先进高强钢DP780板料温成形本构参数识别

王凯迪; 李迪; 冷杨松; 付秋涛; 徐家川; 姜宁

doi:10.13433/j.cnki.1003-8728.20200232

先进高强钢DP780板料温成形本构参数识别

doi: 10.13433/j.cnki.1003-8728.20200232

1.
山东理工大学交通与车辆工程学院，山东淄博　255049
2.
临沂科技职业学院汽修学院，山东临沂　276000

基金项目: 山东省自然科学基金项目（ZR2011EL037）

详细信息

作者简介:
王凯迪（1996−），硕士研究生，研究方向为车身轻量化材料研究，17865165067@163.com

通讯作者:
李迪，副教授，硕士生导师，hahali@sdut.edu.cn

中图分类号: TG142
计量
- 文章访问数: 249
- HTML全文浏览量: 85
- PDF下载量: 10
- 被引次数: 0
出版历程
- 收稿日期: 2020-03-19
- 网络出版日期: 2021-05-27
- 刊出日期: 2021-10-18

Identification of Constitutive Parameters for Sheet Warm Forming of Advanced High Strength Steel DP780

1.
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255049, Shandong, China
2.
School of Automobile Service, Linyi Vocational University of Science and Technology, Linyi 276000, Shandong, China

摘要

摘要: 先进高强双相钢板料温成形的本构模型参数识别，是提高塑性变形行为仿真准确度的关键。通过建立基于拉丁超立方抽样法和Spearman秩相关性分析法的本构模型参数敏感度分析方法，进而实现了参数敏感度的整体性分析。然后结合敏感度分析结果、DP780钢单向拉伸试验以及拉伸过程有限元模拟，构建了不同温度下的距离函数和材料本构参数之间的响应面模型。将本构参数识别问题归结为求解最小距离函数问题，利用遗传算法进行优化计算，最终获得了不同温度下的DP780钢井上胜郎本构模型参数。结果表明，建立的本构参数识别方法较好地满足本构模型精度要求。
- 先进高强度双相钢 /
- 温成形 /
- 本构模型 /
- 参数识别
Abstract: The parameters identification of constitutive model for the sheet warm forming of advanced high strength dual phase steel is the key to improve the simulation accuracy of plastic deformation behavior. By establishing the parameter sensitivity analysis method of constitutive model based on the Latin hypercube sampling method and Spearman rank correlation analysis method, the overall analysis of parameter sensitivity was realized. Then, combining the sensitivity analysis results, the unidirectional tensile test of DP780 steel and the finite element simulation of the tensile process, the response surface model between the distance function and the material parameters in the constitutive model under different temperatures was constructed. The parameter identification problem in the constitutive model was reduced to solving the minimum distance function problem. The optimization algorithm is used for the optimization calculation, and the parameters of the Inoue Sin constitutive model for of DP780 steel under the different temperatures were finally obtained. The results show that the parameter identification method in the constitutive model can meet the requirement of constitutive model accuracy.
- advanced high strength duplex steel /
- warm forming /
- constitutive model /
- parameter identification

HTML全文

图 1 应变率是3.33×10⁻³/s、不同温度下的应力-应变关系

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图 2 不同温度下，逆向识别参数后的本构模型预测值与试验值对比

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表 1 初始本构参数取值范围

温度/K	k	n	m
573	[53.76, 59.74]	[0.243, 0.297]	[−0.008, −0.006]
673	[59.70, 72.97]	[0.178, 0.218]	[−0.004, −0.006]
773	[63.30, 71.04]	[0.119, 0.145]	[0.039, 0.047]
873	[66.90,81.77]	[0.096, 0.118]	[0.127, 0.155]

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表 2 温度为873 K时，本构参数敏感度

样本数量	k	n	m
10	0.4303	0.9879	0.4909
50	0.3717	0.9863	0.4154
100	0.3753	0.9841	0.4262
200	0.3778	0.9841	0.4223
500	0.3769	0.9844	0.4226
1000	0.3768	0.9843	0.4224

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表 3 不同温度本构模型参数敏感度

温度/K	k	n	m
573	0.3605	0.7577	1
673	0.3586	0.7581	1
773	0.3592	0.7578	0.978
873	0.3778	0.9841	0.4223

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表 4 修正后本构参数取值范围

温度/K	k	n	m
573	[53.76, 59.74]	[0.257, 0.284]	[−0.01, −0.0035]
673	[59.70, 72.97]	[0.188, 0.208]	[−0.0075,−0.0025]
773	[63.30, 71.04]	[0.125, 0.138]	[0.041, 0.045]
873	[66.90, 81.77]	[0.105, 0.109]	[0.138, 0.148]

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表 5 正交试验表

温度/K	水平	k	n	m
573	−1	53.76	0.257	−0.01
	0	54.31	0.27	−0.007
	1	59.74	0.284	−0.0035
673	−1	59.70	0.188	−0.0075
	0	66.34	0.198	−0.005
	1	72.97	0.208	−0.0025
773	−1	63.30	0.125	0.041
	0	70.34	0.132	0.043
	1	71.04	0.138	0.045
873	−1	66.90	0.105	0.138
	0	74.34	0.107	0.141
	1	81.77	0.109	0.148

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表 6 遗传算法相关参数

温度/K	杂交概率	变异概率	种群规模	终止进化代数
573	0.85	0.12	60	90
673	0.85	0.12	60	90
773	0.85	0.12	60	90
873	0.8	0.1	50	80

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表 7 逆向识别的本构参数

温度/K	k	n	m	min(D(T))
573	0.269	−0.006	0.005	54.67
673	0.208	−0.007	0.009	68.64
773	0.138	0.041	0.005	71.42
873	0.105	0.138	0.007	76.74

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