Evaluation of Interaction between Bridge Infrastructure Resilience Factors against Seismic Hazard

Román, Ángel Francisco Galaviz; Khan, Md Saiful Arif; Kabir, Golam; Billah, A. H. M. Muntasir; Dutta, Subhrajit

doi:10.3390/su141610277

Cited by 6 publications

(5 citation statements)

References 29 publications

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“…Bridge importance: Román et al (2022) and Khan et al (2022) identified the importance factor as one of the most important factors affecting bridge seismic resilience (Khan et al, 2022;Román et al, 2022b). The RPOA (2008) classifies bridges into three groups: strategic, important, and moderately important based on their role and traffic flow.…”

Section: Identification Of Preference Criteriamentioning

confidence: 99%

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Prioritizing Bridges for Seismic Resilience Enhancement: A Case Study of Algeria

Abdellaoui,

Badaoui,

Bensaibi

et al. 2024

J. Eng. Exact Sci.

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Algeria is located in an active seismic zone, making its bridges vulnerable to damage, especially older ones. Due to the importance of bridges in terms of safety, social, and economic factors, competent authorities must prepare for disasters, particularly earthquakes, by enhancing bridge resilience. However, due to the large number of bridges and lack of funding, it is not feasible to improve all bridges at once. This article proposes a model to determine priorities for enhancing bridge resilience to earthquakes based on expert opinions in three main steps. Step 1: Identification of key criteria, where design phase, bridge health, seismic zone, bridge importance, availability of alternative roads, and disaster insurance are defined as key criteria. Step 2: Calculation of criteria weights using the analytic hierarchy process (AHP) and integration of expert opinions using the Euclidean distance-based aggregation method (EDBAM). Step 3: Calculation of the priority index after evaluating criteria categories. The model was applied to six bridges, and their ranking was established based on the priority index. The model has proven its accuracy and ability to assist decision-makers in identifying priority bridges.

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Section: Identification Of Preference Criteriamentioning

confidence: 99%

“…Modern societies aim to strengthen their resilience to extreme events, recognizing that they cannot prevent all risks and threats, especially seismic ones, as they are inevitable (Román et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

Prioritizing Bridges for Seismic Resilience Enhancement: A Case Study of Algeria

Abdellaoui,

Badaoui,

Bensaibi

et al. 2024

J. Eng. Exact Sci.

View full text Add to dashboard Cite

show abstract

“…Among the components of traffic routes, bridges are the most impactful on a system's resilience. Additionally, bridges are potentially subject to a very large spectrum of degradation processes linked to their constructive materials, structural characteristics and exposure to external agents [1][2][3]. This is why an efficient approach to the management and maintenance of these structures has always been considered of paramount importance, with the United States leading the way since the 1970s.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Approach to Detect Failures in Bridges Based on the Coherence of Signals

et al. 2023

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Structural health monitoring of civil infrastructure, such as bridges and buildings, has become a trending topic in the last few years. The key factor is the technological push given by new technologies that permit the acquisition, storage, processing and visualisation of data in real time, thus assessing a structure’s health condition. However, data related to anomaly conditions are difficult to retrieve, and, by the time those conditions are met, in general, it is too late. For this reason, the problem becomes unsupervised, since no labelled data are available, and anomaly detection algorithms are usually adopted in this context. This research proposes a novel algorithm that transforms the intrinsically unsupervised problem into a supervised one for condition monitoring purposes. Considering a bridge equipped with N sensors, which measure static structural quantities (rotations of the piers) and environmental parameters, exploiting the relationships between different physical variables and determining how these relationships change over time can indicate the bridge’s health status. In particular, this algorithm involves the training of N models, each of them able to estimate the quantity measured via a sensor by using the others’ N−1 measurements. Hence, the system can be represented by the ensemble of the N models. In this way, for each sensor, it is possible to compare the real measurement with the predicted one and evaluate the residual between the two; this difference can be addressed as a symptom of changes in the structure with respect to the condition regarded as nominal. This approach is applied to a real test case, i.e., Candia Bridge in Italy, and it is compared with a state-of-the-art anomaly detector (namely an autoencoder) in order to validate its robustness.

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“…Mao et al [20] presented an assessment of concrete bridge piers with different reinforcement alternatives and conducted numerical studies to investigate the relative performance of different bridge piers under seismic loadings. In addition, Román et al [21] determined the relevant factors required to increase the seismic resilience of roadway bridges and bridge networks according to the crisp Decision-Making and Trial Evaluation Laboratory (DEMATEL) and rough DEMATEL methods.…”

Section: Introductionmentioning

confidence: 99%

Seismic Resilience Assessment of Curved Reinforced Concrete Bridge Piers through Seismic Fragility Curves Considering Short- and Long-Period Earthquakes

Uenaga,

Omidian,

George

et al. 2023

Sustainability

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Curved bridges are commonly used for logistics and emergencies in urban areas such as highway interchange bridges. These types of bridges have complicated dynamic behaviors and also are vulnerable to earthquakes, so their functionality is a critical parameter for decision makers. For this purpose, this study aims to evaluate the bridge seismic resilience under the effects of changes in deck radius (50, 100, 150 m, and infinity), pier height irregularity (Regular and Irregular), and incident seismic wave angle (0°, 45°, and 90°) under short- and long-period records. In the first step, fragility curves are calculated based on the incremental dynamic analysis and probabilistic seismic demand models. Finally, seismic resilience curves/surfaces are constructed and their interpolated values of the log-normal distribution function presented for assessing system resilience. It is found that when long-period records are applied in one given direction, the angle of incidence has the most significant effect on seismic resilience, and bridges are most vulnerable when the angle of incidence tends to 0°. The effect of deck radius on seismic resilience became more remarkable as the angle of incidence increased. Additionally, results indicate that the bridge vulnerability in long-period records is more significant than that under short-period records.

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Evaluation of Interaction between Bridge Infrastructure Resilience Factors against Seismic Hazard

Cited by 6 publications

References 29 publications

Prioritizing Bridges for Seismic Resilience Enhancement: A Case Study of Algeria

Prioritizing Bridges for Seismic Resilience Enhancement: A Case Study of Algeria

A Deep Learning Approach to Detect Failures in Bridges Based on the Coherence of Signals

Seismic Resilience Assessment of Curved Reinforced Concrete Bridge Piers through Seismic Fragility Curves Considering Short- and Long-Period Earthquakes

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