大跨度连续刚构桥服役期变形预测研究

李英华; 何军拥

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Study of Prediction of the Deformations of a Long-span Continious Concrete rigidity Bridge in Service Stage

首发时间：2022-04-15

LI Yinghua ^{1
2}
Li Yinghua, Phd,is served in Shixing County Administrative Service Center. Up to now, I has been the first author and co-author of over 18 peer-reviewed scintific articles in civil engineering and engineering mechanics journals.
HE Junyong ²

1、Shixing County Administrative Service Center
2、Guangdong College of Industry and Commerce

Abstract： The safety of bridges, especially long span bridges, in service has attracted more people\'s attention internationally. The variations in bridge deformation are keys to learn about the health of bridges in service. There are many models which have been set up to predict the deformation of bridges, but because of the shortage of the online data on the deformation of bridges, the models were seldom verified in practical engineering. In this paper, based on the verification with the four-year online monitoring data of deformations from a long-term health monitoring system on the prototype Bridge in Guangdong Province, China, a FEA model of the prototype Bridge was established to simulate the whole procedure, from construction to service, which can calculate the internal forces of the bridge accurately (important factors for calculating the shrinkage and creeping of concrete) in different stages of the bridge life. In the mean time, a BP artificial neural network (ANN) was set up to depict the monitoring data; one word, the BP ANN mode is used to predict the bridge deformations. The predictions of the deformations of the bridge provided by the FEM model and BP artificial neural network model have good agreement; they show that both FEM and BP ANN models are good enough for the prediction of deformations on the bridge, with the verification of the long term health monitoring data, which lays the foundation for further analysis of the bridges and damages.

keywords： Concrete bridges Deflection Numerical simulation Artificial neural network.

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大跨度连续刚构桥服役期变形预测研究

李英华 ¹
Li Yinghua, Phd,is served in Shixing County Administrative Service Center. Up to now, I has been the first author and co-author of over 18 peer-reviewed scintific articles in civil engineering and engineering mechanics journals.
何军拥 ²

1、始兴县行政服务中心
2、广东工贸职业技术学院学院科研管理处

摘要：在役桥梁尤其是大跨径桥梁的安全问题已引起国际社会越来越多的关注。桥梁变形的变化是了解在役桥梁健康状况的关键。目前已经建立了许多桥梁变形预测模型，但由于缺乏桥梁变形的在线数据，这些模型在实际工程中很少得到验证。本文采用原型桥长期健康监测系统的四年变形在线监测数据进行验证的基础上，建立了原型桥从施工到使用的全过程有限元模型，它可以准确计算桥梁寿命不同阶段的内力（计算混凝土收缩和徐变的重要因素）。同时，建立了BP人工神经网络（ANN）来描述监测数据；首先，采用BP神经网络模型对桥梁变形进行预测。有限元模型和BP神经网络模型对桥梁变形的预测结果吻合较好；结果表明，有限元法和BP神经网络模型都能很好地预测桥梁的变形，并通过长期健康监测数据的验证，为桥梁的进一步分析和损伤奠定了基础。

关键词：混凝土桥梁扰度数值模拟人工神经网络。

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LI Yinghua,HE Junyong. Study of Prediction of the Deformations of a Long-span Continious Concrete rigidity Bridge in Service Stage[EB/OL]. Beijing:Sciencepaper Online[2022-04-15]. https://www.paper.edu.cn/releasepaper/content/202204-202.

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论文编号	202204-202
论文题目	大跨度连续刚构桥服役期变形预测研究
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