To improve wind resistance capacity of cable-braced steel portal frames,a double-braced portal frame was proposed by adding two pre-stressed knee braces to a cable-braced portal frame. To study the reasonable range of...To improve wind resistance capacity of cable-braced steel portal frames,a double-braced portal frame was proposed by adding two pre-stressed knee braces to a cable-braced portal frame. To study the reasonable range of application and method of cable parameter determination for this novel structure,the influences of load condition, span, base constraint, and cable parameters on structural performance were investigated by using the finite element code SAP2000. The results show that pre-stressed knee braces can effectively resist both uplifted and lateral wind loads,so this cablestayed and knee-braced steel portal frame is suitable for large wind.When the vertical load is comparable with the wind load,this novel type of portal frames is suitable for a medium span( 21-48 m). The cables in the cable brace can be determined by structural vertical stiffness,and the cables in the knee brace can be designed as the same as those in the cable-stayed part for the reason that their cross sectional area has only a weak effect on the structure. If no cable fails,the pretension variation of the cable does not affect the stiffness of the portal frame. The cable in the cable brace,working together with the cables in the knee braces,can ease uneven distribution of internal force,and their pretensions can be determined according to actual engineering projects.展开更多
This research paper describes an SEE （Structural Engineering Encounter） Lab project. The paper reports on the development of a single-story, single-bay portal frame model as part of the AIMS2 （attract, inspire, men...This research paper describes an SEE （Structural Engineering Encounter） Lab project. The paper reports on the development of a single-story, single-bay portal frame model as part of the AIMS2 （attract, inspire, mentor and support students） grant supported through the US DOE （Department of Education） summer research program at California State University, Northridge. This research effort is part of a comprehensive program to develop laboratory models of structures commonly encountered in civil engineering practice, which can serve the dual purpose of accomplishing engineering education and research in the areas of structural and earthquake engineering. The objective of the present study was to construct a physical model of the aforementioned frame to experimentally collect data due to the application of vertical and lateral loadings through instrumentation such as strain gages and an LVDT （linear variable differential transformer） displacement transducer, and also to make comparisons with theoretical and numerical predictions.展开更多
A number of bridges have collapsed around the world over the past years,with detrimental consequences on safety and traffic.To a large extend,such failures can be prevented by regular bridge inspections and maintenanc...A number of bridges have collapsed around the world over the past years,with detrimental consequences on safety and traffic.To a large extend,such failures can be prevented by regular bridge inspections and maintenance,tasks that fall in the general category of structural health monitoring(SHM).Those procedures are time and labor consuming,which partly accounts for their neglect.Computer vision and artificial intelligence(AI)methods have the potential to ease this burden,by fully or partially automating bridge monitoring.A critical step in this automation is the identification of a bridge’s structural components.In this work,we propose an extensible synthetic dataset for structural component semantic segmentation of portal frame bridges(PFBridge).We first create a 3 dimensional(3D)generic mesh representing the bridge geometry,while respecting a set of rules.The definition of new,or the extension of the existing rules can adjust the dataset to specific needs.We then add textures and other realistic elements to the model,and create an automatically annotated synthetic dataset.The synthetic dataset is used in order to train a deep semantic segmentation model to identify bridge components on bridge images.The amount of available real images is not sufficient to entirely train such a model,but is used to refined the model trained on the synthetic data.We evaluate the contribution of the dataset to semantic segmentation by training several segmentation models on almost 2,000 synthetic images and then finetuning with 88 real images.The results show an increase of 28%on the F1-score when the synthetic dataset is used.To demonstrate a potential use case,the model is integrated in a 3D point cloud capturing system,producing an annotated point cloud where each point is associated with a semantic category(structural component).Such a point cloud can then be used in order to facilitate the generation of a bridge’s digital twin.展开更多
基金Fund of Jiangsu Province Key Laboratory of Structure Engineering,China(No.ZD1302)
文摘To improve wind resistance capacity of cable-braced steel portal frames,a double-braced portal frame was proposed by adding two pre-stressed knee braces to a cable-braced portal frame. To study the reasonable range of application and method of cable parameter determination for this novel structure,the influences of load condition, span, base constraint, and cable parameters on structural performance were investigated by using the finite element code SAP2000. The results show that pre-stressed knee braces can effectively resist both uplifted and lateral wind loads,so this cablestayed and knee-braced steel portal frame is suitable for large wind.When the vertical load is comparable with the wind load,this novel type of portal frames is suitable for a medium span( 21-48 m). The cables in the cable brace can be determined by structural vertical stiffness,and the cables in the knee brace can be designed as the same as those in the cable-stayed part for the reason that their cross sectional area has only a weak effect on the structure. If no cable fails,the pretension variation of the cable does not affect the stiffness of the portal frame. The cable in the cable brace,working together with the cables in the knee braces,can ease uneven distribution of internal force,and their pretensions can be determined according to actual engineering projects.
文摘This research paper describes an SEE （Structural Engineering Encounter） Lab project. The paper reports on the development of a single-story, single-bay portal frame model as part of the AIMS2 （attract, inspire, mentor and support students） grant supported through the US DOE （Department of Education） summer research program at California State University, Northridge. This research effort is part of a comprehensive program to develop laboratory models of structures commonly encountered in civil engineering practice, which can serve the dual purpose of accomplishing engineering education and research in the areas of structural and earthquake engineering. The objective of the present study was to construct a physical model of the aforementioned frame to experimentally collect data due to the application of vertical and lateral loadings through instrumentation such as strain gages and an LVDT （linear variable differential transformer） displacement transducer, and also to make comparisons with theoretical and numerical predictions.
基金The project MIRAUAR received a Grant from the call for projects Ponts Connectés funded by the French State and led by Cerema which aims to improve bridge management by using the most recent techniques in terms of monitoring,data transfer and data processing.
文摘A number of bridges have collapsed around the world over the past years,with detrimental consequences on safety and traffic.To a large extend,such failures can be prevented by regular bridge inspections and maintenance,tasks that fall in the general category of structural health monitoring(SHM).Those procedures are time and labor consuming,which partly accounts for their neglect.Computer vision and artificial intelligence(AI)methods have the potential to ease this burden,by fully or partially automating bridge monitoring.A critical step in this automation is the identification of a bridge’s structural components.In this work,we propose an extensible synthetic dataset for structural component semantic segmentation of portal frame bridges(PFBridge).We first create a 3 dimensional(3D)generic mesh representing the bridge geometry,while respecting a set of rules.The definition of new,or the extension of the existing rules can adjust the dataset to specific needs.We then add textures and other realistic elements to the model,and create an automatically annotated synthetic dataset.The synthetic dataset is used in order to train a deep semantic segmentation model to identify bridge components on bridge images.The amount of available real images is not sufficient to entirely train such a model,but is used to refined the model trained on the synthetic data.We evaluate the contribution of the dataset to semantic segmentation by training several segmentation models on almost 2,000 synthetic images and then finetuning with 88 real images.The results show an increase of 28%on the F1-score when the synthetic dataset is used.To demonstrate a potential use case,the model is integrated in a 3D point cloud capturing system,producing an annotated point cloud where each point is associated with a semantic category(structural component).Such a point cloud can then be used in order to facilitate the generation of a bridge’s digital twin.
