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基于BP神经网络组合套筒的粘弹性分析

Viscoelastic analysis of the sleeve based on the BP neural network

中文摘要英文摘要

粘弹性材料有很强的非线性,基于广义Kelvin模型,给出了粘弹性材料的微分本构关系式。结合粘弹性组合套筒边界条件,本文推导了套筒在平面应变状态下的粘弹性响应的Laplace表达式。通过实例应用三层BP神经网络学习了正交设计试验的结果,经过训练的网络可以实现粘弹性材料测试集的映射。结果显示神经网络测试结果和数值解结果相近,二者误差最大不超过4.5%,说明神经网络经过训练可有效地解决粘弹性材料的非线性问题。

he viscoelastic material has a strong nonlinear, and its differential constitutive equation has been displayed based on the generalized Kelvin model.According to the boundary conditions of the viscoelastic sleeve,this paper deduces the Laplace equation of viscoelastic response in the plane strain.Training the results of orthogonal design test by three layer BP neural network by an example can safely draw a conclusion that the trained network can easily realize the mapping of viscoelastic material test set.It shows that the results of neural network test and numerical solution are almost equal with a maximum error less than 4.5 percent. This paper illustrate that the trained neural network can effectively solve the nonlinear problem of viscoelastic material.

高郁斌、李海滨

力学材料科学计算技术、计算机技术

粘弹性BP神经网络组合套筒正交设计

viscoelasticBP neural networksleeveorthogonal design

高郁斌,李海滨.基于BP神经网络组合套筒的粘弹性分析[EB/OL].(2013-09-09)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/201309-125.点此复制

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