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The fatigue safety assessment of critical details in steel bridges is dominated by several uncertainties mainly related to load modelling. The use of integrated weigh-in-motion (WIM) systems in roadway bridges allows to collect all the necessary information for tracking actual traffic conditions. Based on WIM data, the uncertainty associated to the evaluation of the probability of fatigue failure is reduced, allowing the optimal scheduling of repair and maintenance activities and thus improving safety and economic savings. The paper presents a methodology for estimating fatigue life cycle cost (LCC) of roadway bridges equipped with a WIM system that considers uncertainties in measurement and modelling errors. The procedure allows the quantification of the economic gain enabled by WIM systems, useful in assessing the cost/accuracy trade-off for a given WIM system. It is found that the continuous use of a WIM system may improve the rate of decrease of the structural reliability index, compared with temporally limited use of WIM data. The periodic update of the reliability index and of the probability of failure based on WIM measurements results in a rather accurate estimation of the fatigue life cycle cost, which is crucial in identifying the payback time of the WIM system. [ABSTRACT FROM AUTHOR]

This paper presents the application of a Structural Health Monitoring (SHM) strategy for bridges affected by slow deformation phenomena to a curved roadway bridge undergoing slow landslide‐induced movements. The chosen multidisciplinary approach is based on the combination of remote sensing data through satellite Synthetic Aperture Radar Interferometry (InSAR) and structural analysis up to collapse investigated through the Applied Element Method (AEM). The results of the application to the considered case study demonstrate that the integration of the displacement information obtained through InSAR technique with the numerical analysis allows for improving the comprehension of the health state of the bridge undergoing slow movements and identifying potentially critical conditions for the structure. [ABSTRACT FROM AUTHOR]

This paper presents the structure of new collaborative research project entitled SAFOTEB "A reviewed SAfety FOrmat for structural reliability assessment of post‐TEnsioned concrete Bridges". The research aims at assessing the reliability of the current safety format and developing specific suggestions for existing concrete bridges with post‐tensioned cables. To date, no European code provides specific guidance for such a purpose. Indeed, the status of conservation and possible defects of the cables may be hidden, enlarging the uncertainties in the structural assessment of such constructions. The basic steps of the research are: (i) definition of the probabilistic models for the main variables concerning the assessment of existing post‐tensioned prestressed concrete bridges; (ii) reliability assessment and calibration of updated safety coefficients for the partial factors method; (iii) evaluation of the residual life and model updating through real‐time continuous monitoring systems. The full procedure will be applied on existing case study structures used as benchmarks. The project is funded by FABRE, an Italian research consortium composed by universities and research institutions aimed at the evaluation and monitoring of bridges, viaducts, tunnels and other structures. [ABSTRACT FROM AUTHOR]

Structural Health Monitoring of civil infrastructures often suffers from the limited availability of damage labelled data. The work here seeks to overcome this issue by using Transfer Learning approaches, in the form of Domain Adaptation, for leveraging information from a source structure with determined health‐state labels to make inferences on an unlabeled monitored structure. The idea is to exploit source data to train a Machine Learning algorithm and achieve improved early‐stage damage detection capabilities across a population of bridges. To account for differences in the underlying distributions of each structure, Transfer Learning is seen as a strategy enabling population‐level bridge SHM. In this paper, the natural frequencies obtained from multiple vibration measurements are extracted to characterise different domains during pristine and abnormal conditions. Such damage‐sensitive features are aligned via Domain Adaptation and used to train a standard classifier within a shared feature space. The methodology is validated on the heterogeneous population composed of the Z24 and S101 bridges. The results prove the effectiveness to successfully exchange damage labels, thus increasing available information for health‐state inference for SHM applications with sparce datasets. [ABSTRACT FROM AUTHOR]

