Tema #3 - TDC
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Appello del 16 giugno 2020
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In recent years, there has been an increasing interest in permanent observation of the dynamic behaviour of bridges for longterm
monitoring purpose. This is due not only to the ageing of a lot of structures, but also for dealing with the increasing
complexity of new bridges. The long-term monitoring of bridges produces a huge quantity of data that need to be effectively
processed. For this purpose, there has been a growing interest on the application of soft computing methods. In particular,
this work deals with the applicability of Bayesian neural networks for the identification of damage of a cable-stayed bridge.
The selected structure is a real bridge proposed as benchmark problem by the Asian-Pacific Network of Centers for Research
in Smart Structure Technology (ANCRiSST). They shared data coming from the long-term monitoring of the bridge with the
structural health monitoring community in order to assess the current progress on damage detection and identification
methods with a full-scale example. The data set includes vibration data before and after the bridge was damaged, so they are
useful for testing new approaches for damage detection. In the first part of the paper, the Bayesian neural network model is
discussed; then in the second part, a Bayesian neural network procedure for damage detection has been tested. The proposed
method is able to detect anomalies on the behaviour of the structure, which can be related to the presence of damage. In order
to obtain a confirmation of the obtained results, in the last part of the paper, they are compared with those obtained by using a
traditional approach for vibration-based structural identification.Structural health monitoring of a cable-stayed bridge with Bayesian neural ne...
Structural health monitoring of a cable-stayed bridge with Bayesian neural ne...Franco Bontempi Org Didattica
In recent years, structural integrity monitoring has become increasingly important in structural engineering and construction management. It represents an important tool for the assessment of the dependability of existing complex structural systems as it integrates, in a unified perspective, advanced engineering analyses and experimental data processing. In the first part of this work
the concepts of dependability and structural integrity are
discussed and it is shown that an effective integrity assessment
needs advanced computational methods. For this purpose, soft computing methods have shown to be very useful. In particular, in this work the neural networks model is chosen and successfully improved by applying the Bayesian inference at four hierarchical levels: for training, optimization of the regularization terms, databased model selection, and evaluation of the relative importance of different inputs. In the second part of the article,
Bayesian neural networks are used to formulate a
multilevel strategy for the monitoring of the integrity of long span bridges subjected to environmental actions: in a first level the occurrence of damage is detected; in a following level the specific damaged element is recognized and the intensity of damage is quantified. Soft computing based multilevel strategy for bridge integrity monitoring
Soft computing based multilevel strategy for bridge integrity monitoringFranco Bontempi Org Didattica
Recommended
In recent years, there has been an increasing interest in permanent observation of the dynamic behaviour of bridges for longterm
monitoring purpose. This is due not only to the ageing of a lot of structures, but also for dealing with the increasing
complexity of new bridges. The long-term monitoring of bridges produces a huge quantity of data that need to be effectively
processed. For this purpose, there has been a growing interest on the application of soft computing methods. In particular,
this work deals with the applicability of Bayesian neural networks for the identification of damage of a cable-stayed bridge.
The selected structure is a real bridge proposed as benchmark problem by the Asian-Pacific Network of Centers for Research
in Smart Structure Technology (ANCRiSST). They shared data coming from the long-term monitoring of the bridge with the
structural health monitoring community in order to assess the current progress on damage detection and identification
methods with a full-scale example. The data set includes vibration data before and after the bridge was damaged, so they are
useful for testing new approaches for damage detection. In the first part of the paper, the Bayesian neural network model is
discussed; then in the second part, a Bayesian neural network procedure for damage detection has been tested. The proposed
method is able to detect anomalies on the behaviour of the structure, which can be related to the presence of damage. In order
to obtain a confirmation of the obtained results, in the last part of the paper, they are compared with those obtained by using a
traditional approach for vibration-based structural identification.Structural health monitoring of a cable-stayed bridge with Bayesian neural ne...
