A FE-based NN for finite element analysis

机译：用于有限元分析的FE基NN

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An architecture of Finite Elements based Neural Networks (FE-based NN) and its algorithms for modeling dynamic problems is proposed in this paper. An energy-function-based methodology is applied to combining Finite Element Method (FEM) with an ANN topology. The FE-based NN consists mainly of two node-variable layers and one element-subnet layer. Unknown inputs of the network are updated during the iterations using an inversion technique with imposed boundary conditions. A modified Newmark method is adopted for solving the dynamic problems. Results of the simulation on dynamics show promising results.

机译：提出了一种基于有限元的神经网络（Fe基NN）的架构及其用于建模动态问题的算法。基于能量函数的方法应用于与ANN拓扑结合的有限元方法（FEM）。 FE基NN主要由两个节点可变图层和一个元素 - 子网层组成。使用具有施加边界条件的反转技术在迭代期间更新网络的未知输入。采用改进的纽马克方法来解决动态问题。动态模拟结果显示了有希望的结果。

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《ASME Artificial Neural Networks in Engineering Conference》|1999年||共8页
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Guohe Xu; Guy Littlefair; Richard Penson; Rob Callan;
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A FE-based NN for finite element analysis

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