scholarly journals Finite Element Modelling Tuned on Experimental Testing for the Structural Health Assessment of an Ancient Masonry Arch Bridge

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
G. Castellazzi ◽  
S. De Miranda ◽  
C. Mazzotti
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Health Assessment ◽  
Element Model ◽  
Actual State ◽  
Masonry Arch ◽  
Arch Bridge ◽  
Structural Health ◽  
Structural Health Assessment ◽  
Masonry Arch Bridge

This paper presents the structural health assessment of a railway ancient masonry arch bridge located in Bologna, Italy. A three-dimensional finite element model of the entire bridge, tuned on in situ experimental tests, has been used for the assessment. In particular, the finite element model has been employed to evaluate the structural health of the bridge both in its actual state and in the hypothesis of a structural strengthening intervention.

Structural Health Monitoring using deep learning with optimal finite element model generated data

2020 ◽  
Vol 145 ◽  
pp. 106972 ◽  
Author(s):  
Panagiotis Seventekidis ◽  
Dimitrios Giagopoulos ◽  
Alexandros Arailopoulos ◽  
Olga Markogiannaki
Keyword(s):  
Finite Element ◽  
Deep Learning ◽  
Structural Health Monitoring ◽  
Finite Element Model ◽  
Health Monitoring ◽  
Element Model ◽  
Structural Health

Research on the Shear Nails on the Arch Foot of an Oblique Cross Steel Box Arch Bridge

2013 ◽  
Vol 663 ◽  
pp. 49-54
Author(s):  
Xin Huang ◽  
Z.Z. Bai ◽  
De Wei Chen
Keyword(s):  
Finite Element ◽  
Shear Stress ◽  
Finite Element Model ◽  
Mechanical Performance ◽  
Maximum Shear Stress ◽  
Element Model ◽  
Bottom Up ◽  
Arch Bridge ◽  
Distribution Rules

In order to find the distribution rules on the shear nails on the steel-concrete composite segment of arch foot of an oblique cross steel box arch bridge, it established a space finite element model through the engineering of Wenzhou Weiwulu oblique cross steel box arch bridge, analyzing the maximum shear stress of the shear nails under normal using stage. The result shows that the welding nails in different position have a great difference in their shear stress. The welding nails which welded in a place that has a greater stiffness bear a bigger shear stress. So their mechanical performance of steel-concrete segment is better. In addition, the maximum shear stress becomes bigger from the bottom up to the top of the steel box.

Mechanical Performance and Spatial Stability under Live Load and Wind on Tied-Arch Bridge

2014 ◽  
Vol 501-504 ◽  
pp. 1238-1242
Author(s):  
Li Wang
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Safety Factor ◽  
Mechanical Performance ◽  
Influence Factors ◽  
Element Model ◽  
Structural Defects ◽  
Positive Contribution ◽  
Arch Bridge ◽  
Tied Arch Bridge

Finite element model of the background tied-arch bridge was established and analyzed. Meanwhile, mechanical performance and stability of it under several kinds of simulate structural defects and damages were studied. Some typical damage and influence factors were presented in the beginning. Then, based on the finite element model, the distribution of suspender force corresponding to the simulated defects and failure was calculated respectively. At last, the first class stability safety factor under the combination load was calculated as well as the second class nonlinear stability safety factor under structural arch rib defect. Results of above calculation imply that, suspender forces gained a stronger sensitivity to vertical defect than to transverse defect. While, short suspenders were believed to be more sensitive to lineation defect than long ones according to calculation results. Additionally, secondary inner force of short suspenders was much more intensive than in long ones. The result also tells that lateral wind did bad to stability. Lift wind, contrarily, made a little positive contribution to structures in-plane stability. Simulated structural defects were supposed to aggravate the second class stability safety factor under geometric nonlinear condition.

An inverse elastic method of crack identification based on sparse strain sensing sheet

2020 ◽  
pp. 147592172093951 ◽  
Author(s):  
Zeyu Xiong ◽  
Branko Glisic
Keyword(s):  
Finite Element ◽  
Structural Health Monitoring ◽  
Finite Element Model ◽  
Health Monitoring ◽  
Phase Field ◽  
Direct Contact ◽  
Crack Detection ◽  
Element Model ◽  
Crack Identification ◽  
Structural Health

Reliable damage detection over large areas of structures can be achieved by spatially quasi-continuous structural health monitoring enabled by two-dimensional sensing sheets. They contain dense arrays of short-gauge sensors, which increases the probability to have sensors in direct contact with damage (e.g. crack opening) and thus identify (i.e. detect, localize, and quantify) it at an early stage. This approach in damage identification is called direct sensing. Although the sensing sheet is a reliable and low-cost technology, the overall structural health monitoring system that is using it might become complex due to large number of sensors. Hence, intentional reduction in number of sensors might be desirable. In addition, malfunction of sensors can occur in real-life settings, which results in unintentional reduction in the number of functioning sensors. In both cases, reduction in the number of (functioning) sensors may lead to lack of performance of sensing sheet. Therefore, it is important to explore the performance of sparse arrays of sensors, in the cases where sensors are not necessarily in direct contact with damage (indirect sensing). The aim of this research is to create a method for optimizing the design of arrays of sensors, that is, to find the smallest number of sensors while maintaining a satisfactory reliability of crack detection and accuracy of damage localization and quantification. To achieve that goal, we first built a phase field finite element model of cracked structure verified by the analytical model to determine the crack existence (detection), and then we used the algorithm of inverse elastostatic problem combined with phase field finite element model to determine the crack length (quantification) and location (localization) by minimizing the difference between the sensor measurements and the phase field finite element model results. In addition, we experimentally validated the method by means of a reduced-scale laboratory test and assessed the accuracy and reliability of indirect sensing.

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