首页|基于BP神经网络和Arrhenius本构模型的石墨烯/7075复合材料热变形行为

基于BP神经网络和Arrhenius本构模型的石墨烯/7075复合材料热变形行为

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在 653～713 K温度范围和 0。01～10 s-1 应变速率下，进行了w(GNP/7075Al)=0。5%增强7075铝基复合材料的热压缩试验，建立了BP神经网络和应变补偿Arrhenius模型，同时建立了复合材料的热加工图和动态再结晶体积分数预测模型，研究了复合材料的热变形行为，并确定了复合材料的热加工工艺参数。结果表明:BP神经网络模型得到的流变应力预测值与试验结果吻合较好，其相关系数最高为99。9983%，平均相对误差绝对值最小为0。5%，表明神经网络对w(GNP/7075Al)=0。5%复合材料的热变形行为具有较高的预测精度。w(GNP/7075Al)=0。5%复合材料最佳变形温度和应变速率分别为685～705 K和0。01～0。1 s-1。动态再结晶(DRX)倾向于在低应变速率和高变形温度下发生。数值模拟和热挤压试验表明，在挤压温度693 K、挤压速度1 mm/min的工艺参数下可以挤出表面质量良好的型材。
Thermal deformation behavior of graphene nanosheets reinforced 7075Al based on BP neural network and Arrhenius constitutive equation
At the temperature of 653-713 K and the strain rate of 0.01-10 s-1,Hot compression test of w(GNP/7075Al)=0.5%composite was applied,and strain compensated Arrhenius and BP neural network model were established.At the same time,the hot processing map and dynamic recrystallization volume fraction prediction model of the composite were established.The hot deformation behavior of the composite was studied,and the hot processing parameters of the composite were determined.The results show that the predicted values of flow stress obtained by BP neural network model are in good agreement with the experimental results.The highest correlation coefficient is 99.998 3%,and the minimum absolute value of average relative error is 0.5%.It shows that neural network has high prediction accuracy for the hot deformation behavior of w(GNP/7075Al)=0.5%composites.The optimum deformation temperature and strain rate of w(GNP/7075Al)=0.5%composite are 685-705 K and 0.01-0.1 s-1,respectively.Dynamic recrystallization(DRX)tends to occur at low strain rates and high deformation temperatures.Numerical simulation and hot extrusion test show that the profile with good surface quality can be extruded under the temperature of 693K and extrusion speed 1mm/min.

materials processing engineeringGNP/Al compositesthermal deformationconstitutive equationthermal processing maprecrystallization modelnumerical simulation

娄淑梅、李一明、李鑫、陈鹏、白雪峰、程宝嘉

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山东科技大学 智能装备学院,山东 泰安 271019

材料加工工程 石墨烯/铝复合材料 热变形 本构方程 热加工图 再结晶模型 数值模拟

国家自然科学基金山东省自然科学基金重点项目

51705295ZR2020KE013

2024

10.13229/j.cnki.jdxbgxb.20220756

吉林大学学报(工学版)
吉林大学

吉林大学学报(工学版)

CSTPCD北大核心
影响因子：0.792
ISSN：1671-5497
年,卷(期)：2024.54(5)
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