.png){kind=icon}
返回
Vehicle-Bridge Interaction Modelling Using Precise 3D Road Surface Analysis
.png){kind=icon}
OA
AI
DOI：10.3390/s24020709.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM.
Keyword:
bridge-vehicle interaction
laser scanning
road roughness
numerical modelling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
.png){kind=icon}
Application of weigh-in-motion technologies for pavement and bridge response monitoring: State-of-the-art review动态称重技术在路面和桥梁响应监测中的应用: 最新技术综述
PREAI
分享收藏
Android Malware Detection Technology Based on Improved Bayesian Classification基于改进的贝叶斯分类的Android恶意软件检测技术
PREAI
分享收藏
查看更多内容