Damage assessment of single-layer reticulated domes subjected to mainshock-aftershock sequences based on structural damage factor

Structures ◽  
2021 ◽  
Vol 34 ◽  
pp. 604-614
Author(s):  
He Huang ◽  
Yifan Wang ◽  
Yugang Li
2017 ◽  
Vol 17 (09) ◽  
pp. 1750108 ◽  
Author(s):  
X. D. Zhi ◽  
M. G. Stewart

In order to provide a better understanding of the dynamic behavior of single-layer reticulated domes subjected to explosive blast loads, a number of analyses are carried out on structures with different standoff distances ([Formula: see text]), explosive weights ([Formula: see text]), rise–span ratios ([Formula: see text] and other parameters. An equation for a structural damage factor is proposed to evaluate structural damage quantitatively. The damage states for single-layer reticulated domes are defined based on their structural dynamic performance and corresponding damage factors. Structural reliabilities for different standoff distances are obtained using the Monte-Carlo Analysis. A typical protective measure is bollards which are used to help ensure a minimum standoff distance. To illustrate the cost-effectiveness of such a protective measure, structural damage states and various losses, including direct and indirect economic loss and maimed and fatality loss, are considered for assessing the risk reduction, costs and benefits. It was found that the bollards significantly reduce the likelihood of structural progressive collapse or severe damage, and the optimal standoff distance can be determined.


Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1571 ◽  
Author(s):  
Jhonatan Camacho Navarro ◽  
Magda Ruiz ◽  
Rodolfo Villamizar ◽  
Luis Mujica ◽  
Jabid Quiroga

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 133
Author(s):  
Jérémie Sublime

The Tohoku tsunami was a devastating event that struck North-East Japan in 2011 and remained in the memory of people worldwide. The amount of devastation was so great that it took years to achieve a proper assessment of the economical and structural damage, with the consequences still being felt today. However, this tsunami was also one of the first observed from the sky by modern satellites and aircrafts, thus providing a unique opportunity to exploit these data and train artificial intelligence methods that could help to better handle the aftermath of similar disasters in the future. This paper provides a review of how artificial intelligence methods applied to case studies about the Tohoku tsunami have evolved since 2011. We focus on more than 15 studies that are compared and evaluated in terms of the data they require, the methods used, their degree of automation, their metric performances, and their strengths and weaknesses.


Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.


2004 ◽  
Vol 3 (2) ◽  
pp. 177-194 ◽  
Author(s):  
Lay Menn Khoo ◽  
P. Raju Mantena ◽  
Prakash Jadhav

2001 ◽  
Vol 17 (1) ◽  
pp. 89-112 ◽  
Author(s):  
Mauricio Sánchez-Silva ◽  
Libardo García

Potential damage assessment is fundamental for defining mitigation procedures and risk management strategies. Damage assessment involves the difficulties of defining, assessing, and modeling the variables involved, as well as handling uncertainty. Seismic damage estimation of structures does not only depend on the behavior of the structural system, but it involves other factors, which differ in nature. The paper presents a methodology for damage assessment of structures that combines systems theory, fuzzy logic, and neural networks. A feed-forward neural network supported on the systemic organization of information is used to assess the expected structural damage for a given earthquake. The methodology provides a very useful environment to consider the context of the building structure. The network has been trained using the damage observed in the recent earthquake that occurred in central Colombia. Several sets of structures were evaluated and the results compared to the damage observed. The model showed to be highly reliable and a good representation of experts' opinions. Computer software ERS-99 was developed and is currently being used for teaching and consulting purposes.


2017 ◽  
Vol 842 ◽  
pp. 012016
Author(s):  
Yun-Lai Zhou ◽  
Cao Hongyou ◽  
Ni Zhen ◽  
Magd Abdel Wahab

2012 ◽  
Vol 138 (12) ◽  
pp. 1505-1514 ◽  
Author(s):  
X. D. Zhi ◽  
G. B. Nie ◽  
F. Fan ◽  
S. Z. Shen

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