Please wait a minute...
金属学报  2021, Vol. 57 Issue (8): 1073-1086    DOI: 10.11900/0412.1961.2020.00371
  研究论文 本期目录 | 过刊浏览 |
基于SH-CCT图的Q345钢焊接接头组织与硬度预测方法研究
胡龙1, 王义峰1(), 李索1, 张超华1,2, 邓德安1
1.重庆大学 材料科学与工程学院 重庆 400045
2.南昌大学 机电工程学院 南昌 330031
Study on Computational Prediction About Microstructure and Hardness of Q345 Steel Welded Joint Based on SH-CCT Diagram
HU Long1, WANG Yifeng1(), LI Suo1, ZHANG Chaohua1,2, DENG Dean1
1.College of Materials Science and Engineering, Chongqing University, Chongqing 400045, China
2.School of Mechanical and Electrical Engineering, Nanchang University, Nanchang 330031, China
全文: PDF(16492 KB)   HTML
摘要: 

以通用有限元软件ABAQUS为计算平台,采用Fortran语言编程,分别单独基于单个Q345钢模拟焊接热影响区连续冷却组织转变曲线(SH-CCT,峰值温度分别为900、1100和1300℃,简记为SH-CCT900、SH-CCT1100和SH-CCT1300)和同时基于3个不同温度下的SH-CCT图建立了4种组织与硬度计算模型,利用所建立的模型对Q345钢TIG重熔焊接接头的温度场、组织分布和硬度分布进行了计算,通过模拟结果与实验结果的比较,研究了采用不同的计算模型对焊接接头组织与硬度预测的适用性与准确性。采用单个SH-CCT图的组织计算结果仅在热影响区(HAZ)局部区域与实验结果吻合良好,其他区域有较大偏差。采用单个SH-CCT900图时,计算所得的部分相变区铁素体体积分数与实验结果的相对误差为7.7%;采用单个SH-CCT1100图时,计算所得的细晶区铁素体、贝氏体和马氏体体积分数与实验结果的相对误差分别为11.3%、17.3%和15.5%;采用单个SH-CCT1300图时,计算所得的粗晶区马氏体体积分数与实验结果的相对误差为29.6%。同时采用3个SH-CCT图时,组织计算结果在整个HAZ上与实验结果吻合良好。采用单个SH-CCT图的硬度计算结果仅在HAZ局部较窄区域与实验结果较为接近,而同时采用3个SH-CCT图的硬度计算结果在整个HAZ上都与实验结果较为吻合,其硬度绝对差值范围为0~14 HV。采用上述4种计算模型所得到的焊缝区组织与硬度计算结果都与实验结果有较大偏差,需进一步获取精确的焊缝区SH-CCT图。在实际焊接过程中,若只考虑热影响某一区域(如粗晶区)的相变情况,也可以仅采用对应的单一SH-CCT图来进行数值预测。

关键词 Q345钢组织与硬度计算SH-CCT图数值模拟    
Abstract

Q345 steel is a low-alloy high-strength steel that is widely used in production. As the solid-state phase transition of Q345 steel is very sensitive to temperature, the microstructure and hardness of joints fabricated with this steel are difficult to predict. Therefore, studying the welding metallurgy, residual welding stress, and welding deformation of Q345 steel joints is essential for improving the safety and service life of Q345 welding structures. In this study, the microstructure and distribution of hardness of a Q345-steel tungsten-inert-gas welded and re-melted joint were calculated using four models encoded in the general finite element software, ABAQUS, and FORTRAN language. Three models were based on only one of three welding continuous-cooling transformation curves of the simulated heat-affected zone (SH-CCT) of Q345 steel, with peak temperatures of 1300, 1100, and 900oC (hereafter denoted as SH-CCT1300, SH-CCT1100, and SH-CCT900, respectively). The final model was based on the associated diagram consisting of these curves SH-CCT diagram above. Comparing the simulation and experimental results, the capabilities and accuracies of the prediction methods based on the different models were investigated. The microstructural calculations of the single SH-CCT diagram agreed with the experimental results only in the local heat-affected zone (HAZ) and largely deviated in the other areas. In the model based on SH-CCT900, the relative error of the ferrite volume fraction in the inter-critically HAZ (ICHAZ) was 7.7%. In the model based on SH-CCT1100, the relative errors of the ferrite, bainite, and martensite volume fractions in the fine-grained HAZ (FGHAZ) were 11.3%, 17.3%, and 15.5%, respectively. In the model based on SH-CCT1300, the relative error of the martensite volume fraction in the coarse-grained HAZ (CGHAZ) was 29.6%. In contrast, the microstructural calculations of the associated SH-CCT diagram agreed with the experimental results over the whole HAZ. The results showed that models based on the single SH-CCT diagrams met the tested hardness only in several narrow areas of the HAZ, but the hardness computed by the model, based on the associated diagram, was consistent with the tested hardness, with absolute differences ranging from 0 to 14 HV. The calculated microstructure and hardness in the fusion zone (FZ) greatly deviated from the test results in all the four models, indicating that predictions in the FZ require an accurate SH-CCT diagram of the FZ. In practical welding processes, the corresponding single SH-CCT diagram can adequately predict the microstructure and hardness during the phase transition of one HAZ area (such as the CGHAZ).

