Free Vibration Response of a Frame Structural Model Controlled by a Nonlinear Active Mass Driver System

Active control devices, such as active mass dampers, are mainly employed for the reduction of wind-induced vibrations in high-rise buildings, with the final aim of satisfying vibration serviceability limit state requirements and of meeting appropriate comfort criteria. When such active devices, normally operating under wind loads associated with short return periods, are subjected to seismic events, they can experience large amplitude vibrations and exceed stroke limits. This may lead to a reduced performance of the control system that can even worsen the performance of the whole structure. In this paper, a nonlinear control strategy based on a modified direct velocity feedback algorithm is proposed for handling stroke limits of an active mass driver (AMD) system. In particular, a suitable nonlinear braking term proportional to the relative AMD velocity is included in the control law in order to slowdown the device in the proximity of the stroke limits. Experimental and numerical free vibration tests are carried out on a scaled-down five-story frame structure equipped with an AMD to demonstrate the effectiveness of the proposed control strategy

active control of art objects subjected to seismic excitation

Abstract The problem of the protection of statues and works of art is important in earthquake-prone regions. Among mitigation techniques, the base isolation demonstrates to be one of the most effective, as it creates a disconnection between the artwork and the floor that avoids the seismic acceleration transmission. Although passive base isolation systems, if well designed for a specific location and a specific piece of art, are efficient in protecting the artifact, they are not immediately adaptable for different artworks, different locations within the building and different seismic hazard conditions. For these reasons, in the present paper it is exploited the possibility of using a base active control strategy in which a force provided by an actuator counterbalances the seismic acceleration. The base active and passive control solutions are compared considering different seismic intensities and different characteristics of the artwork. Results demonstrate the robustness and adaptability of active control for the seismic protection of works of art

OPTIMAL DESIGN OF AN ARRAY OF ACTIVE TUNED MASS DAMPERS

In this paper, a comprehensive procedure is developed for the optimization of a hybrid control system for tall buildings subjected to wind-induced vibrations. The control system is made of active tuned mass dampers (ATMDs) and is conceived to mitigate the flexural and torsional response in serviceability limit state conditions. The feedback information necessary to compute the control forces is provided by a limited number of accelerometers arranged over the building's height. To reduce the computational effort, subsequent optimization subprocedures are employed that take advantage of the genetic algorithm to find the solution of the nonlinear, constrained optimization problems. At first, the optimization of the ATMDs' number and positions over the top floor of the building is carried out. Then, the optimal location of the accelerometers over the building's height is obtained. The reduction of the flexural and torsional accelerations is chosen as target of the optimization problem. The technical limitations of the ATMDs, such as the actuators saturation and the limited stroke extensions, are the constraints to the problem. As an illustrative example, a control system is optimized for the response mitigation of a tall building subjected to wind load. Copyright © 2012 John Wiley & Sons, Ltd

Identification of the nonlinear behaviour of a cracked RC beam through the statistical analysis of the dynamic response

SUMMARY This study investigates a new identification procedure suitable to deal with nonlinear systems. The proposed approach is made up of three main parts: system excitation with a band-limited white noise, solution of the Fokker–Planck equation that describes the motion of the structure in a parametric form and identification of the unknown system parameters by minimizing a suitable functional. The new procedure is able, for instance, to assess the severity of cracking caused by the shrinkage or by the overcoming of the concrete tensile strength in reinforced concrete (RC) structures. Cracked RC elements, in fact, exhibit a nonlinear behaviour due to different values of the flexural stiffness that depends on the opening of the cracks. Some numerical simulations allowed verifying the applicability of the procedure. Copyright # 2008 John Wiley & Sons, Ltd

Life-cycle cost analysis of bridges subjected to fatigue damage

AbstractLife-cycle cost analysis (LCCA) is a decision-making tool particularly useful for the design of bridges as it predicts lifetime expenses and supports the inspections management and the maintenance activities. LCCA allows to consider uncertainties on loads, resistances, degradation and on the numerical modelling and structural response analysis. It also permits to consider different limit states and different types of damage in a unified framework. Among the types of damages that can occur to steel and steel-concrete composite bridges, fatigue is one of the most dangerous ones, as it may lead to sudden and fragile rupture, even at operational traffic levels. In this context, the present paper proposes a framework for LCCA based on the use of the Pacific Earthquake Engineering Research (PEER) equation which is for the first time utilized for fragility and cost analysis of bridges subjected to fatigue, highlighting the possibility of treating the problem of fatigue damage estimation with an approach similar to the one currently adopted for damage induced by other hazards, like earthquake and wind. To this aim, a damage index computed through the Palmgren-Miner's rule is adopted as engineering demand parameter. The framework is applied to a composite steel-reinforced concrete multi-span roadway bridge by evaluating the fatigue limit state from different traffic load models, i.e. a Technical Code-based model and a model based on results of Weigh in Motion monitoring system. The evolution over time of the probability of failure and the life-cycle costs due to fatigue damage induced by heavy traffic loads are investigated for different probability distributions of the engineering demand parameter and for different fragility models. The comparison between the fatigue failure probabilities and the life-cycle costs obtained with the two traffic models, encourages the adoption of traffic monitoring systems for a correct damage estimation

