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Civil engineering structures play an important role in any country for improving the economy together with the social and environmental welfare. An unwanted failure might cause significant impacts at different levels for the structure owner and for users. Fatigue is one of the main degradation processes on steel structures that causes structural fa...
Contexts in source publication
Context 1
... comprehensive LCM is composed of different modules that work in an integrated way to minimize the life-cycle cost, and maximize the extended service life, etc. Figure 2.1 illustrates the general framework for LCM for deteriorating structures. It starts with analyzing the structure under investigation to determine the potential deteriorating mechanisms. ...
Context 2
... actions are generally employed to change the course of the structural deterioration. They can mainly be grouped in two categories namely preventive and corrective actions , see Figure 2.2. The goal of preventive maintenance interventions is either to stop or slow down the aging process which can help to extend the service life of a structure. ...
Context 3
... kind of maintenance can be planned or unplanned due to some unwanted accidents on the structure ( Barone and Frangopol, 2014). The effect of preventive and corrective maintenance actions on the structural performance is illustrated in Figure 2.3 in addition to the cumulative cost of maintenance. ...
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... degradation of structures can have different behavior depending on the governing failure mode. Figure 2.4 illustrates some of possible deterioration pat-terns. ...
Context 5
... many of the components in the civil engineering structures are covered with a protection layer, they may show a two-phase degradation process, see case 6 on Figure 2.4. ...
Context 6
... or Wöhler curves usually characterize the fatigue behavior of different materials (Susmel, 2009;Susmel et al., 2011). An illustration of S-N curve is provided in Figure 2.5. S-N curves show the relation between the level of stress ranges S and the associated number of cycles N to failure. ...
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... As the stress ranges are getting closer to the endurance limit, the number of cycles to failure increases, see Figure 2.5. The experiments are performed for some given test specimen and lab conditions. ...
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... modes of crack opening can be identified in literature such as tensile opening, sliding, and tearing. These types of cracks are illustrated in Figure 2.6. A Stress Intensity Factor (SIF) can be defined at the tip of the crack for each opening mode as K I , K II , and K III respectively. ...
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... it can be seen from Figure 2.7, crack propagation can be divided into three stages. ...
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... such cases the performance function should encompass both criteria in Equations 2.18 and 2.19. One solution is to resort to the R6 curve based rule, see Figure 2.8, which has been originally proposed by Harrison et al. (1977). The performance function G(L r , K r ) may have different closed-form expressions. ...
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... cost optimization is an important step within the LCM in which the optimum intervention times and types of maintenance and inspection interventions can be decided according to different objectives such as structural performance, cost, and service life ( Liu and Frangopol, 2005;Frangopol and Liu, 2007). Figure 2.9 shows the relationship between the expected life-cycle cost and structural performance. ...
Context 12
... comprehensive LCM is composed of different modules that work in an integrated way to minimize the life-cycle cost, and maximize the extended service life, etc. Figure 2.1 illustrates the general framework for LCM for deteriorating structures. It starts with analyzing the structure under investigation to determine the potential deteriorating mechanisms. ...
Context 13
... actions are generally employed to change the course of the structural deterioration. They can mainly be grouped in two categories namely preventive and corrective actions , see Figure 2.2. The goal of preventive maintenance interventions is either to stop or slow down the aging process which can help to extend the service life of a structure. ...
Context 14
... kind of maintenance can be planned or unplanned due to some unwanted accidents on the structure ( Barone and Frangopol, 2014). The effect of preventive and corrective maintenance actions on the structural performance is illustrated in Figure 2.3 in addition to the cumulative cost of maintenance. ...
Context 15
... degradation of structures can have different behavior depending on the governing failure mode. Figure 2.4 illustrates some of possible deterioration pat-terns. ...
Context 16
... many of the components in the civil engineering structures are covered with a protection layer, they may show a two-phase degradation process, see case 6 on Figure 2.4. ...
Context 17
... or Wöhler curves usually characterize the fatigue behavior of different materials (Susmel, 2009;Susmel et al., 2011). An illustration of S-N curve is provided in Figure 2.5. S-N curves show the relation between the level of stress ranges S and the associated number of cycles N to failure. ...
