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Preview: Journal of Structural Control

Structural Control and Health Monitoring

Wiley Online Library : Structural Control and Health Monitoring

Published: 2017-10-01T00:00:00-05:00


Wireless structural control using stochastic bandwidth allocation and dynamic state estimation with measurement fusion


Wireless sensor networks are becoming more popular for structural monitoring because of their low installation costs; in addition, coupling structural control with wireless data acquisition can also yield advantages. However, these systems have limited communication bandwidth, limiting their effectiveness as the number of devices in control networks grows large if centralized control approaches are used. Traditional methods for collocating data in wireless structural control network rely on time-budgeted bandwidth or spatial decentralization, where the network is divided into smaller subnetworks. These methods are largely static and typically do not take into account any measure of data quality to prioritize transmissions. This study presents a dynamic approach for bandwidth allocation in wireless structural control networks that relies on an application-specific, autonomous, and controller-aware, carrier sense multiple access with collision detection protocol. Stochastic parameters are derived to strategically alter back-off times in the carrier sense multiple access with collision detection algorithm based on nodal observability and output estimation error. Inspired by data fusion approaches, this paper presents 2 different methods for neighborhood state estimation using a dynamic form of measurement-only fusion. Upon receiving data from the contended wireless medium, each wireless unit fuses incoming data using a precalculated static Kalman gain matrix for the corresponding dynamic neighborhood. Onboard, each wireless unit contains a library of Kalman gain matrices, to accommodate any possible set of communicated data. Both numerical simulations and small-scale laboratory experimental results are presented.

A semi-baseline damage identification approach for complex structures using energy ratio correction technique


Because damage identification results based on the Lamb waves propagation approach can be influenced by varying environmental and operational conditions, development of a robust monitoring system with no need of the prior measured data of the structure has gained much attention recently. The instantaneous baseline damage detection technique is one of the promising methods that overcome the mentioned obstacles. For this, the material properties, electromechanical characteristics, and the geometric features must be identical. Also, sensor distances in similar paths and the geometric dimensions of the transducers must be the same. So, implementing the instantaneous baseline damage identification in complex structures is rather complicated due to the inherent non-homogeneities involved. To ease the complexity, this article proposes a semi-instantaneous baseline damage identification approach by modifying an existing instantaneous baseline method. This is used to detect and characterize fatigue cracks that initiate around the rivet holes of lap joint structures. In this method, an active sensing network is mounted on the lap joint, and a robust and effective feature called energy ratio change is extracted from the collected time-domain signals using the wavelet transform. The introduced “identicality coefficient” for all the sensing paths in pristine condition of the structure is obtained and used to remove any inequalities that may occur to the signals of each path. The obtained results show that the proposed method can detect fatigue cracks around the lap joint rivet holes and estimate the crack size. An experiment as well as numerical simulations is performed to verify the method.

Experimental study of local and modal approaches to active vibration control of elastic systems


Two different methods, local and modal, are suggested to control systems with distributed parameters, each of them having its own advantages and drawbacks. The aim of the present research is to carry out experiments aiming in comparison of these 2 methods for the problem of suppression of forced bending vibrations of a thin metal beam. Two pairs of piezoelectric sensors and actuators are attached to the beam in each control system considered. Their locations are chosen so as to provide the most efficient measurement and excitation of the first and second vibration modes of the beam. Frequency methods of the automatic control theory are employed to design stable control systems that can efficiently suppress bending vibrations of the beam with the first and second resonance frequencies. As a result, control systems with the desired performance are created on the basis of both local and modal methods. The obtained modal system works efficiently for both resonances, whereas the local systems demonstrate appropriate performance either at the first or at the second resonance frequency only. This difference is due to the fact that in the case of modal control, each control loop corresponds to a particular vibration mode and can be designed to provide optimal performance at the required frequency. The performed benchmark study demonstrates the advantages of the modal method over the local one for the cases where it is necessary to suppress vibrations in the frequency range that contains more than one resonance frequency of the control object.