Key wordsQ345 steel    simulation of microstructure and hardness    SH-CCT diagram    numerical simulation
收稿日期: 2020-09-18     
ZTFLH:  TG401  
基金资助:国家自然科学基金项目(51875063)
通讯作者: 王义峰     E-mail: wangyf0902@cqu.edu.cn
Corresponding author: WANG Yifeng     E-mail: wangyf0902@cqu.edu.cn
作者简介: 胡 龙,男,1994年生,博士生

引用本文:

胡龙, 王义峰, 李索, 张超华, 邓德安. 基于SH-CCT图的Q345钢焊接接头组织与硬度预测方法研究[J]. 金属学报, 2021, 57(8): 1073-1086.
Long HU, Yifeng WANG, Suo LI, Chaohua ZHANG, Dean DENG. Study on Computational Prediction About Microstructure and Hardness of Q345 Steel Welded Joint Based on SH-CCT Diagram. Acta Metall Sin, 2021, 57(8): 1073-1086.

链接本文:

https://www.ams.org.cn/CN/10.11900/0412.1961.2020.00371      或      https://www.ams.org.cn/CN/Y2021/V57/I8/1073

图1  焊接试件几何尺寸及热电偶布置示意图
图2  硬度测量位置及测量间距
图3  有限元模型示意图
图4  热-冶金顺序耦合关系
图5  热-冶金顺序耦合计算流程
图6  计算得到的铁素体和贝氏体的参数K、n
CaseSH-CCT900SH-CCT1100SH-CCT1300
1Yes××
2×Yes×
3××Yes
4YesYesYes
表 1  组织计算案例
图7  峰值温度在900℃与1100℃之间铁素体开始转变线的插值示意图
图8  焊接接头各区域微观组织的OM像(a) local welded joint (b) fusion zone (FZ)(c) coarse grained heat affected zone (CGHAZ) (d) fine grained heat affected zone (FGHAZ)(e) inter-critically heat affected zone (ICHAZ) (f) base metal (BM)
图9  焊接接头硬度分布
图10  移动热源温度场分布
图11  焊接接头区域划分的计算结果与实际结果对比图
图12  试板上表面距离焊趾不同位置处的热循环曲线计算结果与实验结果对比图
图13  焊接加热过程奥氏体体积分数(f)
图14  焊接接头组织计算结果
图15  距离焊缝中心不同位置的各相体积分数计算结果(a) Case 1 (b) Case 2 (c) Case 3 (d) Case 4
图16  焊接接头硬度分布(模拟)
图17  焊接接头距上表面1 mm处的硬度分布
1 Shi G, Shi Y J, Ban H Y. High-Strength Steel and Structure [M]. Beijing: China Architecture & Building Press, 2014: 1
1 施 刚, 石永久, 班慧勇. 高强度钢材钢结构 [M]. 北京: 中国建筑工业出版社, 2014: 1
2 Liu H J, Yan J C, Wei Y H. Welding Metallurgy and Weldability [M]. Beijing: China Machine Press, 2007: 1
2 刘会杰, 闫久春, 魏艳红. 焊接冶金与焊接性 [M]. 北京: 机械工业出版社, 2007: 1
3 Masao T. Determining the strength of welded joints—Knowing the characteristics of welding and utilizing inspection technology for quality control [J]. J. Jpn. Weld. Soc., 2012, 15: 21
3 豊田政男. 溶接継手の強度を決めるもの—溶接の特徴を知り、品質管理に検査技術を活かす [J]. 日本溶接学会誌, 2012, 15: 21
4 Huang J H. Principles of Welding Metallurgy [M]. Beijing: China Machine Press, 2015: 205
4 黄继华. 焊接冶金原理 [M]. 北京: 机械工业出版社, 2015: 205
5 Li Y J, Wang J. Analysis and Countermeasures of Celding Defects [M]. 2nd Ed., Beijing: Chemical Industry Press, 2014: 1
5 李亚江, 王 娟. 焊接缺陷分析与对策 [M], 第2版, 北京: 化学工业出版社, 2014: 1
6 Sista S, Yang Z, Debroy T. Three-dimensional monte carlo simulation of grain growth in the heat-affected zone of a 2.25Cr-1Mo steel weld [J]. Metall. Mater. Trans., 2000, 31B: 529
