1,720,974 research outputs found
Structural Health Monitoring: approcci innovativi tramite tecniche ibride di supervised Machine Learning
No full textIl lavoro presenta approcci innovativi alle tecniche di monitoraggio dello stato di salute strutturale facendo ampio uso di strumenti quali Finite Element Model Update e Intelligenza Artificiale.
L'obbiettivo è sviluppare un framework in grado di stabilire lo stato di salute strutturale in modo efficace e robusto spingendosi infine alla determinazione probabilistica della sua vita residua.
Nel corso del lavoro è stato inoltre sviluppato un software per l'identificazione dinamica modale e l'analisi di segnali ambientali e sismici.The paper presents innovative approaches to structural health monitoring techniques making extensive use of tools such as Finite Element Model Update and Artificial Intelligence.
The goal is to develop a frameowrk capable of establishing the health status for a structure in an effective and robust manner spienging eventually to the probabilistic determination of its remaining life.
In the course of the work, software for dynamic modal identification and analysis of environmental and seismic signals was also developed
Framework for Identification and Prediction of Corrosion Degradation in a Steel Column through Machine Learning and Bayesian Updating
Full text linkIn recent years, structural health monitoring, starting from accelerometric data, is a method which has become widely adopted. Among the available techniques, machine learning is one of the most innovative and promising, supported by the continuously increasing computational capacity of current computers. The present work investigates the potential benefits of a framework based on supervised learning suitable for quantifying the corroded thickness of a structural system, herein uniformly applied to a reference steel column. The envisaged framework follows a hybrid approach where the training data are generated from a parametric and stochastic finite element model. The learning activity is performed by a support vector machine with Bayesian optimization of the hyperparameters, in which a penalty matrix is introduced to minimize the probability of missed alarms. Then, the estimated structural health conditions are used to update an exponential degradation model with random coefficients suitable for providing a prediction of the remaining useful life of the simulated corroded column. The results obtained show the potentiality of the proposed framework and its possible future extension for different types of damage and structural types
Machine Learning technique for the diagnosis of environmental degradation in a steel structure
No full textIn recent years, monitoring techniques for knowledge of structural safety have become increasingly important. Machine Learning techniques are certainly among the most innovative techniques and with an incredible future potential supported by an ever more computational power availability. In this paper, various supervised learning techniques are investigated in order to quantify the generalized corrosion thickness that could occur in a steel structure. At this regard, a finite element model has been developed in the Finite Element Software OpenSees in which a stochastic ergodic white noise process at the column base has been introduced to simulate environmental vibrations. Furthermore, to simulate the operating conditions, the masses were introduced in probabilistic terms. Once the vibration signals were extracted in terms of accelerations, various features in frequency domain were calculated for AI training. Different configurations of Support Vector Machines (linear, quadratic, cubic and Gaussian) were explored also with Bayesian optimization of the hyperparameters and definition of the penalty matrix. The results obtained show the potential of these techniques for structural monitoring and their future possible extension to different structural typologies and with different damage types
Operational modal analysis, seismic vulnerability assessment and retrofit of a degraded RC bell tower
Full text linkThis paper presents damage assessment through Operational Modal Analysis (OMA) and Finite Element (FE) model updat- ing of the bell tower of the church of Castro in Bergamo, Italy. The tower is a 39 m high reinforced concrete structure with hollow cross-section and double-curved shape. The research was dictated by the need to identify the actual damage state of the structure, which was found through visual inspections. Piezoelectric accelerometers were used to record the ambient vibrations in subsequent test setups, using the roving technique for system identification. A detailed FE model was created with shell elements and calibrated to match the system identification results. A simplified beam model was then developed based on the modal analysis results of the detailed model. A sensitivity analysis was performed to identify the most influen- tial model parameters on the modal characteristics of the system. Subsequently, the optimal values of these parameters were determined by an optimisation procedure carried out using a typical global optimization algorithm. The updating results allowed assessment of the actual condition of the bell tower and its seismic vulnerability. Finally, a seismic strengthening solution was recommended
Integrated BIM-SHM techniques for the assessment of seismic damage
Full text linkNowadays, there is an increasing massive use of BIM technologies in the field of construction and civil engineering, both in the design phase and in the construction and management of the life cycle of the structure. This work aims to explore the possibility of integrating BIM technologies within the Structural Health Monitoring field. In particular, a framework has been developed to define in probabilistic terms through fragility curves the presence of damage after a seismic event and promptly visualize the damaged elements in a digital twin model and share the information with the various stakeholders. In particular, the effort has been placed in analyzing in detail the flow of data recorded from possible sensors placed on the building, passing through the post-processing and evaluation of the structural health of structural and non-structural elements up to the integration of this information in a BIM environment
Damaged detection of a bell tower through OMA
No full textThis document presents the Operational Modal Analysis and finite element update of the bell tower of the church of Castro (BG), in Italy. This procedure was adopted to identi- fy the actual state of structural damage following the widespread carbonation and oxidation of the surface concrete layer and the significant localized damage of the rebars detected by visual inspections. The 39m high structure is a reinforced concrete tower with a hollow sec- tion with a double concavity and a tapered section in elevation. Four uniaxial piezoelectric accelerometers were adopted to record environmental vibrations for dynamic identification using the roving technique. After performing dynamic identification, two types of 3D structur- al models were compared, namely with shell elements and beam elements. Finally, a calibra- tion of the shell finite element model was carried out to identify the boundary conditions and the extension of the damage. The knowledge of the actual state of the structural damage ena- bles the definition and the design of the retrofit strategy aimed at guaranteeing both static and seismic safety, as well as the future preservation of the structure
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Investigation on the Use of SAR Data at the Building Scale
No full textIn the last decades, the Synthetic Aperture Radar (SAR) technology has undergone a quality increase in signal acquisition and therefore a greater quality and precision of the measurements. This allowed to develop a technique capable of capturing the displacements over time, called Differential Interferometric SAR (D-InSAR). At first, the Satellite Interferometry (InSAR) technique was used to determine the displacements that occurred as a result of earthquakes, land-slides and volcanic eruptions. Now, thanks to the sensitivity achieved, several studies are currently ongoing to investigate the possibility of using these techniques to monitor the movements and deformations of buildings and infrastructures. In this paper, an attempt is made to evaluate the correlation between DInSAR data and the damage states of buildings based on differential settlement scenarios. For this purpose, nonlinear numerical models of RC buildings have been developed and analyzed
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