趋势。屈服强度与碳含量具有一定的关系,故用Erfc函数对其进行表征,即
式中,αA=0.11;βA=0.92。根据硬度梯度的变化规律,当超过渗碳有效深度时,硬度不发生变化,其力学性能也不再发生改变。h/hb≥1时,屈服强度亦为定值。取h/hb=1时对应的屈服强度,故Asubstrate=1 262.01 MPa。
表面变质层各层深处的应变硬化系数如图13所示,应变硬化系数逐渐减小。应变硬化系数也是表面变质层的表征参数之一,同样可采用Erfc函数对其进行表征,即
式中,αB=-1.12;βB=2.30。取h/hb=1时对应的函数值作为渗碳热处理后18CrNiMo7-6合金钢芯部的应变硬化系数,故Bsubstrate=2 497.87 MPa。
表面变质层各层深处的应变硬化指数变化如图14所示。应变硬化指数逐渐降低,对其沿渗碳方向采用Erfc函数进行表征,即
式中,αn=-2.27;βn=1.19。取h/hb=1时对应的函数值作为渗碳热处理后18CrNiMo7-6合金钢芯部的应变硬化指数,故nsubstrate=0.58。
表层试样(n=0.94)因较高的应变硬化能力及低延展性,显著限制了塑性变形,从而更易形成脆性断裂[图11(a)];而随着渗碳深度的增加,应变硬化指数n逐渐降低,材料塑性变形能力增强,韧性断裂逐渐占据主导。
根据含有不同表面变质层厚度的圆柱试样动态压缩试验塑性变形阶段数据,得到表面变质层各层深处的应变率敏感系数。将J-C本构模型变换为
将固定塑性变形阶段应变代入式(14)得到各层深处应变率敏感系数(无量纲值)。具体数值如表2所示。依据霍普金森动态压缩试验中的一维应力波假定和应变均匀性假定,以及本文中的均匀变形假定,不考虑变形不均匀性对应变率敏感系数C的影响。
表面变质层各层深处的应变率敏感系数如图15所示。随着渗碳深度的增加,18CrNiMo7-6合金钢表面变质层的应变率敏感系数逐渐增大。
沿渗碳方向对应变率敏感系数采用Erfc函数进行表征,如式(15)所示。变质层最表层相较于渗碳前18CrNiMo7-6合金钢的应变率敏感系数C下降约74%。
式中,αC=-1.128;βC=1.236。取h/hb=1时对应的函数值作为渗碳热处理后18CrNiMo7-6合金钢芯部的应变率敏感系数,故Csubstrate=0.023。
由于表面变质层各层深处的准静态参数均已求出,选取高温拉伸试验塑性段均匀变化的应力-应变数据,代入式(8),求出表面变质层各层深处的热软化指数mk(无量纲值),如表3所示。
表面变质层各层深处的热软化指数变化如图16所示。热软化指数沿渗碳方向逐渐降低,沿渗碳方向对其采用Erfc函数进行表征,如式(16)所示。最表层变质层相较于渗碳前18CrNiMo7-6合金钢的热软化指数m上升约51%。
式中,αm=-0.96;βm=0.98。取h/hb=1时对应的函数值作为渗碳热处理后18CrNiMo 7-6合金钢芯部的热软化指数,故msubstrate=0.56。
本文对渗碳热处理后的18CrNiMo7-6合金钢表面变质层进行分层,开展不同温度的拉伸试验和室温动态压缩试验,得出以下结论:
1)依据不同温度准静态拉伸和室温动态压缩真应力-应变曲线,表面变质层存在明显的热软化和应变率强化效应。室温下,试样断裂模式沿渗碳方向由准解理断裂向韧性断裂转变。最表层试样随着试验温度的升高,从脆性断裂转变为韧性断裂。
2)提出一种确定渗碳表面变质层J-C本构模型参数的分层反演方法,得到表面变质层J-C本构参数随深度变化的关系。变质层最表层屈服强度相较于渗碳前18CrNiMo7-6合金钢提升约3.5倍,变质层最表层热软化指数提升约51%,而应变率敏感系数C下降约74%。
3)表面变质层的屈服强度A、应变硬化系数B、应变硬化指数n、热软化指数m沿无量纲深度呈递减趋势,应变率敏感系数C呈递增趋势。
  • 国家自然科学基金重点项目(12432004)
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2025年第47卷第9期
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doi: 10.16579/j.issn.1001.9669.2025.09.004
  • 接收时间:2025-04-27
  • 首发时间:2026-03-20
  • 出版时间:2025-09-15
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  • 收稿日期:2025-04-27
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Key Program of National Natural Science Foundation of China(12432004)
国家自然科学基金重点项目(12432004)
作者信息
    1.郑州大学 机械与动力工程学院,郑州 450001
    2.抗疲劳制造产业技术研究院,郑州 450016
    3.河南省抗疲劳制造技术工程研究中心,郑州 450001

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赵明皞,男,1963年生,河南巩义人,博士,教授;主要研究方向为关键零部件的疲劳、断裂及可靠性;E-mail:
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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