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Enregistrement W146801596

Development of Deterioration Models for Bridge Decks Using System Reliability Analysis

2013· dissertation· en· W146801596 sur OpenAlexaboutno aff
Farzad Ghodoosipoor

Notice bibliographique

RevueSpectrum Research Repository (Concordia University) · 2013
Typedissertation
Langueen
DomaineEngineering
ThématiqueConcrete Corrosion and Durability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésReliability (semiconductor)Bridge (graph theory)Reliability engineeringEngineeringProcess (computing)Structural systemDeckStructural engineeringComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Generally, in the existing Bridge Management Systems(BMS) deterioration is modeled based on the visual inspections where the corresponding condition states are assigned to individual elements. In this case, the limited attention is given to the correlation between bridge elements from structural perspective. In this process, the impact of the history of deterioration on the reliability of a structure is disregarded which may lead to inappropriate conclusions. The Improved estimate of service life of a bridge deck may help decision makers enhance the intervention planning and optimize the bridge life cycle costs. A reliability-based deterioration model can potentially be an appropriate replacement for the existing procedures.
\nThe objective of this thesis is to evaluate the system reliability of conventional bridges designed based on the existing codes. According to the methodology developed in this thesis, the predicted element-level structural conditions for different time intervals are applied in the non-linear Finite Element model of a bridge superstructure and the system reliability indices are estimated for different time intervals. The resulting degradation curve could be calibrated and updated based on the outcomes of the visual inspections. Also, the reliability of innovative bridges that use non-conventional materials or structural forms such as Steel-Free Deck System has been evaluated by applying the newly developed method. The available deterioration models for conventional superstructuresare not applicable for the innovative bridge systems. Since there is no established deterioration model available for these innovative structures, it is difficult to predict the reliability of such bridges at different time intervals. The method developedhere adopts the reliability theory and establishes deterioration models for conventional and innovative bridges based on their failure mechanisms.
\nThis method has been applied in simply-supported traditional reinforced-concrete bridge superstructures designed according to the Canadian Highway Bridge Design Code (CHBDC-S6), and in an innovative structure with a Steel-Free Deck System, namely the Crowchild Bridge, in Calgary, Canada, as case studies. As an example to show the application of such developed deterioration curve, the developed model has been adopted in an old superstructure in Montreal. The results obtained from the newly developed model and bridge engineering groups’ estimations are found to be in accordance. Based on the reliability estimates, the conventional bridges designed based on the new code are found to be in a good condition during the initial stages of their service life,but their condition degrades faster once corrosion in steel reinforcements is initiated and spalling of concrete becomes evident. In case of the Steel-Free Deck, there is a low probability of failure at the end of the 75 years of its service life. It is found that the element-level assessment of a concrete deck is a conservative approach, since the interaction between the structural elements results in considerably higher reliability index and lower probability of failure. This thesis demonstrates how the proposed system reliability-based evaluation method can be adopted in determining the structural condition of a bridge which represents an important step forward in Bridge Management Systems. The system reliability deterioration model can be easily integrated to the existing Bridge Management Systems (BMS) by replacing the existing condition index by the reliability index or adding it to the assessing process as an additional parameter.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,665
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,281
Écart entre enseignants0,235 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2013
Routes d'admission1
Résumé présentoui

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