Un mestiere difficile. 20 maggio 2015
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UN MESTIERE DIFFICILE: come non andare in prigione facendo l’ingegnere 20 maggio 2015 ore 14.00 – Facoltà di Ingegneria - aula 24 – via Eudossiana 18
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CM - Sustainability of tall buildings: issues and structural design.
Lezione del 17 dicembre 2015 dell'Ing. Konstantinos Gkoumas al Corso di Costruzioni Metalliche del Prof. Ing. Franco Bontempi, Facolta' di Ingegneria Civile e Industriale, Universita' degli Studi di Roma La Sapienza.
Calcolo della precompressione: DOMINI e STRAUS7
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DOMINI e STRAUS7
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Sapienza Università di Roma
II evento didattica 5 aprile 2022 TECNICA DELLE COSTRUZIONI.pdf
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• illustrare l'identità culturale, e tecnica – di cui il progetto è parte fondante – del SSD Tecnica delle Costruzioni nella didattica,
• evidenziando contemporaneamente le opportunità di collaborazione trasversale con altre discipline,
• con particolare riferimento ai corsi della lauree magistrali o
equivalenti, e livelli di formazione successivi (master e dottorati).
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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
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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
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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. Recommended
CM - Sustainability of tall buildings: issues and structural design.
Lezione del 17 dicembre 2015 dell'Ing. Konstantinos Gkoumas al Corso di Costruzioni Metalliche del Prof. Ing. Franco Bontempi, Facolta' di Ingegneria Civile e Industriale, Universita' degli Studi di Roma La Sapienza.
Calcolo della precompressione: DOMINI e STRAUS7
Calcolo della precompressione:
DOMINI e STRAUS7
Corso di Gestione di Ponti e Grandi Strutture A.A. 2021/22
Prof. Ing. Franco Bontempi
Facoltà di Ingegneria Civile e Industriale
Sapienza Università di Roma
II evento didattica 5 aprile 2022 TECNICA DELLE COSTRUZIONI.pdf
Scopo dell'evento è
• illustrare l'identità culturale, e tecnica – di cui il progetto è parte fondante – del SSD Tecnica delle Costruzioni nella didattica,
• evidenziando contemporaneamente le opportunità di collaborazione trasversale con altre discipline,
• con particolare riferimento ai corsi della lauree magistrali o
equivalenti, e livelli di formazione successivi (master e dottorati).
ICAR 09_incontro del 5 aprile 2022_secondo annuncio.pdf
L’incontro ha l’obiettivo di delineare l'identità culturale, scientifica e tecnica della disciplina della Tecnica delle Costruzioni nella didattica, evidenziando contemporaneamente le opportunità di collaborazione trasversale con altre discipline, con particolare riferimento ai corsi della lauree magistrali o equivalenti, e livelli di formazione successivi (master e dottorati).
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, 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.Soft computing based multilevel strategy for bridge integrity monitoring
Soft computing based multilevel strategy for bridge integrity monitoringFranco 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
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presented, with particular attention to the ones necessary for structural damage identification.
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within the framework of the finite element method by means of a deteriorating reinforced concrete beam element. The effectiveness of the
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Un mestiere difficile. 20 maggio 2015
- 1. Corso di Legislazione delle OO.PP. e dell’Edilizia - Diritto urbanistico – Sociologia Urbana Presenta Prof. Antonio D’Andrea – Direttore DICEA Introduce Prof. Alessandro Cutini Relatore: Prof. Avv. Donatella Morroni Esperienze sul campo Ing. Franco Bontempi - Professore Ing. Roberta Silo - Assessore Comunale Ing. Sergio Anania - Dipendente Ing. Stefania Arangio - Libera professionista Ing. Giuseppe Galiano - Studente Ph.D. UN MESTIERE DIFFICILE: come non andare in prigione facendo l’ingegnere 20 maggio 2015 ore 14.00 – facoltà di ingegneria - aula 24 – via Eudossiana 18 Conclude: Prof. Ing. Alessandro Cutini -