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Q235动态再结晶微观组织演化模型及其参数辨识 被引量:2

Microstructure Evolution Model for Q235 Under Dynamic Recrystallization and Its Parameter Identification
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摘要 建立了Q235动态再结晶微观组织演化的元胞自动机(CA)模型,提出了应用反分析原理来辨识模型参数的新方法。以实验流动应力曲线为依据,通过非线性回归的方法确定加工硬化和动态回复阶段的模型参数;将CA模型和自适应响应面(ARSM)优化技术相结合确定动态再结晶(DRX)的模型参数。模拟结果与实验结果良好一致,表明所提出的基于流动应力的反分析方法能够有效确定DRX模型参数,提高DRX微观组织演化的模拟精度。 A cellular automata(CA) model applying for Q235 was constructed and a new inverse analysis method was proposed to identify the model parameters.Based on the flow stress curve under hot deformation conditions,the nonlinear regression method was used to determine the model parameters in work hardening and dynamic recovery model;and the model parameters in DRX were identified by coupling CA model with an adaptive response surface method(ARSM).The good agreement between the simulation results and the experimental observations demonstrates the availability of the proposed method.
出处 《热加工工艺》 CSCD 北大核心 2010年第24期33-37,共5页 Hot Working Technology
基金 国家重点基础研究发展规划(973)项目(2006CB705401) 国家自然科学基金资助项目(50675133) 江苏省高校自然科学研究项目(10KJD46003)
关键词 动态再结晶 元胞自动机模型 响应面方法 参数辨识 dynamic recrystallization cellular automata method response surface method parameter identification
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参考文献14

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二级参考文献30

共引文献44

同被引文献37

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