Article (Périodiques scientifiques)
Bayesian forces identification in cable networks with small bending stiffness
Piciucco, Davide; Foti, Francesco; Geuzaine, Margaux et al.
2024In Structural Health Monitoring
Peer reviewed vérifié par ORBi
 

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piciucco-et-al-2023-bayesian-forces-identification-in-cable-networks-with-small-bending-stiffness.pdf
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Détails



Mots-clés :
Bayesian regression; cable force; Cable network; identification; natural frequencies; structural health monitoring; vibrations; Bayesian; Bending stiffness; Cable forces; Cable networks; Cables structures; Crossing point; Force identification; Identification; Vibration; Biophysics; Mechanical Engineering
Résumé :
[en] The regular monitoring of cable forces is essential for ensuring the safety of cable structures both during construction and throughout their lifetime. This paper aims at developing a vibration-based identification procedure of the axial forces, bending stiffness, and, secondarily, the crossing point position of cable networks. A model constituted by two crossing stays having small bending stiffness and negligible sag effects is considered. The in-plane direct dynamic problem is solved both numerically and through a perturbation approach. The obtained results are compared to the outcomes of a finite element model for verification purposes. The theoretical studies are also supported by experimental tests performed on a real cable-stayed bridge (Haccourt bridge), which provide insights into the dynamics of the system showing that models of cables with small bending stiffness are more appropriate than taut string models. The inverse analysis based on non-linear Bayesian regression is developed and the closed-form asymptotic formulations are used to prove that the bending stiffness, the cable forces, and the crossing point position can be separately identified from a set of observed frequencies. The implemented procedure is then applied to the tested bridge as a proof of concept, showing that the proposed in-plane identification strategy provides satisfactory results.
Disciplines :
Ingénierie civile
Auteur, co-auteur :
Piciucco, Davide;  Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy
Foti, Francesco ;  Université de Liège - ULiège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil ; Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy
Geuzaine, Margaux  ;  Université de Liège - ULiège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil
Denoël, Vincent  ;  Université de Liège - ULiège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil
Langue du document :
Anglais
Titre :
Bayesian forces identification in cable networks with small bending stiffness
Date de publication/diffusion :
juillet 2024
Titre du périodique :
Structural Health Monitoring
ISSN :
1475-9217
eISSN :
1741-3168
Maison d'édition :
SAGE
Peer reviewed :
Peer reviewed vérifié par ORBi
Subventionnement (détails) :
This work was supported by the Service Public de Wallonie. Special thanks to T. Auguste for providing assistance with the collection of experimental data on the Haccourt bridge.
Disponible sur ORBi :
depuis le 29 décembre 2023

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