scholarly journals Field Application of Cable Tension Estimation Technique Using the h-SI Method

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Myung-Hyun Noh ◽  
WooYoung Jung
Keyword(s):  
Tensile Force ◽  
Optimal Solution ◽  
Field Application ◽  
Theoretical Formulation ◽  
Long Span Bridges ◽  
Long Span ◽  
Identification Technique ◽  
Actual Field ◽  
Force Variation ◽  
Microgenetic Algorithm

This paper investigates field applicability of a new system identification technique of estimating tensile force for a cable of long span bridges. The newly proposed h-SI method using the combination of the sensitivity updating algorithm and the advanced hybrid microgenetic algorithm can allow not only avoiding the trap of local minimum at initial searching stage but also finding the optimal solution in terms of better numerical efficiency than existing methods. First, this paper overviews the procedure of tension estimation through a theoretical formulation. Secondly, the validity of the proposed technique is numerically examined using a set of dynamic data obtained from benchmark numerical samples considering the effect of sag extensibility and bending stiffness of a sag-cable system. Finally, the feasibility of the proposed method is investigated through actual field data extracted from a cable-stayed Seohae Bridge. The test results show that the existing methods require precise initial data in advance but the proposed method is not affected by such initial information. In particular, the proposed method can improve accuracy and convergence rate toward final values. Consequently, the proposed method can be more effective than existing methods in terms of characterizing the tensile force variation for cable structures.

scholarly journals Application of Laser Vibrometer to the Measurement and Control of Cable Tensile Forces in Cable-Stayed Bridges

2012 ◽  
Vol 8 (10) ◽  
pp. 810682 ◽  
Author(s):  
Cheol-Hwan Kim ◽  
Byung-Wan Jo ◽  
Jin-Taek Jun
Keyword(s):  
Tensile Force ◽  
Indirect Measurement ◽  
Laser Vibrometer ◽  
Data Logger ◽  
Long Span Bridges ◽  
Long Span ◽  
Tensile Forces ◽  
And Control ◽  
Measurement And Control

The tensile forces acting on the cable of long-span bridges are one of the most important factors since they reflect not only the structural stability of cables but also the overall quality of construction. Currently, indirect measurement using accelerometers attached to the surface of the cable is widely used to measure the natural frequency of cable. The frequency obtained from the accelerometer is converted to the tensile force of the cable. However, it sometimes requires many hazardous labors such as attaching the device on the surface of cable and wiring it with data logger, which could hinder the safety of workers during the erection of cables. In this study, a method using laser vibrometer is introduced to measure the tensile forces on cables at a distance. In addition, this study developed a unique postanalysis computer program that can calculate the tensile forces in real time. Compared with the values obtained from the accelerometers, the laser vibrometer system provided accurate and reliable matching.

Moving Load and Fatigue Analysis of a Long Span High Speed Railway Bridge

2012 ◽  
Vol 629 ◽  
pp. 403-408 ◽  
Author(s):  
Alessio Pipinato
Keyword(s):  
High Speed ◽  
Moving Load ◽  
Optimal Solution ◽  
Fatigue Analysis ◽  
Suspension Bridges ◽  
Railway Bridge ◽  
Structural Shape ◽  
High Speed Railway ◽  
Long Span Bridges ◽  
Long Span

Long span bridges, as cable-stayed and suspension bridges, have gained much popularity in recent decades for their structural shape, efficient use of materials and other optimal solution. A new phase is starting with main span lengths going over thousands of meter. As a matter of fact, small size substructures are required, the development of efficient construction techniques are growing on and faster progress in the FEM and design are evident. Ever since the dramatic collapse of the first examples of such long span structures, as the Tacoma Narrows Bridge in 1940, much attention has been given to the dynamic behavior of these structures. In this paper a moving load analysis performed on a cable stayed high speed railway bridge is presented together with a fatigue analysis of the cable stays, discussed according to the Italian code verification procedure.