7 Wu M W, Xiong S M. Microstructure simulation of high pressure die cast magnesium alloy based on modified CA method [J]. Acta Metall. Sin., 2010, 46: 1534
7 吴孟武, 熊守美. 基于改进CA方法的压铸镁合金微观组织模拟 [J]. 金属学报, 2010, 46: 1534
8 Yu J, Xu Q Y, Cui K, et al. Numerical simulation of microstructure evolution based on a modified Ca method [J]. Acta Metall. Sin., 2007, 43: 731
8 于 靖, 许庆彦, 崔 锴等. 基于一种改进CA模型的微观组织模拟 [J]. 金属学报, 2007, 43: 731
9 Chen M J, Lv W, Huang Z X, et al. Application and development of microstructure simulation in welding research [J]. Electr. Weld. Mach., 2019, 49(2): 68
9 陈满骄, 吕 威, 黄作勋等. 微观组织模拟在焊接研究中的应用与发展 [J]. 电焊机, 2019, 49(2): 68
10 Zheng W J, He Y M, Yang J G, et al. Influence of the crystal orientation of epitaxial solidification on the linear instability dynamic during the solidification of welding pool [J]. J. Mech. Eng., 2018, 54(2): 62
10 郑文健, 贺艳明, 杨建国等. 焊接熔池凝固过程联生结晶晶体学取向对线性不稳定动力学的影响 [J]. 机械工程学报, 2018, 54(2): 62
11 Song K J. Modeling of microstructure in TIG welding heat affected zone and study on mechanical constitutive relation for TA15 alloy [D]. Harbin: Harbin Institute of Technology, 2014
11 宋奎晶. TA15钛合金TIG焊热影响区组织模拟及力学本构关系研究 [D]. 哈尔滨: 哈尔滨工业大学, 2014
12 Cheon J, Na S J. Prediction of welding residual stress with real-time phase transformation by CFD thermal analysis [J]. Int. J. Mech. Sci., 2017, 131-132: 37
13 Deng D A, Zhang Y B, Li S, et al. Influence of solid-state phase transformation on residual stress in P92 steel welded joint [J]. Acta Metall. Sin., 2016, 52: 394
13 邓德安, 张彦斌, 李 索等. 固态相变对P92钢焊接接头残余应力的影响 [J]. 金属学报, 2016, 52: 394
14 Deng D A, Ren S D, Li S, et al. Influence of multi-thermal cycle and constraint condition on residual stress in P92 steel weldment [J]. Acta Metall. Sin., 2017, 53: 1532
14 邓德安, 任森栋, 李 索等. 多重热循环和约束条件对P92钢焊接残余应力的影响 [J]. 金属学报, 2017, 53: 1532
15 Xavier C R, Delgado Junior H G, Castro J A, et al. Numerical predictions for the thermal history, microstructure and hardness distributions at the HAZ during welding of low alloy steels [J]. Mater. Res., 2016, 19: 520
16 Kang S H, Im Y T. Finite element investigation of multi-phase transformation within carburized carbon steel [J]. J. Mater. Process. Technol., 2007, 183: 241
17 Han L Z, Gu J F, Pan J S. Metallographic Atlas of SA508 Gr.3 Steel for Nuclear Power Heavy Forging [M]. Shanghai: Shanghai Jiao Tong University Press, 2016: 24