Adaptive constrained unscented Kalman filtering for real-time nonlinear structural system identification


The unscented Kalman filter (UKF) is often used for nonlinear system identification in civil engineering; nevertheless, the application of the UKF to highly nonlinear structures could not provide accurate results. In this paper, an improvement of the UKF algorithm has been adopted. This methodology can consider state constraints, and it can estimate the measurement noise covariance matrix. The results obtained adopting a modified UKF have been compared to the ones obtained using the UKF for parameter estimation of a single degree of freedom nonlinear hysteretic system. The second part of this work shows results of an experimental activity on a base-isolated prototype structure. Both numerical and experimental results underline that the adopted algorithm produces better state estimation and parameter identification than the UKF, being capable of taking into account parameter boundaries. The adopted algorithm is more robust than the standard UKF in the case of measuring noise variation.

Optimal tuned mass-damper-inerter (TMDI) design for seismically excited MDOF structures with model uncertainties based on reliability criteria


The tuned mass-damper-inerter (TMDI) is a recently proposed linear passive dynamic vibration absorber for the seismic protection of buildings. It couples the classical tuned mass damper (TMD) with an inerter, a two-terminal device resisting the relative acceleration of its terminals, in judicial topologies, achieving mass-amplification and higher-modes-damping effects compared to the TMD. This paper considers an optimum TMDI design framework accommodating the above effects while accounting for parametric uncertainty to the host structure properties, modeled as a linear multi degree of freedom system, and to the seismic excitation, modeled as stationary colored noise. The inerter device constant, acting as a TMD mass amplifier, is treated as a design variable, whereas performance variables sensitive to high-frequency structural response dynamics are used to account for the TMDI influence to the higher structural modes. Reliability criteria are adopted for quantifying the structural performance, expressed through the probability of occurrence of different failure modes related to the trespassing of acceptable thresholds for the adopted performance variables: floor accelerations, interstory drifts, and attached mass displacement. The design objective function is taken as a linear combination of these probabilities following current performance-based seismic design trends. Analytical and simulation-based tools are adopted for the efficient estimation of the underlying stochastic integral defining the structural performance under uncertainty. A 10-story building under stationary Kanai-Tajimi stochastic excitation is considered to illustrate the design framework for various TMDI topologies and attached mass values. It is shown that the TMDI achieves enhanced structural performance and robustness to building and excitation uncertainties compared to same mass/weight TMDs.

Optimal design of semiactive MR-TLCD for along-wind vibration control of horizontal axis wind turbine tower


Present study aims to address the design of smart vibration control scheme for horizontal axis wind turbine tower using magneto-rheological tuned liquid column damper. With this in view, a reduced order model of the blade-tower system is used, considering centrifugal stiffening and gravitational effects that lead to time-dependent dynamic stiffness matrix. Aerodynamic load on the blades is modeled using blade element momentum theory. Semiactive control law in linear quadratic regulator framework is developed to mitigate the along-wind vibration of the tower. To implement the control law, multiblade coordinate transformation is adopted that converts the system matrices in the nonrotating framework to tackle its time dependency. The performance of the proposed control algorithm is demonstrated using numerical simulations with and without controller. Clipped optimality of the control force is imposed to keep the parameters of magneto-rheological tuned liquid column damper in the feasible range. Finally, sensitivity analysis is carried out to demonstrate the performance envelope of the proposed control algorithm for different operational scenario. Results presented in this paper clearly demonstrate that the proposed algorithm can be employed for effective along-wind vibration control of large HWAT tower.

Wave-based SHM of sandwich structures using cross-sectional waves


The identification of structural damage in composite waveguides is a critical issue in aerospace and transportation industries. Frequently, these structures involve periodic patterns or dissipative components that considerably reduce the range, robustness, and available bandwidth of ultrasonic structural health monitoring techniques. On the other hand, wave-based methods provide more accurate information on a defect's type, size, and location than modal analysis techniques. This paper focuses on a low-frequency wave-based method for structural integrity assessment of complex waveguides. The wave finite element method is employed to compute the dispersion curves of non-standard cross-sectional waves exhibiting increased strain energy. The spectral results are used to analyse the diffusion of guided elastic waves through representative localized defects in a laminated sandwich panel. To validate the diffusion model, reflection and transmission coefficients are determined for several wave pulses on typical defects using time-domain virtual experiments and cross-sectional energy acquisition. Results demonstrate that using cross-sectional waves provides a sensitivity to damage up to 2.8× higher than flexural waves in the low-frequency range. These results are explained by the presence of local resonances within the cross section, producing wavelengths in the transverse direction of propagation. These waves may prove suitable for cost-effective structural health monitoring applications because they can travel long distances through heterogeneous and periodic structures.