A new method for earthquake-induced damage identification in historic masonry towers combining OMA and IDA

AbstractThis paper presents a novel method for rapidly addressing the earthquake-induced damage identification task in historic masonry towers. The proposed method, termed DORI, combines operational modal analysis (OMA), FE modeling, rapid surrogate modeling (SM) and non-linear Incremental dynamic analysis (IDA). While OMA-based Structural Health Monitoring methods using statistical pattern recognition are known to allow the detection of small structural damages due to earthquakes, even far-field ones of moderate intensity, the combination of SM and IDA-based methods for damage localization and quantification is here proposed. The monumental bell tower of the Basilica of San Pietro located in Perugia, Italy, is considered for the validation of the method. While being continuously monitored since 2014, the bell tower experienced the main shocks of the 2016 Central Italy seismic sequence and the on-site vibration-based monitoring system detected changes in global dynamic behavior after the earthquakes. In the paper, experimental vibration data (continuous and seismic records), FE models and surrogate models of the structure are used for post-earthquake damage localization and quantification exploiting an ideal subdivision of the structure into meaningful macroelements. Results of linear and non-linear numerical modeling (SM and IDA, respectively) are successfully combined to this aim and the continuous exchange of information between the physical reality (monitoring data) and the virtual models (FE models and surrogate models) effectively enforces the Digital Twin paradigm. The earthquake-induced damage identified by both data-driven and model-based strategies is finally confirmed by in-situ visual inspections

An Automated Procedure for Assessing Local Reliability Index and Life-Cycle Cost of Alternative Girder Bridge Design Solutions

Stakeholders of civil infrastructures have to usually choose among several design alternatives in order to select a final design representing the best trade-off between safety and economy, in a life-cycle perspective. In this framework, the paper proposes an automated procedure for the estimation of life-cycle repair costs of different bridge design solutions. The procedure provides the levels of safety locally guaranteed by the selected design solution and the related total life-cycle cost. The method is based on the finite element modeling of the bridge and uses design traffic models as suggested by international technical standards. Both the global behavior and the transversal cross section of the bridge are analyzed in order to provide local reliability indexes. Several parameters involved in the design, such as geometry and loads and materials' characteristics, are considered as uncertain. Degradation models are adopted for steel carpentry and rebars. The application of the procedure to a road bridge case study shows its potential in providing local safety levels for different limit states over the entire lifetime of the bridge and the life-cycle cost of the infrastructure, highlighting the importance of the local character of the life-cycle cost analysis

Deep neural networks for unsupervised damage detection on the Z24 bridge

During their life-cycle, civil infrastructures are continuously prone to significant functionality losses, primarily due to material's degradation and exposure to several natural hazards. Following these concerns, many researchers have attempted to develop reliable monitoring strategies, as integration to visual inspections, to efficiently ensure bridge maintenance and early-stage damage detection. In this framework, recent improvements in sensor technologies and data science have stimulated the use of Machine Learning (ML) algorithms for Structural Health Monitoring (SHM). Among unsupervised learning techniques, the potential of autoencoder networks has been attracting notable interest in the context of anomaly detection. In this light, the present paper proposes two different autoencoder-based damage detection techniques, focused on the Multi-Layer Perceptron (MLP) and the Convolutional Autoencoder (CAE) networks, respectively. During the training, the selected ML models learn how reconstructing raw acceleration sequences acquired from sound conditions. Unknown data, including both healthy and damaged bridge responses, are afterwards used to test the implemented networks and to detect damage occurrence. To this aim, a specific index of reconstruction loss is selected as a damage sensitive feature with the aim to quantify the errors between the original and reconstructed sequences. The performance exhibited by the two approaches is compared and evaluated by application to the Z24 benchmark bridge. Results demonstrate the effectiveness of the proposed methodology to perform feature classification and real time damage detection at the level of macro-sequences as new sensor data is collected, resulting suitable for continuous assessment of full-scale monitored bridges