Estudio experimental y simulación del comportamiento inelástico de paneles compuestos usando redes neuronales artificiales

IF 0.4 4区 工程技术 Q4 CONSTRUCTION & BUILDING TECHNOLOGY
Wilmer Barreto, R. Picón
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引用次数: 0

Abstract

The analysis of complex structures, such as panels composed of various materials, is difficult to model due to the variability in the mechanical properties of the materials. The foregoing, coupled with non-linearity in the behavior of materials, makes the application of traditional numerical methods difficult and highly demanding in computational time. The present work introduces a less conventional technique like the artificial neural networks (ANN) for the modeling of the permanent deformation and damages in a compose slab subjected to flexion. 400 ANN models were trained and verified, which were able to model the non-linearity of the structural element, successfully reproduce the damages due to cracking and buckling of the panel, as well as reproduce the global permanent deformation of the element.
利用人工神经网络对复合板非弹性行为进行实验研究和仿真
由于材料力学性能的可变性,对复杂结构(如由各种材料组成的面板)的分析很难建模。上述情况,加上材料行为的非线性,使得传统数值方法的应用变得困难,并且在计算时间上要求很高。目前的工作介绍了一种不太传统的技术,如人工神经网络(ANN),用于对屈曲复合板的永久变形和损伤进行建模。对400个ANN模型进行了训练和验证,这些模型能够对结构元件的非线性进行建模,成功地再现了由于面板开裂和屈曲造成的损伤,以及再现了元件的整体永久变形。
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来源期刊
Informes De La Construccion
Informes De La Construccion 工程技术-结构与建筑技术
CiteScore
0.90
自引率
16.70%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Founded in 1948 by the Instituto Técnico de la Construcción y del Cemento, Informes de la Construcción is a scientific journal issued quarterly. Its articles cover fields such as architecture, engineering, public works, environment, building services, rehabilitation, construction systems, testing techniques, results of research on building components and systems and so forth. Journal"s readership includes architects, engineers and construction companies, as well as researchers and professionals engaging in building construction and public works.
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