Alternate Designs for Long Span Bridges

PCI Journal ◽  
1980 ◽  
Vol 25 (4) ◽  
pp. 48-58
Author(s):  
Felix Kulka
Keyword(s):  
Long Span Bridges ◽  
Long Span

Wind Buffeting in Time Domain Analysis of Long-Span Bridges using RM Bridge

2017 ◽  
Vol 109 (6) ◽  
pp. 3307-3317
Author(s):  
Afshin Hatami ◽  
Rakesh Pathak ◽  
Shri Bhide
Keyword(s):  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Long Span Bridges ◽  
Long Span

scholarly journals Wind-Induced Phenomena in Long-Span Cable-Supported Bridges: A Comparative Review of Wind Tunnel Tests and Computational Fluid Dynamics Modelling

2021 ◽  
Vol 11 (4) ◽  
pp. 1642
Author(s):  
Yuxiang Zhang ◽  
Philip Cardiff ◽  
Jennifer Keenahan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Tunnel ◽  
Careful Analysis ◽  
Wind Effects ◽  
Wind Tunnel Tests ◽  
Long Span Bridges ◽  
Long Span ◽  
Comparative Review ◽  
Dynamics Modelling

Engineers, architects, planners and designers must carefully consider the effects of wind in their work. Due to their slender and flexible nature, long-span bridges can often experience vibrations due to the wind, and so the careful analysis of wind effects is paramount. Traditionally, wind tunnel tests have been the preferred method of conducting bridge wind analysis. In recent times, owing to improved computational power, computational fluid dynamics simulations are coming to the fore as viable means of analysing wind effects on bridges. The focus of this paper is on long-span cable-supported bridges. Wind issues in long-span cable-supported bridges can include flutter, vortex-induced vibrations and rain–wind-induced vibrations. This paper presents a state-of-the-art review of research on the use of wind tunnel tests and computational fluid dynamics modelling of these wind issues on long-span bridges.

scholarly journals Damage Identification of Long-Span Bridges Using the Hybrid of Convolutional Neural Network and Long Short-Term Memory Network

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 180
Author(s):  
Lei Fu ◽  
Qizhi Tang ◽  
Peng Gao ◽  
Jingzhou Xin ◽  
Jianting Zhou
Keyword(s):  
Short Term Memory ◽  
Damage Identification ◽  
Identification Accuracy ◽  
Damage Localization ◽  
Short Term ◽  
Term Memory ◽  
Localization Accuracy ◽  
Long Span Bridges ◽  
Long Span ◽  
Long Short Term Memory

The shallow features extracted by the traditional artificial intelligence algorithm-based damage identification methods pose low sensitivity and ignore the timing characteristics of vibration signals. Thus, this study uses the high-dimensional feature extraction advantages of convolutional neural networks (CNNs) and the time series modeling capability of long short-term memory networks (LSTM) to identify damage to long-span bridges. Firstly, the features extracted by CNN and LSTM are fused as the input of the fully connected layer to train the CNN-LSTM model. After that, the trained CNN-LSTM model is employed for damage identification. Finally, a numerical example of a large-span suspension bridge was carried out to investigate the effectiveness of the proposed method. Furthermore, the performance of CNN-LSTM and CNN under different noise levels was compared to test the feasibility of application in practical engineering. The results demonstrate the following: (1) the combination of CNN and LSTM is satisfactory with 94% of the damage localization accuracy and only 8.0% of the average relative identification error (ARIE) of damage severity identification; (2) in comparison to the CNN, the CNN-LSTM results in superior identification accuracy; the damage localization accuracy is improved by 8.13%, while the decrement of ARIE of damage severity identification is 5.20%; and (3) the proposed method is capable of resisting the influence of environmental noise and acquires an acceptable recognition effect for multi-location damage; in a database with a lower signal-to-noise ratio of 3.33, the damage localization accuracy of the CNN-LSTM model is 67.06%, and the ARIE of the damage severity identification is 31%. This work provides an innovative idea for damage identification of long-span bridges and is conducive to promote follow-up studies regarding structural condition evaluation.

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