Integrated Framework for Assessment of Time-Variant Flood Fragility of Bridges Using Deep Learning Neural Networks

Khandel, Omid; Soliman, Mohamed

doi:10.1061/(asce)is.1943-555x.0000587

Cited by 23 publications

(11 citation statements)

References 56 publications

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“…Moreover, they are useful due to the possibility of introducing uncertainties in both capacity and demand while also providing the reliability of a structure over a range of loads expressed commonly by a lognormal distribution [13]. Flood-related fragility curves can also be used to assist quality control strategies before, during, and after a flood event [22]. Then, a lognormal adjustment is performed to obtain the coefficients of a lognormal distribution for fragility curve that fits the failure probabilities previously found.…”

Section: Fragility Analysismentioning

confidence: 99%

“…Nevertheless, the methodologies implemented in these research efforts are case-specific and time-consuming due to the use of finite element modeling for probabilistic analysis, which hinders the possibility of applying them at a network level scale, i.e., for a large portfolio of assets [21]. Some research contributions have introduced surrogate modeling techniques into the probabilistic framework for quantifying the failure probability of bridges under flood hazards to overcome this issue [22,23]. Yet, there is limited research on the fragility modeling of MAB subjected to flood and scour effects using surrogate modeling.…”

Section: Introductionmentioning

confidence: 99%

“…Flood fragility curves can be useful in aiding and providing valuable information that can be implemented into the bridge management decision-making process, thus reducing the bridge failure probability under flood-related events by applying maintenance and mitigation alternatives [22].…”

mentioning

confidence: 99%

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In-Plane Fragility and Parametric Analyses of Masonry Arch Bridges Exposed to Flood Hazard Using Surrogate Modeling Techniques

et al. 2022

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Natural disasters are unavoidable and can cause serious damage to bridges, which may lead to catastrophic losses, both human and economic. Therefore, the assessment of bridges exposed to these events is of paramount importance to identify possible mitigation needs. The objective of the present work is to present consistent tools that may allow us to obtain the failure probability of a masonry arch bridge under a flood event, leading to local scour. Surrogate models were implemented to ease the computational cost of the probabilistic analysis. Moreover, a stochastic parametric analysis based on the geotechnical properties of the soil components of masonry arch bridges located in Portugal was performed. The results show the failure mechanism of the masonry arch bridges when subjected to scour-induced settlements and the influence of soil density on the failure probability obtained for different flow discharge values and angles of attack. The presented methodology and derived fragility curves can be used to assess bridge performance under a flood event, thus providing useful information for bridge management and monitoring.

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Section: Fragility Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In-Plane Fragility and Parametric Analyses of Masonry Arch Bridges Exposed to Flood Hazard Using Surrogate Modeling Techniques

et al. 2022

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“…At present, a certain amount of work has been carried out on bridge assessment methods. Tra c load models, corrosion degradation models, and nite element models of existing reinforced concrete bridges have been studied [1][2][3][4][5][6][7][8][9], and machine learning methods have been applied to the construction of structural reliability assessment frameworks [10,11], but the amount of data required to build the models is greatly increased and does not apply to small and medium span bridges. Reliability studies on steel bridges have also been carried out gradually.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Reliability Assessment Method for Existing Railway Bridges Based on Bayesian Theory

Chen

Bing

et al. 2022

Advances in Civil Engineering

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The increase in traffic volume and train load poses new challenges to the reliability assessment of existing railway bridges. To construct a comprehensive assessment method for the safety and reliability of existing railway bridges, firstly, the risk factors of railway bridge structures are analyzed and the evaluation criteria are determined; secondly, based on the accident tree theory, a multilevel Bayesian network model with key points is established, and the ability of the Bayesian network bidirectional reasoning and sensitivity analysis is used to evaluate the structural safety; finally, the result was applied to the marina northern Songhua River extra-large bridge to verify the applicability of the comprehensive evaluation of the reliability of an existing railway bridge. This approach provides a theoretical basis for the maintenance and reinforcement of the Songhua River Bridge along the Bin-North Line.

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“…Lin et al [13] proposed an integrated analysis technique to study the performance of pile-supported bridges under scoured conditions. Finally, Khandel et al [14] developed a deep learning based integrated neural network for the assessment of different flood hazard intensities to simulate structural behavior of a bridge foundation under scour condition.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Progressive Scouring of a Pier-on-Bank

Chavan

Chen²,

Shanmugam³

et al. 2022

CivilEng

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Scour, caused by swiftly moving water, can remove alluvial sediment and soil, creating holes surrounding a bridge component and compromising the integrity of the bridge structure. Such problems can be equally critical for bridges with piers-on-bank bridges subjected to severe storm and flooding issues. In this paper, the Phillips Road Bridge over Toby Creek (35°18′28.2″ N 80°44′16.6″ W, Charlotte, NC, USA), a pier-on-bank bridge with critical/significant local scour holes and deep riverbank erosion cuts was selected as case study bridge. To investigate the scour effect on the bridge with pier-on-bank performance, the scoured area around a single pier is first quantified using a terrestrial laser and then modeled using nonlinear finite element (FE) analysis, where the local scour is modeled as progressive mass losses using the Element Removal (ER) technique. The FE results are compared to the design loading scenario and the results substantiated that the local scouring could cause large deflection and increased bending moment on the bridge pier.

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Integrated Framework for Assessment of Time-Variant Flood Fragility of Bridges Using Deep Learning Neural Networks

Cited by 23 publications

References 56 publications

In-Plane Fragility and Parametric Analyses of Masonry Arch Bridges Exposed to Flood Hazard Using Surrogate Modeling Techniques

In-Plane Fragility and Parametric Analyses of Masonry Arch Bridges Exposed to Flood Hazard Using Surrogate Modeling Techniques

A Comprehensive Reliability Assessment Method for Existing Railway Bridges Based on Bayesian Theory

Modeling of Progressive Scouring of a Pier-on-Bank

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