The assessment of risk conditions of bridges and viaducts allows management authorities to ensure the safety of the users and the proper allocation of economic resources for maintenance and retrofitting interventions. A common circumstance in practice regards the lack of information as well as the need to update it, causing delays in the risk evaluation and, consequently, in the entire decision‐making process. Especially in the managing of large bridge assets, the retrieval/updating of information can be costly, both in terms of time and economic resources. In this regard, the execution of visual inspections to determine the defect level of bridges and viaducts is the most resource‐intensive operation on the part of the management authorities. In this paper, a new methodology to prioritize visual inspections of bridges according to their risk condition and operating costs is proposed and illustrated with a real case study. A novel aspect of the proposed methodology regards the use of information gain criteria to refine the outcomes from the risk assessment and prioritization process. Finally, the outcomes of the methodology are implemented in a GIS framework to ensure high interoperability and facilitate the construction of intuitive risk maps to assist inspection plans. [ABSTRACT FROM AUTHOR]

The behavior of post‐tensioned concrete bridges is often influenced by time‐dependent phenomena, such as relaxation of prestressing steel, creep and shrinkage of concrete. For bridges built using the balanced cantilever method, the evolution of time‐dependent phenomena during the construction phase must be carefully considered. In common practice, the assessment of the structural safety of this bridge typology is a complex task due to the numerous factors and uncertainties involved in the evaluation process. Numerical models can be adopted to perform structural analyses at successive phases over bridges' lifetime, while destructive and non‐destructive evaluation methods are used to gather information to ensure that the numerical model matches the actual behavior of the bridge. In this context, this paper presents the structural behavior assessment of a multi‐span post‐tensioned box girder bridge with vertically prestressed internal joints. A numerical model was constructed to investigate on the effect of creep and construction phases on the actual stress/strain conditions of the bridge. To reduce model‐based uncertainties, compression tests were carried out on concrete cores extracted from the structure and the results of static load tests were used for model validation purposes. [ABSTRACT FROM AUTHOR]

Bridges' integrity, safety and serviceability are fundamental targets that need to be ensured during the structural lifetime, owing to the crucial role that such infrastructure components play in modern communities. Recently, a particular attention is being paid to the management of bridges since many of them have reached the end of their expected service life. To this purpose, the Italian Ministry of Sustainable Mobility issued in 2020 the "Guidelines for risk classification and management, safety assessment and monitoring of bridges" that regulate visual inspections, risk assessment based on multilevel protocols and consequent monitoring and maintenance activities. In this context, structural health monitoring (SHM) systems play a fundamental role to guarantee safety and adequate performance levels. However, the synergy between visual inspections and SHM is yet to be fully understood and exploited. The main goal of this research work is to contribute to filling this gap by proposing a general probabilistic framework, based on Life‐Cycle Cost Analysis (LCCA), able to fuse information from SHM data and visual inspections, with the aim to plan over time short‐term and long‐term interventions and to optimize fund allocation by considering all the stored information. [ABSTRACT FROM AUTHOR]

Recent advances in computing performance and simulation tools allow today the development of high-fidelity computational models which accurately reproduce the structural behavor of existing structures. At the same time, advancements in sensing technology and data management enable engineers to remotely observe monitored structures in a continuous and comprehensive way. Merging the two approaches is a challenge recently addressed by the engineering research community, which led to the concept of digital twin (DT)—a simulation model continuously fed by sensor data which, throughout the whole lifespan of the structure, stands as its digital proxy. In the seismic field achieving such a task is still problematic, in particular for large and complex structures such as historical masonry palaces. To this aim, the paper proposes the integrated use of DTs and vibration data to support the seismic structural health monitoring of monumental palaces, discussing a practical application to the historical Consoli Palace in Gubbio, Italy. To overcome the computational limitations of classical approaches, an efficient equivalent frame (EF) model of the palace is built and continuously updated in quasi real-time based on modal information identified from vibration data. The performance and accuracy of the Equivalent Frame model are compared with those of a high-fidelity Finite Element representation, highlighting both their feasibility and limitations. Employing modal data recorded across the 15 May 2021 earthquake, the EF model demonstrates the ability to quickly assess the structural integrity of the palace in the post-earthquake scenario, as well as to forecast the residual capacity with respect to future seismic events. [ABSTRACT FROM AUTHOR]

