基于机器学习算法的工程地质力学特性及CFRP加固技术研究

Sci. Program. Pub Date : 2022-01-07 DOI:10.1155/2022/2765327
Baoqi Yan, Nuoya Zhang, Ganggang Lu, Yue Hui
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引用次数: 1

摘要

我们完成了基于机器学习算法的预警与评估分析模块的设计。针对自然暴露条件下的预应力cfrp加固钢筋混凝土桥梁,建立了自然暴露条件下加筋部位长期预应力损失及cfrp -混凝土界面粘结行为的理论模型。分析深入揭示了D桥的技术和工程地质力学特征。同时,通过对D桥梁状态监测系统的一系列实验研究,提供了D桥梁状态监测系统的数据采集与传输、处理与控制,以及桥梁状态监测与评价软件。针对如何修复D桥的工程地质力学特性,提出了预应力碳纤维布加固技术。由钢筋混凝土(RC)制成的预应力碳纤维增强复合材料(CFRP)结构更好地利用了CFRP的高强特性而改变。强化了构件的应力分布,提高了构件的整体强度。它更多地得到土木工程和交通部门工程师的支持。然而,大多数预应力cfrp -钢筋混凝土结构都处于自然暴露环境中,自然暴露环境对预应力cfrp -钢筋混凝土构件长期力学性能的影响尚不清楚。本文主要利用对桥体的工程地质力学特征及加固技术的研究,使人们对其概念有深入的了解,为今后桥体的养护保护提供合理的使用方法和措施。本文研究了基于机器学习算法的工程地质力学特性,并将其应用于CFRP加固技术的研究,旨在促进其更好的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Engineering Geomechanics Characteristics and CFRP Reinforcement Technology Based on Machine Learning Algorithms
We have completed the design of an early warning and evaluation analysis module based on machine learning algorithms. Aiming at the prestressed CFRP-strengthened reinforced concrete bridges under natural exposure, we developed a theoretical model to analyze the long-term prestress loss of reinforced parts and the adhesion behavior of the CFRP-concrete interface under natural exposure conditions. The analysis deeply reveals the technical and engineering geomechanics characteristics of the D bridge. At the same time, through a series of experimental studies on the D bridge condition monitoring system, the data acquisition and transmission, processing and control of the D bridge condition monitoring system, and the bridge condition monitoring and evaluation software are provided. Regarding how to repair the engineering geomechanical characteristics of D bridge, we mentioned the prestressed CFRP reinforcement technology. The prestressed carbon fiber reinforced composite (CFRP) structure made of reinforced concrete (RC) makes better use of the high-strength characteristics of CFRP and changes. It strengthens the stress distribution of the components and improves the overall strength of the components. It is more supported by engineers in the civil engineering and transportation departments. However, most prestressed CFRP-reinforced RC structures are located in natural exposure environments, and the effect of natural exposure environments on the long-term mechanical properties of prestressed C FRP-reinforced RC components is still unclear. This article mainly uses the research on the engineering geomechanics characteristics and reinforcement technology of the bridge body, so that people have a deep understanding of its concept, and provides reasonable use methods and measures for the maintenance and protection of the bridge body in the future. This paper studies the characteristics of engineering geomechanics based on machine learning algorithms and applies them to the research of CFRP reinforcement technology, aiming to promote its better development.
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