首页> 外文期刊>Bulletin of the Polytechnic Institute of Jassy, Constructions, Architechture Section >Neural Networks Used in Design of Reinforced Layer for Existing Slabs for Airport Rigid Runway Structures
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Neural Networks Used in Design of Reinforced Layer for Existing Slabs for Airport Rigid Runway Structures

机译:神经网络在机场刚性跑道结构现浇板加筋层设计中的应用

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摘要

In this paper a method of using neural networks for improving the computing method by increasing the accuracy in design of the reinforced concrete slabs from airport infrastructure is presented. The obtained results after the models developed with the method of finite element were used in order to create a neural networks simulating the function HR=f (He , css , K,?adm), for dual type of landing gear, for each loading, reaction modulus considered, to design the reinforced layer for existing cement concrete slabs. The use of neural networks for the interpolations of functions to dimension the slabs proved an increase of result accuracy compared to the reading of nomograms, previously carried out, as well as the possibility of computing the variable concrete slab thickness, other than the one considered for the nomograms.
机译:本文提出了一种利用神经网络通过提高机场基础设施中钢筋混凝土板的设计精度来改进计算方法的方法。使用有限元方法开发的模型获得的结果用于创建一个神经网络,用于模拟起落架的双重类型,每次加载的函数HR = f(He,css,K,?adm)考虑反应模量,以设计现有水泥混凝土板的增强层。与以前进行的列线图的读取相比,使用神经网络对函数进行插值来确定板的尺寸证明了结果精度的提高,并且可以计算可变的混凝土板厚度(考虑的除外)。诺模图。

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