Over the last decades, the rising number of aging infrastructures has progressively fueled much interest toward the field of structural health monitoring. Following the increasing popularity of artificial intelligence algorithms, an autoencoder‐based damage detection technique within the context of unsupervised learning is proposed in this paper to provide support for practical engineering applications. The developed methodology uses the autoencoder to reconstruct raw acceleration sequences of user‐defined length collected from a healthy structure. To quantify the errors between the original input and the reconstructed output, which may be representative of damage occurrence, two indexes of reconstruction loss are selected as damage‐sensitive features. To support damage detection, a selected number of short‐time sequences are finally grouped into a unique macrosequence. The novel procedure can effectively both work at the single sensor level, as well as combine the predictive models using an ensemble learning strategy. Avoiding system identification, results obtained in the Z24 bridge demonstrate that the proposed method is quite effective for local damage detection with limited computational effort and using a limited number of sensors, thereby suitable to be easily applicable in the context of real‐time bridge assessment. [ABSTRACT FROM AUTHOR]

The aeroelastic wind tunnel testing of flexible roofs made of hyperbolic paraboloid cable nets is a challenging task for designers and researchers, with very limited documented experiences in the literature. The reduced-scale model construction and its dynamic identification are the main issues to address when approaching this problem, mainly because of (i) the very small mass of the roof, (ii) the strict aeroelastic criteria to satisfy and (iii) a large number of very closely spaced significant natural frequencies. To suggest an approach to follow to investigate the wind—structure interaction for this structural typology, this paper discusses the aeroelastic scaling, the aeroelastic model construction, the dynamic modal identification and the FEM predictive numerical modelling of hyperbolic paraboloid roofs (HPRs) with square, rectangular and circular plan shapes and two different curvatures. Modal identification is especially challenging due to the presence of several closely spaced modes and it is here tackled by different methods such as Welch’s method, random decrement technique (RDT), Empirical mode decomposition with a time-varying filter (TVF-EMD) and frequency domain decomposition method (FDD). The satisfying accuracy of the aeroelastic scaling has been verified by comparing the wind-induced vertical displacements of the prototypes against those of the experimental models. Furthermore, an extensive qualitative investigation of the natural mode shapes has been carried out revealing that test models reproduce most of the prototype modes. [ABSTRACT FROM AUTHOR]

Many countries exposed to high levels of seismic risk, including Italy, are facing a huge challenge in promptly quantifying post-earthquake damages to their built historical heritage. In this context, structural health monitoring plays a fundamental role allowing to continuously track changes in selected damage-sensitive features. However, monitoring data interpretation is often not univocal and may be affected by large uncertainty, provoking false positives and false negatives. Hence, this research proposes a novel approach for post-earthquake structural condition assessment by exploiting the aggregation of different sources of information, notably steering from both monitoring and visual inspection campaigns, in order to take risk-informed decisions. More in depth, an automatic tool is proposed to detect and locate structural damages in monumental structures with the aid of a data fusion approach including vibration-based system identification, static and dynamic measurements, finite element (FE) and surrogate modeling, Bayesian-based model updating and visual inspections. In a preliminary phase, potential damage-sensitive regions in the structure are identified through FE-based numerical analysis and engineering judgment. Then, the solution of the inverse problem aimed at deriving the Bayesian posterior statistics of the uncertain parameters is entrusted to a computational-effective surrogate model (SM). Finally, the Bayesian-based updated parameters are adjusted considering the different allowable sources of information to achieve a final assessment. The effectiveness of the proposed approach is demonstrated by using the recorded data acquired in the Consoli Palace, an historical building located in Umbria, central Italy, which has been continuously monitored since 2017 using dynamic, static and environmental sensors and which has been hit by low-intensity earthquakes in 2021. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar Interferometry (InSAR) using satellite data is revealing a promising tool for monitoring long-term deformation phenomena in critical infrastructural systems. Nevertheless, its use in structural engineering is still quite limited and a general understanding of its potential is still missing, especially when dealing with bridge structures for which specific methods of data processing and displacement assessment with error quantification need to be developed, accounting for the type of deformation phenomena and for the orientation of the bridge. In order to partly fill this research gap, this paper proposes a post-processing methodology to derive two-dimensional displacement configurations of multi-span bridges with properly defined error bounds, using both ascending and descending Synthetic Aperture Radar acquisitions. In order to obtain an engineering meaningful estimate of the uncertainties affecting the reconstructed bridge deformations, both random and systematic errors are quantified, accounting for the orientation of the bridge with respect to the Line-Of-Sights of the satellites, the hypothesized deformation plane and the accuracy of InSAR measurements. The proposed procedure has been applied to the illustrative case study of the Albiano-Magra Bridge in Italy, collapsed on 8 April 2020. The results, referred to the monitoring period 2015–2020, demonstrate the effectiveness of the proposed method in supporting engineering assessments. In particular, an initially temperature-induced stationary deformation phenomenon has been observed, with all spans moving upwards or downwards during summer and winter. Afterwards, displacements of increasing amplitude for two side spans have been observed during the three years preceding the failure, providing information on the possible cause of collapse. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of rebars' corrosion monitoring systems on the vulnerability assessment and life-cycle cost analysis (LCCA) of reinforced concrete (RC) bridge piers subjected to repeated earthquake loading. A methodology is proposed to investigate the life-cycle economic savings gained with the use of a structural health monitoring (SHM) system made of corrosion sensors, exploiting the construction of damage-dependent fragility curves and using the pacific earthquake engineering research (PEER) equation to calculate the seismic probability of failure. The availability of corrosion sensors' data is accounted for in the degradation model for assessing the probability of failure by assuming that the recorded corrosion parameters are deterministic variables during the monitored period. Monitoring data are simulated by choosing values from the literature for the parameters representing the corrosion conditions. Seismic damage accumulation is considered through Monte Carlo (MC) simulations of long-term seismic scenarios considering the mean annual rate of earthquake occurrence obtained by the seismic hazard curves. The results of the methodology application to a case study highlight the importance of incorporating corrosion effects for the correct estimation of seismic life-cycle vulnerability. They are also used to discuss the advantage in terms of the safety and economy of including corrosion sensors for optimizing maintenance activities as opposed to purely inspection-based evaluations. [ABSTRACT FROM AUTHOR]

