Parameter Identification of Viscoplastic Model Considering Dynamic Recrystallization
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摘要: 針對含動態再結晶粘塑性模型中的材料參數應用傳統的測試方法很難準確測定的問題,吸收了遺傳算法、增廣高斯-牛頓算法、Levenberg-Marquardt算法和可變多面體算法的優點,構造了一套混合的全局優化算法.以26Cr2Ni4MoV為例,以鐓粗實驗提供的實驗數據和剛塑性有限元模擬提供的數值解差值的l2范數的平方作為目標函數,應用構造的算法識別了該模型中的材料參數,計算結果和實驗結果符合良好.Abstract: The viscoplastic model considering dynamic recrystallization describes the coupling process of macroscopic deformation and microstructure evolution during hot working. It is difficult to measure the material parameters accurately by means of traditional testing methods. A hybrid global optimization algorithm is designed, which combines the strengths of genetic algorithm, Levenberg-Marquardt algorithm, augmented Gauss-Newton method and flexible tolerance method. The square sum of the norm of the difference between the experimental values obtained from upsetting experiment and the calculated values obtained from finite element simulation is defined as an objective function. Taking 26Cr2Ni4MoV as an example, the material parameters are identified by the designed algorithm. The comparison between simulated and experimental results shows that the calculated results are well with the experimental. This indicates that the constructed algorithm can effectively identify the material parameters of the model and the model can describe accurately the evolution of microstructure during hot working.
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Key words:
- viscoplastic model /
- global optimization /
- inverse analysis /
- finite element /
- parameter identification
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