Context 18
... As the stress ranges are getting closer to the endurance limit, the number of cycles to failure increases, see Figure 2.5. The experiments are performed for some given test specimen and lab conditions. ...
Context 19
... modes of crack opening can be identified in literature such as tensile opening, sliding, and tearing. These types of cracks are illustrated in Figure 2.6. A Stress Intensity Factor (SIF) can be defined at the tip of the crack for each opening mode as K I , K II , and K III respectively. ...
Context 20
... it can be seen from Figure 2.7, crack propagation can be divided into three stages. ...
Context 21
... such cases the performance function should encompass both criteria in Equations 2.18 and 2.19. One solution is to resort to the R6 curve based rule, see Figure 2.8, which has been originally proposed by Harrison et al. (1977). The performance function G(L r , K r ) may have different closed-form expressions. ...
Context 22
... cost optimization is an important step within the LCM in which the optimum intervention times and types of maintenance and inspection interventions can be decided according to different objectives such as structural performance, cost, and service life ( Liu and Frangopol, 2005;Frangopol and Liu, 2007). Figure 2.9 shows the relationship between the expected life-cycle cost and structural performance. ...
Citations
Cette thèse porte sur le développement des méthodes de l'analyse de fiabilité dans le contexte des modèles numériques coûteux en temps de calcul. L'analyse de fiabilité consiste à calculer et à prédire la probabilité de défaillance d'une structure. Ceci est généralement assuré par les méthodes de simulation qui sont à ce jour un moyen incontournable vue leur capacité à traiter des problèmes complexes. Toutefois, ces méthodes souffrent des temps de calcul considérables engendrés par les multiples appels à des fonctions de performance coûteuses en temps de calcul et qui impliquent des modèles numériques onéreux. L'utilisation des méthodes d'apprentissage actif du méta-modèle de type krigeage, notamment les méthodes AK, est une des alternatives proposées pour diminuer les temps de calcul. Elle consiste à substituer la fonction de performance coûteuse à évaluer par un modèle mathématique simplifié dont les temps d'évaluation sont largement inférieurs par rapport au premier. Le méta-modèle est calibré à partir d'un nombre limité d'évaluations de la fonction de performance, appelé plan d'expériences. Ce dernier est constitué d'une façon adaptative dans le contexte de l'apprentissage actif. Cette thèse a pour objectif d'étendre l'utilisation des méthodes AK afin d'apporter des éléments de réponse au choix du type et de la configuration du méta-modèle en premier lieu et de proposer ensuite une nouvelle méthode pour le traitement des problèmes soumis à l'aléa spatial. La première contribution de la thèse propose donc de substituer la fonction de performance par un ensemble de méta-modèles afin de de s'affranchir du choix ad hoc du type et/ou de la configuration du méta-modèle. Une méthode dénommée AKE-MCS est proposée pour l'estimation de la probabilité de défaillance, où la mise en place d'un ensemble de méta-modèles est effectuée par l'agrégation pondérée des prédictions de trois krigeages ordinaires ayant différents noyaux. Cet ensemble est calibré itérativement en utilisant une nouvelle fonction d'apprentissage basée sur la probabilité de mauvais classement du point de prédiction par l'ensemble de méta-modèles. La seconde contribution porte sur l'analyse de fiabilité des structures sujettes à une variabilité spatiale aléatoire. Cette dernière peut générer de multiples lieux de défaillance qui sont généralement non pris en compte lors de l'estimation de la probabilité de défaillance à cause de l'hypothèse d'unicité du lieu de la défaillance. Ceci entraine généralement une mauvaise estimation de la probabilité de défaillance. La considération des multiples lieux de défaillance potentiels est ici effectuée par des méthodes de fiabilité système, par analogie entre la formulation mathématique des systèmes série et celle du problème abordé. Une extension de la méthode AK-SYS est proposée, dénommée AK-SYSs. Les lieux de défaillance potentiels ne sont pas sélectionnés à l'avance puisqu'ils sont méconnus, ils sont identifiés itérativement. La méthode proposée combine donc le processus d'enrichissement de la méthode AK-SYS avec une stratégie de recherche active des lieux de défaillance potentiels.
