| 基于Kriging代理模型的TP304不锈钢裂尖驱动力概率预测（英文） |
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| 引用本文： | 赵宽,李金平,王帮文,崔强. 基于Kriging代理模型的TP304不锈钢裂尖驱动力概率预测（英文）[J]. 稀有金属材料与工程, 2023, 52(11): 3741-3747 |
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| 作者姓名： | 赵宽 李金平 王帮文 崔强 |
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| 作者单位： | 西安科技大学 机械工程学院，陕西 西安 710054,长安大学 高速公路筑养装备与技术教育部工程研究中心，陕西 西安 710054,西安科技大学 机械工程学院，陕西 西安 710054,西安科技大学 机械工程学院，陕西 西安 710054 |
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| 基金项目： | 国家自然科学基金项目（52075434）, 高速公路筑养装备与技术教育部工程研究中心（长安大学）开放基金项目(300102253512) |
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| 摘 要： | 为了探究材料和载荷的随机性对TP304不锈钢裂尖驱动力的影响规律，通过将弹塑性有限元和Kriging代理模型相结合，实现裂尖驱动力的概率预测。为了提高有限元分析的效率，使用MATLAB对ABAQUS软件的前置处理和后置处理程序进行二次开发，实现随机样本的自动更改、批量计算和概率预测结果的自动分析。研究得到了随机因素作用下TP304不锈钢材料裂尖驱动力的统计分布规律，以及失效概率、失效概率密度函数、累计概率密度函数等概率特征，并对各随机因素的灵敏度进行了分析。最后，通过与Monte Carlo法对比分析了该方法的有效性和效率。结果表明，载荷和材料参数的随机性会显著影响TP304不锈钢裂纹尖端的驱动力，从而影响TP304不锈钢的失效概率，载荷和应变硬化指数对奥氏体TP304不锈钢材料裂尖驱动力的分散性影响最大。
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| 关 键 词： | 概率预测 裂尖驱动力 J积分 Kriging代理模型 |
| 收稿时间： | 2023-04-02 |
| 修稿时间： | 2023-06-05 |
Probability Prediction of Crack Driving Force of Crack Tips of TP304 Stainless Steel Based on Kriging Surrogate Model |
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| Zhao Kuan,Li Jinping,Wang Bangwen and Cui Qiang. Probability Prediction of Crack Driving Force of Crack Tips of TP304 Stainless Steel Based on Kriging Surrogate Model[J]. Rare Metal Materials and Engineering, 2023, 52(11): 3741-3747 |
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| Authors: | Zhao Kuan Li Jinping Wang Bangwen Cui Qiang |
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| Affiliation: | School of Mechanical Engineering, Xi''an University of Science and Technology, Xi''an 710054, China,Engineering Research Center of Expressway Construction & Maintenance Equipment and Technology of MOE, Chang''an University, Xi ''an 710054, China,School of Mechanical Engineering, Xi''an University of Science and Technology, Xi''an 710054, China,School of Mechanical Engineering, Xi''an University of Science and Technology, Xi''an 710054, China |
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| Abstract: | To explore the influence of randomness of materials and loads on the crack driving force of TP304 stainless steel, a probability prediction for crack driving force through the elastic-plastic finite element method (EPFEM) coupled with the Kriging surrogate model was proposed. To improve the efficiency of finite element analysis, MATLAB was used to further develop the pre-processing and post-processing procedures of ABAQUS software to realize the automatic change of random specimens, batch calculation, and automatic analysis of probability prediction results. The statistical distribution law of the crack driving force of TP304 stainless steel material under the action of random factors was obtained, as well as other probability characteristics, including failure probability, failure probability density function, cumulative probability density function, etc. The sensitivity of each random factor was analyzed. Finally, the effectiveness and efficiency of the proposed method were analyzed, compared with those of the Monte Carlo method. Results show that the randomness of load and material parameters can significantly influence the driving force of crack tips of TP304 stainless steel, thereby affecting the failure probability of TP304 stainless steel. The load and strain hardening exponent present the most obvious effect on the dispersion of crack driving force of austenitic TP304 stainless steel. |
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| Keywords: | probability prediction crack driving force J-integral Kriging surrogate model |
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