17 韩利战, 顾剑锋, 潘健生. 核电大型锻件SA508 Gr.3钢金相图谱 [M]. 上海: 上海交通大学出版社, 2016: 24
18 Eshraghi-Kakhki M, Kermanpur A, Golozar M A. Three-dimensional simulation of quenching process of plain carbon steel gears incorporating phase transformations [J]. Mater. Sci. Technol., 2012, 28: 197
19 Zhang Q, Xie J W, Gao Z Y, et al. A metallurgical phase transformation framework applied to SLM additive manufacturing processes [J]. Mater. Des., 2019, 166: 107618
20 Ronda J, Oliver G J. Consistent thermo-mechano-metallurgical model of welded steel with unified approach to derivation of phase evolution laws and transformation-induced plasticity [J]. Comput. Meth. Appl. Mech. Eng., 2000, 189: 361
21 Deng D A, Murakawa H. Finite element analysis of temperature field, microstructure and residual stress in multi-pass butt-welded 2.25Cr-1Mo steel pipes [J]. Comput. Mater. Sci., 2008, 43: 681
22 den Uijl N J, Nishibata H, Smith S, et al. Prediction of post weld hardness of advanced high strength steels for automotive application using a dedicated carbon equivalent number [J]. Weld. World, 2008, 52: 18
23 Zhou H, Zhang Q Y, Yi B, et al. Hardness prediction based on microstructure evolution and residual stress evaluation during high tensile thick plate butt welding [J]. Int. J. Naval Archit. Ocean Eng., 2020, 12: 146
24 Deng D A, Kiyoshima S. Influence of annealing temperature on calculation accuracy of welding residual stress in a SUS304 stainless steel joint [J]. Acta Metall. Sin., 2014, 50: 626
24 邓德安, Kiyoshima S. 退火温度对SUS304不锈钢焊接残余应力计算精度的影响 [J]. 金属学报, 2014, 50: 626
25 Yang S M, Tao W Q. Heat Transfer [M]. Beijing: Higher Education Press, 2006: 1
25 杨世铭, 陶文铨. 传热学 [M]. 北京: 高等教育出版社, 2006: 1
26 Goldak J, Chakravarti A, Bibby M. A new finite element model for welding heat sources [J]. Metall. Trans., 1984, 15B: 299
27 Lu S J, Wang H, Dai P Y, et al. Effect of creep on prediction accuracy and calculating efficiency of residual stress in post weld heat treatment [J]. Acta Metall. Sin., 2019, 55: 1581
27 逯世杰, 王 虎, 戴培元等. 蠕变对焊后热处理残余应力预测精度和计算效率的影响 [J]. 金属学报, 2019, 55: 1581
28 Watt D F, Coon L, Bibby M, et al. An algorithm for modelling microstructural development in weld heat-affected zones (part a) reaction kinetics [J]. Acta Metall., 1988, 36: 3029
29 Kang S H, Im Y T. Three-dimensional thermo-elastic-plastic finite element modeling of quenching process of plain-carbon steel in couple with phase transformation [J]. Int. J. Mech. Sci., 2007, 49: 423