Structural health monitoring of a cable-stayed bridge with Bayesian neural ne...Franco Bontempi Org Didattica
In recent years, structural integrity monitoring has become increasingly important in structural engineering and construction management. It represents an important tool for the assessment of the dependability of existing complex structural systems as it integrates, in a unified perspective, advanced engineering analyses and experimental data processing. In the first part of this work
the concepts of dependability and structural integrity are
discussed and it is shown that an effective integrity assessment
needs advanced computational methods. For this purpose, soft computing methods have shown to be very useful. In particular, in this work the neural networks model is chosen and successfully improved by applying the Bayesian inference at four hierarchical levels: for training, optimization of the regularization terms, databased model selection, and evaluation of the relative importance of different inputs. In the second part of the article,
Bayesian neural networks are used to formulate a
multilevel strategy for the monitoring of the integrity of long span bridges subjected to environmental actions: in a first level the occurrence of damage is detected; in a following level the specific damaged element is recognized and the intensity of damage is quantified. Soft computing based multilevel strategy for bridge integrity monitoring
Soft computing based multilevel strategy for bridge integrity monitoringFranco Bontempi Org Didattica
Analisi strutturale nonlineare in presenza di softeningThe role of softening in the numerical analysis of R.C. framed structures
The role of softening in the numerical analysis of R.C. framed structuresFranco Bontempi Org Didattica
A numerical approach to the reliability analysis of reinforced and prestressed concrete structures is presented. The problem is formulated in terms of the probabilistic safety factor and the structural reliability is evaluated by Monte
Carlo simulation. The cumulative distribution of the safety factor associated with each limit state is derived and a reliability index is evaluated. The proposed procedure is applied to reliability analysis of an existing prestressed concrete arch bridge.Reliability of material and geometrically non-linear reinforced and prestress...
Reliability of material and geometrically non-linear reinforced and prestress...Franco Bontempi Org Didattica
This paper presents a general approach to the probabilistic prediction of the structural service life and to the maintenance
planning of deteriorating concrete structures. The proposed formulation is based on a novel methodology for the assessment of the time-variant structural performance under the diffusive attack of external aggressive agents. Based on this methodology, Monte Carlo
simulation is used to account for the randomness of the main structural parameters, including material properties, geometrical parameters, area and location of the reinforcement, material diffusivity and damage rates. The time-variant reliability is then computed with respect to proper measures of structural performance. The results of the lifetime durability analysis are finally used to select, among different maintenance scenarios, the most economical rehabilitation strategy leading to a prescribed target value of the structural service life. Two numerical applications, a box-girder bridge deck and a pier of an existing bridge, show the effectiveness of the proposed methodology.Probabilistic Service Life Assessment and Maintenance Planning of Concrete St...
Probabilistic Service Life Assessment and Maintenance Planning of Concrete St...Franco Bontempi Org Didattica
This paper presents a novel approach to the problem of durability analysis and lifetime assessment of concrete structures under
the diffusive attack from external aggressive agents. The proposed formulation mainly refers to beams and frames, but it can be easily
extended also to other types of structures. The diffusion process is modeled by using cellular automata. The mechanical damage coupled to diffusion is evaluated by introducing suitable material degradation laws. Since the rate of mass diffusion usually depends on the stress state, the interaction between the diffusion process and the mechanical behavior of the damaged structure is also taken into account by a proper modeling of the stochastic effects in the mass transfer. To this aim, the nonlinear structural analyses during time are performed
within the framework of the finite element method by means of a deteriorating reinforced concrete beam element. The effectiveness of the
proposed methodology in handling complex geometrical and mechanical boundary conditions is demonstrated through some applications.
Firstly, a reinforced concrete box girder cross section is considered and the damaging process is described by the corresponding evolution of both bending moment–curvature diagrams and axial force-bending moment resistance domains. Secondly, the durability analysis of a
reinforced concrete continuous T-beam is developed. Finally, the proposed approach is applied to the analysis of an existing arch bridge and to the identification of its critical members.Cellular Automata Approach to Durability Analysis of Concrete Structures in A...
