scholarly journals Assessment of the Seismic Behaviour of a Retrofitted Old R.C. Highway Bridge Through PsD Testing

Author(s):  
Fabrizio Paolacci ◽  
Luigi Di Sarno ◽  
Pierre Pegon ◽  
Francisco Javier Molina ◽  
Martin Poljansek ◽  
...  
Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 90-92
Author(s):  
Kae Doki ◽  
Yuki Funabora ◽  
Shinji Doki

Every day we are seeing an increasing number of robots being employed in our day-to-day lives. They are working in factories, cleaning our houses and may soon be chauffeuring us around in vehicles. The affordability of drones too has come down and now it is conceivable for most anyone to own a sophisticated unmanned aerial vehicle (UAV). While fun to fly, these devices also represent powerful new tools for several industries. Anytime an aerial view is needed for a planning, surveillance or surveying, for example, a UAV can be deployed. Further still, equipping these vehicles with an array of sensors, for climate research or mapping, increases their capability even more. This gives companies, governments or researchers a cheap and safe way to collect vast amounts of data and complete tasks in remote or dangerous areas that were once impossible to reach. One area UAVs are proving to be particularly useful is infrastructure inspection. In countries all over the world large scale infrastructure projects like dams and bridges are ageing and in need of upkeep. Identifying which ones and exactly where they are in need of patching is a huge undertaking. Not only can this work be dangerous, requiring trained inspectors to climb these megaprojects, it is incredibly time consuming and costly. Enter the UAVs. With a fleet of specially equipped UAVs and a small team piloting them and interpreting the data they bring back the speed and safety of this work increases exponentially. The promise of UAVs to overturn the infrastructure inspection process is enticing, but there remain several obstacles to overcome. One is achieving the fine level of control and positioning required to navigate the robots around 3D structures for inspection. One can imagine that piloting a small UAV underneath a huge highway bridge without missing a single small crack is quite difficult, especially when the operators are safely on the ground hundreds of meters away. To do this knowing exactly where the vehicle is in space becomes a critical variable. The job can be made even easier if a flight plan based on set waypoints can be pre-programmed and followed autonomously by the UAV. It is exactly this problem that Dr Kae Doki from the Department of Electrical Engineering at Aichi Institute of Technology, and collaborators are focused on solving.


2021 ◽  
Vol 239 ◽  
pp. 112222
Author(s):  
Yong Yang ◽  
Shiqiang Feng ◽  
Yicong Xue ◽  
Yunlong Yu

Author(s):  
Xiaowei Cheng ◽  
Haoyou Zhang

AbstractUnder strong earthquakes, reinforced concrete (RC) walls in high-rise buildings, particularly in wall piers that form part of a coupled or core wall system, may experience coupled axial tension–flexure loading. In this study, a detailed finite element model was developed in VecTor2 to provide an effective tool for the further investigation of the seismic behaviour of RC walls subjected to axial tension and cyclic lateral loading. The model was verified using experimental data from recent RC wall tests under axial tension and cyclic lateral loading, and results showed that the model can accurately capture the overall response of RC walls. Additional analyses were conducted using the developed model to investigate the effect of key design parameters on the peak strength, ultimate deformation capacity and plastic hinge length of RC walls under axial tension and cyclic lateral loading. On the basis of the analysis results, useful information were provided when designing or assessing the seismic behaviour of RC slender walls under coupled axial tension–flexure loading.


Author(s):  
A. Sandoli ◽  
G. P. Lignola ◽  
B. Calderoni ◽  
A. Prota

AbstractA hybrid seismic fragility model for territorial-scale seismic vulnerability assessment of masonry buildings is developed and presented in this paper. The method combines expert-judgment and mechanical approaches to derive typological fragility curves for Italian residential masonry building stock. The first classifies Italian masonry buildings in five different typological classes as function of age of construction, structural typology, and seismic behaviour and damaging of buildings observed following the most severe earthquakes occurred in Italy. The second, based on numerical analyses results conducted on building prototypes, provides all the parameters necessary for developing fragility functions. Peak-Ground Acceleration (PGA) at Ultimate Limit State attainable by each building’s class has been chosen as an Intensity Measure to represent fragility curves: three types of curve have been developed, each referred to mean, maximum and minimum value of PGAs defined for each building class. To represent the expected damage scenario for increasing earthquake intensities, a correlation between PGAs and Mercalli-Cancani-Sieber macroseismic intensity scale has been used and the corresponding fragility curves developed. Results show that the proposed building’s classes are representative of the Italian masonry building stock and that fragility curves are effective for predicting both seismic vulnerability and expected damage scenarios for seismic-prone areas. Finally, the fragility curves have been compared with empirical curves obtained through a macroseismic approach on Italian masonry buildings available in literature, underlining the differences between the methods.


2021 ◽  
Vol 232 ◽  
pp. 111828
Author(s):  
Kai Heng ◽  
Ruiwen Li ◽  
Zhuoran Li ◽  
Hao Wu

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