Applying advanced data analytics and machine learning to enhance the safety control of dams

The protection of critical engineering infrastructures is vital to today’s so- ciety, not only to ensure the maintenance of their services (e.g., water supply, energy production, transport), but also to avoid large-scale disasters. Therefore, technical and financial efforts are being continuously made to improve the safety control of large civil engineering structures like dams, bridges and nuclear facilities. This con- trol is based on the measurement of physical quantities that characterize the struc- tural behavior, such as displacements, strains and stresses. The analysis of monitor- ing data and its evaluation against physical and mathematical models is the strongest tool to assess the safety of the structural behavior. Commonly, dam specialists use multiple linear regression models to analyze the dam response, which is a well- known approach among dam engineers since the 1950s decade. Nowadays, the data acquisition paradigm is changing from a manual process, where measurements were taken with low frequency (e.g., on a weekly basis), to a fully automated process that allows much higher frequencies. This new paradigm escalates the potential of data analytics on top of monitoring data, but, on the other hand, increases data quality issues related to anomalies in the acquisition process. This chapter presents the full data lifecycle in the safety control of large-scale civil engineering infrastructures (focused on dams), from the data acquisition process, data processing and storage, data quality and outlier detection, and data analysis. A strong focus is made on the use of machine learning techniques for data analysis, where the common multiple linear regression analysis is compared with deep learning strategies, namely recur- rent neural networks. Demonstration scenarios are presented based on data obtained from monitoring systems of concrete dams under operation in Portugal.info:eu-repo/semantics/acceptedVersio

Measurements of the Colosseum response to environmental actions

The Colosseum is the most famous monument of ancient Rome. Differential settlements of its foundations, standing partly on alluvial deposits and partly on stiff soil, and various earthquakes are the main causes of collapses that give the Colosseum its present shape. In order to preserve the monument a number of structural interventions were made during the 19th century. At present, the health status of the monument requires to be monitored against possible degradation phenomena. During the preliminary design stage of a new underground line crossing the center of Rome, at present under construction, further investigations on materials properties and dynamic features have been performed. In particular, twelve accelerometers on two vertical lines in the highest portion of the monument have been installed. In the present paper data gathered with this monitoring system for a long period of time gives the opportunity of a further insight into the health conditions of the structure. The vibration levels induced by road traffic during a long interval of time and frequencies and mode shapes of low modes are identified using ambient vibration. Both these results are compared with the outcomes of an experimental campaign of a few years ago. Finally, the dynamic behaviour recorded during the 2016 Central Italy seismic sequence is analysed and discussed

Stima del danno in edifici di muratura soggetti a cedimenti

Several simplified approaches for the damage evaluation of masonry structures subjected to base settlements are available in literature. These approaches do not take explicitly into account typical features of historic buildings, such as complex layout, ancient materials and construction techniques. The finite elements method allows accurate linear and nonlinear modelling, but usually the level of damage cannot be directly calculated. This paper aims at proposing a methodology based on damage mechanics, in order to correlate a damage functional, calculated by means of a finite elements model, to suitable damage categories. Linear models can be used, providing their conditions of reliability. The parameter equivalent strain, formerly proposed for concrete, has been suitably applied to masonry. Several finite element codes include damage functionals, in the present paper the ADINA software has been used and the corresponding formulation has been simplified in terms of equivalent strain. Both compressive and tensile damage functionals can be defined, but the last one is more able to describe typical damage to masonry buildings. Due to the fragile behaviour of the masonry, the maximum value of the damage functional typically is attained in many points of the structure. Thus, a mean value of the functional over a suitably selected domain has been proposed, in order to distinguish between different damage states. The integration domains correspond to parts of the structure having a role in the structural behaviour (walls, spandrels). In absence of experimental data about damage to masonry in terms of crack openings (damage categories) as a function of the applied load, nonlinear finite element models have been used and a set of pseudoexperimental data has been created. Finally a correlation between the mean value of the damage functional and the damage category has been obtained. The methodology presented is intended to be used with finite element models of masonry buildings subjected to foundation settlements and a real example is illustrated. Using the proposed correlation, the damage functional can be evaluated in the above mentioned domains and the corresponding damage category is estimated

Dynamic identification of a masonry building using forced vibration tests

The aim of the paper is to check the capability of dynamic identification procedures. usually applied to reinforced concrete or steel buildings, in the estimation of the dynamic characteristics of masonry buildings. To this purpose. the dynamic behaviour at low vibration levels of an existing masonry building subjected to forced, sinusoidal or sweep, vibration test. was Investigated. Possibly on account of weak nonlinearities of the building, the measurements obtained with sinusoidal tests seemed more suited than those obtained by sweep tests for the application of identification techniques. These concern both modal and physical models: the dynamical characteristic; of the building. the frequencies and some eigenvector components obtained by modal identification. were assumed as experimental data to update suitability selected stiffness parameters of a finite element model of the structure. The updating was performed by means of a specially developed dynamic identification code based on an output error equation. Criteria for a rational choice of physical parameters and measurements were applied. A very pod agreement between numerical and experimental frequency response functions was obtained with the modal identification, while the physical model showed some rigidity in fitting all the experimental data. albeit with an acceptable level of scatter, Taken as a whole, the results show that well-established identification techniques can furnish useful information concerning the dynamic properties of existing masonry structures. (C) 2004 Elsevier Ltd. All rights reserved