首页|使用遗传算法增强GH4169高温合金BP-ANN本构模型的预测稳定性

使用遗传算法增强GH4169高温合金BP-ANN本构模型的预测稳定性

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为了更好地描述GH4169高温合金的塑性流动行为，利用Gleeble 1500热模拟试验机进行了不同变形温度和应变速率下的GH4169高温合金等温热压缩试验。基于真实应力-应变数据建立了GH4169高温合金反向传播人工神经网络(BP-ANN)本构模型，并进一步考察了本构模型的预测稳定性与模型参数之间的关系。预测结果发现，GH4169高温合金BP-ANN本构模型的输出对模型参数具有很强的依赖性。针对这一问题，本研究采用遗传算法(GA)优化BP-ANN本构模型的方法，建立GA-BP-ANN集成本构模型。优化后的结果表明，GH4169高温合金的GA-BP-ANN集成本构模型大幅增强了BP-ANN本构模型的预测稳定性，提升了BP-ANN本构模型的泛化能力。
Application of genetic algorithm to enhance the predictive stability of BP-ANN constitutive model for GH4169 superalloy
In order to better characterize the plastic flow behavior of GH4169 superalloy,isothermal compression tests of GH4169 superalloy at different temperatures and strain rates were carried out using Gleeble 1500 thermal simulator.The back propagation artificial neural network(BP-ANN)constitutive model of GH4169 superalloy was established based on true stress-strain data,and the relationship between the prediction stability of the constitutive model and the model parameters was further investigated.The prediction results show that the BP-ANN model outputs were highly influenced by the model parameters.To address this issue,genetic algorithm(GA)was used to optimize the BP-ANN constitutive model,and the GA-BP-ANN integrated constitutive model was presented.The optimization results show that the GA-BP-ANN integrated constitutive model greatly enhances the prediction stability and improves the generalization ability of GH4169 superalloy's BP-ANN constitutive model.

GH4169 superalloystress-strainbackpropagationartificial neural networkgenetic algorithm

郑德宇、夏玉峰、滕海灏、余盈燕

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Chongqing Key Laboratory of Advanced Mold Intelligent Manufacturing,School of Materials Science and Engineering,Chongqing University,Chongqing 400044,China

GH4169高温合金 应力-应变 反向传播 人工神经网络 遗传算法

National Key Research and Development Program,China中央高校基本科研业务费专项Chongqing Natural Science Foundation General Project,China

2022YFB37051032023CDJXY-020cstc2021jcyjmsxmX1085

2024

10.1007/s11771-024-5591-x

中南大学学报(英文版)
中南大学

中南大学学报(英文版)

CSTPCDEI
影响因子：0.47
ISSN：2095-2899
年,卷(期)：2024.31(3)
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