Life-cycle cost analysis is an approach that has gained popularity for assisting the design of civil infrastructures. The life-cycle cost analysis approach can be leveraged for structures equipped with structural health monitoring systems in order to quantify the benefits of the technology and de facto support its long-term implementation. However, for new structures, the long-term assessment of the expected value of the total investment cost, in terms of the current worth at the design time, is still the focus of ongoing research due to unknowns and uncertainties on the impact of the structural health monitoring system on long-term structural performance. This article proposes a new combined model of life-cycle cost formulation and simulation methodology for the long-term financial assessment of transportation bridges equipped with seismic structural health monitoring systems, in order to evaluate the total costs and benefits offered by such monitoring systems for post-seismic assessments. The formulation characterizes the time evolution of bridge management cost terms, highlighting the most sensitive parameters. The simulation methodology allows to quantitatively weigh each maintenance action on the total cost based on when the action is performed. The model is used to compare structures managed by the traditional approach of post-earthquake inspection versus those managed by a condition-based approach enabled by structural health monitoring systems. The originality of the model empowers the comparison by payback time, defined as the break-even point between costs and benefits of a structural health monitoring system, as well as by economic gain, defined as the difference between the total costs of an unmonitored versus a monitored structure through the end of service life. The proposed model is demonstrated through parametric analyses on a case study consisting of a continuous steel-concrete composite bridge, where the structural health monitoring system is used to monitor the elastic limit state condition of bending forces in piers during the earthquake. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

Tall buildings are especially prone to damage caused by winds and earthquakes. In practice, only a single hazard is assumed to dominate the design and is adopted for structural verifications. This is also the case when supplemental damping devices such as tuned mass dampers (TMDs) are adopted. Nevertheless, previous research has shown that from a life-cycle cost (LCC) perspective the dominant hazard concept is misleading, and a multi-hazard approach is necessary. This article proposes a methodology for multi-objective optimization-based design of multiple TMDs (MTMDs) attached to tall buildings subjected to both winds and earthquakes. The LCC related to damage on non-structural components is taken as one of the objective functions to join consistently these hazards. The MTMDs initial cost is selected as the second objective function. The results of these multi-objective optimization problems are Pareto fronts of optimized solutions that may be of interest to stakeholders, including non-technical decision makers. A genetic algorithm is adopted as solution strategy. A realistic case study is presented, and the optimization results are compared with classic literature solutions. [ABSTRACT FROM AUTHOR]