Cellular Automata Approach to Durability Analysis of Concrete Structures in A...Franco Bontempi Org Didattica
The paper deals with the assessment during time of r.c. structures under damage due to diffusion of external agents inside the structure. The diffusion process is modelled by a cellular automata based approach, taking the interaction with the mechanical state of the structures, i.e. the cracking state of the structures, into account. A so-called staggered process then solves the coupled problem. An application shows the effectiveness of the proposed analysis strategy, together some design considerations about the structural robustness.
Atti Congresso CTE, Pisa 2000 UNA FORMULAZIONE DEL DEGRADO DELLA RISPOSTA DI STRUTTURE INTELAIATE IN C.A./C...
UNA FORMULAZIONE DEL DEGRADO DELLA RISPOSTA DI STRUTTURE INTELAIATE IN C.A./C...Franco Bontempi Org Didattica
Domanda appello di Tecnica delle Costruzioni del 6 luglio 2021.Descrivere questo elemento strutturale e indicare le cause del collasso
Descrivere questo elemento strutturale e indicare le cause del collassoFranco Bontempi Org Didattica
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Analisi strutturale nonlineare in presenza di softeningThe role of softening in the numerical analysis of R.C. framed structures
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A numerical approach to the reliability analysis of reinforced and prestressed concrete structures is presented. The problem is formulated in terms of the probabilistic safety factor and the structural reliability is evaluated by Monte
Carlo simulation. The cumulative distribution of the safety factor associated with each limit state is derived and a reliability index is evaluated. The proposed procedure is applied to reliability analysis of an existing prestressed concrete arch bridge.Reliability of material and geometrically non-linear reinforced and prestress...
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This paper presents a general approach to the probabilistic prediction of the structural service life and to the maintenance
planning of deteriorating concrete structures. The proposed formulation is based on a novel methodology for the assessment of the time-variant structural performance under the diffusive attack of external aggressive agents. Based on this methodology, Monte Carlo
simulation is used to account for the randomness of the main structural parameters, including material properties, geometrical parameters, area and location of the reinforcement, material diffusivity and damage rates. The time-variant reliability is then computed with respect to proper measures of structural performance. The results of the lifetime durability analysis are finally used to select, among different maintenance scenarios, the most economical rehabilitation strategy leading to a prescribed target value of the structural service life. Two numerical applications, a box-girder bridge deck and a pier of an existing bridge, show the effectiveness of the proposed methodology.Probabilistic Service Life Assessment and Maintenance Planning of Concrete St...
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This paper presents a novel approach to the problem of durability analysis and lifetime assessment of concrete structures under
the diffusive attack from external aggressive agents. The proposed formulation mainly refers to beams and frames, but it can be easily
extended also to other types of structures. The diffusion process is modeled by using cellular automata. The mechanical damage coupled to diffusion is evaluated by introducing suitable material degradation laws. Since the rate of mass diffusion usually depends on the stress state, the interaction between the diffusion process and the mechanical behavior of the damaged structure is also taken into account by a proper modeling of the stochastic effects in the mass transfer. To this aim, the nonlinear structural analyses during time are performed
within the framework of the finite element method by means of a deteriorating reinforced concrete beam element. The effectiveness of the
proposed methodology in handling complex geometrical and mechanical boundary conditions is demonstrated through some applications.
Firstly, a reinforced concrete box girder cross section is considered and the damaging process is described by the corresponding evolution of both bending moment–curvature diagrams and axial force-bending moment resistance domains. Secondly, the durability analysis of a
reinforced concrete continuous T-beam is developed. Finally, the proposed approach is applied to the analysis of an existing arch bridge and to the identification of its critical members.Cellular Automata Approach to Durability Analysis of Concrete Structures in A...
Cellular Automata Approach to Durability Analysis of Concrete Structures in A...Franco Bontempi Org Didattica
The paper deals with the assessment during time of r.c. structures under damage due to diffusion of external agents inside the structure. The diffusion process is modelled by a cellular automata based approach, taking the interaction with the mechanical state of the structures, i.e. the cracking state of the structures, into account. A so-called staggered process then solves the coupled problem. An application shows the effectiveness of the proposed analysis strategy, together some design considerations about the structural robustness.
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Esami a distanza. Severgnini. Corriere della sera.
Esami a distanza. Severgnini. Corriere della sera.
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