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Détail de l'auteur
Auteur Kirk Grimmelsman
Documents disponibles écrits par cet auteur
Affiner la rechercheMitigating epistemic uncertainty in structural identification: case study for a long-span steel arch bridge / Qin Pan in Journal of structural engineering, Vol. 137 N° 1 (Janvier 2011)
[article]
in Journal of structural engineering > Vol. 137 N° 1 (Janvier 2011) . - pp. 1-13
Titre : Mitigating epistemic uncertainty in structural identification: case study for a long-span steel arch bridge Type de document : texte imprimé Auteurs : Qin Pan, Auteur ; Kirk Grimmelsman, Auteur ; Franklin Moon, Auteur Année de publication : 2011 Article en page(s) : pp. 1-13 Note générale : Génie Civil Langues : Anglais (eng) Mots-clés : Bridge Identification Field test Finite-element modeling Uncertainty Index. décimale : 624 Constructions du génie civil et du bâtiment. Infrastructures. Ouvrages en terres. Fondations. Tunnels. Ponts et charpentes Résumé : Characterization of constructed civil-engineering systems through structural identification (St-Id) has gained increasing attention in recent years due to its potential to enable more effective infrastructure asset management and performance-based engineering. Although there have been recent advances that mitigate the challenges posed by aleatory (random) uncertainty, there are many remaining challenges associated with epistemic (bias) uncertainty that often have a more critical impact on the reliability of St-Id (especially with applications to constructed systems). The objective of this paper is to illustrate various sources of epistemic uncertainty and describe mitigation approaches by detailing the St-Id of a long-span steel arch bridge. This application includes a priori modeling, ambient vibration monitoring, data processing, feature extraction, and finite-element (FE) model correlation. Following a description of the St-Id, the impact of various modeling uncertainties on the calibrated FE model is evaluated by comparing different identification scenarios. Finally, a simple and rational approach to “truth testing” the identified model is developed and employed to determine its admissibility.
DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v137/i1/p1_s1?isAuthorized=no [article] Mitigating epistemic uncertainty in structural identification: case study for a long-span steel arch bridge [texte imprimé] / Qin Pan, Auteur ; Kirk Grimmelsman, Auteur ; Franklin Moon, Auteur . - 2011 . - pp. 1-13.
Génie Civil
Langues : Anglais (eng)
in Journal of structural engineering > Vol. 137 N° 1 (Janvier 2011) . - pp. 1-13
Mots-clés : Bridge Identification Field test Finite-element modeling Uncertainty Index. décimale : 624 Constructions du génie civil et du bâtiment. Infrastructures. Ouvrages en terres. Fondations. Tunnels. Ponts et charpentes Résumé : Characterization of constructed civil-engineering systems through structural identification (St-Id) has gained increasing attention in recent years due to its potential to enable more effective infrastructure asset management and performance-based engineering. Although there have been recent advances that mitigate the challenges posed by aleatory (random) uncertainty, there are many remaining challenges associated with epistemic (bias) uncertainty that often have a more critical impact on the reliability of St-Id (especially with applications to constructed systems). The objective of this paper is to illustrate various sources of epistemic uncertainty and describe mitigation approaches by detailing the St-Id of a long-span steel arch bridge. This application includes a priori modeling, ambient vibration monitoring, data processing, feature extraction, and finite-element (FE) model correlation. Following a description of the St-Id, the impact of various modeling uncertainties on the calibrated FE model is evaluated by comparing different identification scenarios. Finally, a simple and rational approach to “truth testing” the identified model is developed and employed to determine its admissibility.
DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v137/i1/p1_s1?isAuthorized=no