A collaborative machine learning-optimization algorithm to improve the finite element model updating of civil engineering structures

Naranjo-Pérez, Javier; Infantes, María; Jiménez‐Alonso, Javier Fernando; Sáez, Andrés

doi:10.1016/j.engstruct.2020.111327

Cited by 27 publications

(12 citation statements)

References 41 publications

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“…Tran-Ngoc et al [132] used the particle swarm optimisation and genetic algorithm to update the Nam O arch bridge in Vietnam. More recently, Nguyen et al [133] investigated hybrid updating for building deterioration assessment and Naranjo-Pérez et al [134] proposed a collaborative algorithm combing optimisation algorithms alongside ANN.…”

Section: Computational Intelligence Methodsmentioning

confidence: 99%

Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

et al. 2022

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As important links in the transport infrastructure system, cable-stayed bridges are among the most popular candidates for implementing structural health monitoring (SHM) technology. The primary aim of SHM for these bridges is to ensure their structural integrity and satisfactory performance by monitoring their behaviour over time. Finite element (FE) model updating is a well-recognised approach for SHM purposes, as an accurate model serves as a baseline reference for damage detection and long-term monitoring efforts. One of the many challenges is the development of the initial FE model that can accurately reflect the dynamic characteristics and the overall behaviour of a bridge. Given the size, slenderness, use of long cables, and high levels of structural redundancy, precise initial models of long-span cable-stayed bridges are desirable to better facilitate the model updating process and to improve the accuracy of the final updated model. To date, very few studies offer in-depth discussions on the modelling approaches for cable-stayed bridges and the methods used for model updating. As such, this article presents the latest advances in finite element modelling and model updating methods that have been widely adopted for cable-stayed bridges, through a critical literature review of existing research work. An overview of current SHM research is presented first, followed by a comprehensive review of finite element modelling of cable-stayed bridges, including modelling approaches of the deck girder and cables. A general overview of model updating methods is then given before reviewing the model updating applications to cable-stayed bridges. Finally, an evaluation of all available methods and assessment for future research outlook are presented to summarise the research achievements and current limitations in this field.

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Section: Computational Intelligence Methodsmentioning

confidence: 99%

Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

et al. 2022

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“…The technical condition examination stage is crucial for the correctness of the technical condition assessment. At this stage, the key is to define the research area and the appropriate selection of measurement techniques [31][32][33][34][35][36][37][38][39][40]. Practice shows that for economic reasons, in-depth studies of all defects are not carried out and the research area is narrowed down to the most severe irregularities.…”

Section: Step Ii-technical Conditions Examinationmentioning

confidence: 99%

“…At this stage, it is necessary to verify the impact of the measured irregularities on the structure. This verification is usually based on computer-aided calculations [39,40]. In the case of the assessment of the technical condition of the load-carrying structures, the most-used calculation approach is based on the finite element method.…”

Section: Step Iii-technical Conditions Assessmentmentioning

confidence: 99%

The Assessment of the Technical Condition of Complex Fatigued Load-Carrying Structures

Misiewicz

Więckowski

2021

Applied Sciences

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This article presents a research approach that enables the assessment of the technical condition of complex technical objects. The main emphasis is placed on the load-carrying structures of these objects. The procedure applying experimental research techniques and computer computations using the finite element method is described. The combination of the two techniques assesses the technical condition of the structure. The described approach is presented using the example of two objects.

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“…Human beings are depending a lot on machines, robot and computers to mitigate their workload, and to make the tasks quick, easy and effective. In fact, artificial intelligence and machine learning have revolutionized the world because they provide users with intelligent systems and interfaces in many domains including civil engineering [1], [2], education [3]- [7], tourism [8]- [10], medicine [11]- [15] and also justice.…”

Section: Introductionmentioning

confidence: 99%

Application of machine learning algorithms for predicting outcomes of accident cases in Moroccan courts

Aissa

Ahajjam

Zeroual

et al. 2022

IJEECS

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<p><span>Due to the large number of legal cases, the processing of them by the courts is generally very slow. Among these cases, we find accidents cases, which require a great speed of judgment to compensate the victims of those accidents. To this end, we thought of exploiting the possibilities offered by machine learning in order to simulate the work of judges and contribute to speeding up the time of decision. Further, we applied different machine learning algorithms, such as linear regression, decision trees, and random forests. According to the results achieved, the Random Forest is the most perfect model for with the utmost accuracy about 91.05%</span></p>

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A collaborative machine learning-optimization algorithm to improve the finite element model updating of civil engineering structures

Cited by 27 publications

References 41 publications

Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

The Assessment of the Technical Condition of Complex Fatigued Load-Carrying Structures

Application of machine learning algorithms for predicting outcomes of accident cases in Moroccan courts

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