The aim of this work is to propose an efficient tool for the design of the monitoring system of precast reinforced concrete industrial buildings in seismic hazard zones, enabling the rapid post-earthquake damage assessment. The methodology, designated as spatio-temporal online monitoring (STOM) is performed by analyzing data obtained from a set of bi-directional accelerometers integrated in smart columns within the building. Acceleration records are converted into inter-story drift ratio (IDR) data, designated as engineering demand parameters, by double integration. Then, calculated IDRs are compared to three levels of alert thresholds meaning that, for the selected damage state, the structure is classified as apparently safe, restricted use or unsafe, corresponding to slight damage, moderate damage and severe damage. Finally, the STOM results trigger visual inspections, thus representing the main inputs needed by engineers in order to evaluate the structural health status and eventually decide for further actions. Measurements data are collected across time as well as space to ensure greater robustness and effectiveness. The STOM methodology allows the preliminary design, i.e., number and location of sensors and optimal demand thresholds, by exploiting the receiver operating characteristics (ROC) analysis, which classifies the different options on the basis of their performance in reporting true damage scenarios with respect to false alarms. Hence, seismic monitoring data are used in conjunction with the pre-evaluated alert states as an engineering decision-support tool for the post-earthquake diagnosis of the structure. [ABSTRACT FROM AUTHOR]

Structural Health Monitoring (SHM) based on Automated Operational Modal Analysis (A-OMA) has gained increasing importance in the conservation of heritage structures over recent decades. In this context, finite element model updating techniques using modal data constitute a commonly used approach for damage identification. Nevertheless, the large number of simulations usually involved in the associated minimization problem hinders the application to real-time condition assessment. This is especially critical for historic buildings, where the modelling of complex geometries involves large computational burdens. Alternatively, surrogate models offer an efficient solution to replace computationally demanding numerical models and so perform continuous model updating. In this light, this paper presents a surrogate-based model updating approach for online assessment of historic buildings and its application to a medieval masonry tower, the Sciri Tower in Perugia (Italy). Using modal properties identified by A-OMA, the proposed approach allows the continuous fitting of certain damage-sensitive parameters of the structure. To do so, three different surrogate models are considered, including the quadratic response surface method, Kriging, and Random Sampling High-Dimensional Model Representation, and their effectiveness is compared from an SHM perspective. The reported results demonstrate the suitability of the proposed methodology for tracking the temperature-dependent intrinsic properties of the tower. [ABSTRACT FROM AUTHOR]

This paper presents an enhanced version and the validation of a recently proposed methodology for earthquake-induced damage detection and localization in masonry towers by using long-term vibration monitoring data. The proposed enhanced method is based on continuous operational modal analysis through stochastic subspace identification, dynamic multiple linear regressive analysis to remove the effects of changing environmental conditions and finite element (FE) model updating. Any anomalous frequency deviation from normal conditions resulting from an earthquake triggers the damage localization process. This task is performed by solving an inverse FE model calibration problem, where equivalent elastic properties of macrostructural elements are identified by minimizing an objective function considering experimentally identified and numerically predicted damage-induced decays in natural frequencies and changes in eigenvector components. To minimize the computational effort of this calibration procedure, a quadratic surrogate model is constructed using a tuned numerical FE model of the structure. The methodology is validated through application to the "Sciri Tower", an historic civic masonry tower located in Perugia, Italy, that has been continuously monitored by the authors for more than 1 year. The validation is carried out by using simulated damage scenarios and a set of real far-field earthquake data and is based on a FE model of the tower including surrounding buildings, calibrated on the basis of the measured data from ambient vibration tests. The results demonstrate that the proposed procedure is capable of correctly detecting and localizing earthquake-induced damages. [ABSTRACT FROM AUTHOR]