30 Fukumoto M, Yoshizaki M, Imataka H, et al. Three-dimensional FEM analysis of helical gear subjected to the carburized quenching process [J]. J. Soc. Mat. Sci., Japan, 2001, 50: 598
30 福本学, 吉崎正敏, 今高秀樹等. ヘリカルギアの浸炭焼入れ3次元シミュレーション [J]. 材料, 2001, 50: 598
31 Deng D A. FEM prediction of welding residual stress and distortion in carbon steel considering phase transformation effects [J]. Mater. Des., 2009, 30: 359
32 Song Y P, Liu G Q, Liu J T. et al. Prediction of microstructure distribution in quenched jominy specimen by maynier mathematic model [J]. Heat Treat. Met., 2006, 31(3): 93
32 宋月鹏, 刘国权, 刘建涛等. 基于梅尼尔模型端淬试样组织分布的预报预测 [J]. 金属热处理, 2006, 31(3): 93
33 Song D L, Jiao S H. Validation of hardness prediction mathematic models [J].Mater. Mech. Eng., 2008, 32(003): 29
33 宋冬利,焦四海. 硬度预测模型的试验验证[J]. 机械工程材料, 2008, 32(003): 29
34 Kasuya T, Hashiba Y. Carbon equivalent to assess hardenability of steel and prediction of HAZ hardness distribution [J]. Shinnittetsu Giho, 2006, 385: 48
35 Zhang C H, Li S, Hu L, et al. Effects of pass arrangement on angular distortion, residual stresses and lamellar tearing tendency in thick-plate T-joints of low alloy steel [J]. J. Mater. Process. Technol., 2019, 274: 116293
[1] 李子晗, 忻建文, 肖笑, 王欢, 华学明, 吴东升. 热导型等离子弧焊电弧物理特性和熔池动态行为[J]. 金属学报, 2021, 57(5): 693-702.
[2] 杨勇, 赫全锋. 高熵合金中的晶格畸变[J]. 金属学报, 2021, 57(4): 385-392.
[3] 王富强, 刘伟, 王兆文. 铝电解槽中局部阴极电流增大对电解质-铝液两相流场的影响[J]. 金属学报, 2020, 56(7): 1047-1056.
[4] 刘继召, 黄鹤飞, 朱振博, 刘阿文, 李燕. 氙离子辐照后Hastelloy N合金的纳米硬度及其数值模拟[J]. 金属学报, 2020, 56(5): 753-759.
[5] 王波,沈诗怡,阮琰炜,程淑勇,彭望君,张捷宇. 冶金过程中的气液两相流模拟[J]. 金属学报, 2020, 56(4): 619-632.
[6] 许庆彦,杨聪,闫学伟,柳百成. 高温合金涡轮叶片定向凝固过程数值模拟研究进展[J]. 金属学报, 2019, 55(9): 1175-1184.
[7] 戴培元,胡兴,逯世杰,王义峰,邓德安. 尺寸因素对2D轴对称模型计算不锈钢管焊接残余应力精度的影响[J]. 金属学报, 2019, 55(8): 1058-1066.
[8] 逯世杰, 王虎, 戴培元, 邓德安. 蠕变对焊后热处理残余应力预测精度和计算效率的影响[J]. 金属学报, 2019, 55(12): 1581-1592.
[9] 张清东, 林潇, 刘吉阳, 胡树山. Q&P钢热处理过程有限元法数值模拟模型研究[J]. 金属学报, 2019, 55(12): 1569-1580.
[10] 李军, 夏明许, 胡侨丹, 李建国. 大型铸锭均质化问题及其新解[J]. 金属学报, 2018, 54(5): 773-788.
[11] 刘新华, 付华栋, 何兴群, 付新彤, 江燕青, 谢建新. Cu-Al复合材料连铸直接成形数值模拟研究[J]. 金属学报, 2018, 54(3): 470-484.
[12] 刘政, 陈志平, 陈涛. 坩埚尺寸和电磁频率对半固态A356铝合金浆料流动的影响[J]. 金属学报, 2018, 54(3): 435-442.
[13] 王锦程, 郭灿, 张琪, 唐赛, 李俊杰, 王志军. 原子尺度下凝固形核计算模拟研究的进展[J]. 金属学报, 2018, 54(2): 204-216.
[14] 沈厚发, 陈康欣, 柳百成. 钢锭铸造过程宏观偏析数值模拟[J]. 金属学报, 2018, 54(2): 151-160.
[15] 朱苗勇, 娄文涛, 王卫领. 炼钢与连铸过程数值模拟研究进展[J]. 金属学报, 2018, 54(2): 131-150.