This article investigates the possibility of using active control devices for the seismic protection of museum artifacts subjected to sliding and rocking. An actively base isolated system is compared to a passively base isolated one constituted by a spring-dashpot system that can represent a simplified modeling of both a base isolator or a flexible case-supporting system. Results show that active base isolation has superior performance than the passive one for the seismic protection of museum's artifacts. Moreover, due to their adaptability and robustness, active control devices can be adopted for different works of art in different site exposure conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents a framework for life-cycle loss estimation for non-structural damage in tall buildings under wind and seismic loads. Life-cycle cost analysis is a useful design tool for decision- makers, aimed at predicting monetary losses over the lifetime of a structure, accounting for uncertainties involved in the problem definition. For tall buildings, sensitive to dynamic excitations like earthquake and wind, it can be particularly suitable to base design decisions not only on initial cost and performance but also on future repair expenses. The proposed approach harmonises the procedures for intervention costs evaluation of structures subjected to multiple-hazards, taking into account the peculiar differences of wind and earthquake, in terms of load characterisation, type and evolution of damage. Relative effect of the two hazards on damage to drift- and acceleration-sensitive non-structural elements are examined. The influence of uncertainty in structural damping is also taken into account. It is shown that, although it is commonly believed that the design of a given structure is usually dominated by either winds or earthquakes, when LCC-based design is performed, both winds and earthquakes may be important. [ABSTRACT FROM AUTHOR]

Model reference adaptive control (MRAC) strategies are gaining an increasing interest by researchers working in the area of structural control mainly for their capacity of compensating for large uncertainties, faults and time varying disturbances in linear and nonlinear plants. In this paper a modification of the standard MRAC algorithm is proposed which adopts multiple reference models (M-MRAC). The motivation of the proposed scheme is that flexible buildings subjected to multiple hazards, like wind and earthquake, require different damping levels to avoid the occurrence of different limit states. A M-MRAC scheme that uses two reference models is adopted. The first reference model, with small structural damping, is active in the presence of low level excitation like moderate wind loading, while the second reference model, with a higher damping, is activated when a suitable response-dependent signal exceeds a defined threshold in the presence of severe seismic loading. Analyses on a tall building subjected to wind and earthquake show the capacity of the M-MRAC in tracking the reference system and in mitigating the structural response. Comparison with traditional MRAC highlights that the main advantage of M-MRAC is the reduction of the control force, at the expense of a slight reduction of control effectiveness. [ABSTRACT FROM AUTHOR]

Active control systems are a viable solution to mitigate seismic effects in buildings. The actual response of structures equipped with active control devices is influenced by control-structure interaction (CSI) and actuation imperfection. This paper investigates both effects on the response and on closed-loop stability of a frame structure equipped with an Active Mass Driver with electric torsional servomotor. The closed-loop stability conditions are studied by investigation of the root-locus of the system and the effects of CSI and actuation imperfection are individually quantified. Results obtained under harmonic and seismic base excitations show that accounting for CSI leads to non-negligible variations in control performance, especially for large mass ratios, and that actuator's dynamics significantly influence the system's stability. [ABSTRACT FROM AUTHOR]

In this paper a newly proposed approach to robust optimization is adopted in order to study the influence of uncertain structural parameters on the design of a passive control system The control devices are Tuned Mass Dampers placed on a tall building subjected to wind load. The uncertain structural variables are the floors' mass and stiffness. The spatial variability of the mass over the floor's surface is considered by ideally dividing each floor into a certain number of partitions in which the mass varies as a random variable. The robust optimization procedure is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The Latin Hypercube Sampling is employed to reduce the number of samples. The optimization of stiffnesses and dampings of the devices is carried out for each sample set of structural mass and stiffness matrices, allowing the evaluation of the probability distributions of the optimal parameters and the objective function. The robust designs are those having corresponding values of the objective function lying in the neighborhood of the expected value of the distribution The robust optimization is applied to a tall building controlled by a Tuned Mass Damper and subjected to wind loads obtained from wind tunnel tests. Several numerical analyses are carried out considering different numbers of surface partitions. Both the separate and joint influence of the mass and stiffness uncertainty is considered. The results show that the selected designs are robust, as they guarantee a small variability of structural performance caused by uncertainties. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

ABSTRACT 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. [ABSTRACT FROM AUTHOR]