Optimal design of double-skin façades as vibration absorbers


In this paper, several layouts of double-skin façades (DSFs) used as mass dampers to reduce the vibrations in structures under seismic events are analyzed. First, the mathematical coupled problem is studied considering a non-classically damped system excited by a set of accelerograms. The design problem aims to determine the optimal values of four parameters, namely, the flexural stiffness and damping of the DSF panel and the stiffnesses of the elements that connect the DSF to the primary structure. Second, four objective functions are investigated. Two of these functions aim to minimise, respectively, the variance of displacements and accelerations of the primary structure for each earthquake record. The remaining two, instead, minimise the average of the displacements and accelerations calculated for all the selected accelerograms. Finally, numerical analyses are performed on a 6-storey building and four DSF designs are proposed. The particle swarm optimisation is used to estimate the optimal parameters. Comparisons among the DSF layouts are presented in terms of minima of the objective functions and in terms of energy transfer functions, and a simplified design method for the connection elements is discussed.

Using the signal-to-noise ratio of GPS records to detect motion of structures


Although major breakthroughs have been achieved during the last decades in the use of Global Positioning System (GPS) technology on structural health monitoring, the mitigation of the biases and errors impeding its positioning accuracy remains a challenge. This paper tests an alternative approach that can increase the reliability of the GPS system in structural monitoring by using the spectral content of the signal-to-noise ratio (SNR) of GPS signals to detect frequencies of antenna vibrations. This approach suggests the potential of using SNR data analysis as a supplement to low-quality positioning solution or as a near real-time alert of excessive vibration proceeding the position solution calculation. Experiments, involving a GPS antenna subjected to vertical vibrations of 0.4- to 4.5-cm amplitude at a range of frequencies between 0.007 and 1 Hz, examine the dynamic multipath-induced SNR response corresponding to the antenna motion. Synchronised fluctuations in the SNR time series were observed to reflect the antenna motion and their spectral content to include the frequencies of motion. SNR records from the GPS monitoring of the Wilford suspension bridge were used to validate the SNR sensitivity to controlled vibrations of the bridge deck. The natural frequency of 1.64 Hz was extracted from SNR measurements using spectral analysis on a 6-mm amplitude vibration, and the frequency of the semistatic displacement (∼0.02 Hz) was revealed in the SNR records permitting, after appropriate filtering, the estimation of a few millimetre semistatic displacement from the GPS time series without the need for any other sensor.

The wavelet transform as a Gaussian process for damage detection


This paper presents a novel statistical model for the wavelet transform of the acceleration response of a structure based on Gaussian process theory with applications to earthquake damage detection. The proposed model considers the wavelet coefficients at each time sample as a realization of a Gaussian process that depends solely on the damage state of the structure. Damage is then detected by identifying changes in the distribution of the model parameters. The model is purely data driven; it requires no prior knowledge of the structural properties, and all the parameters are learned directly from the measured data. The estimation of the model parameters is transformed to an optimization problem and the convexity of the objective function is investigated. An efficient algorithm for the parameter estimation is proposed and tested for accuracy. Finally, the statistical model is applied to the data obtained from a series of shake table experiments conducted at the University of Nevada, Reno. The results of the application of the proposed statistical model and implementation methodology are presented, and the validity of the model assumptions and damage detection capability are illustrated. A damage detection scheme based on the model parameters and statistical hypothesis testing is proposed and evaluated using the experimental dataset.

Multiresolution Bayesian nonparametric general regression for structural model updating


A novel Bayesian method, namely, multiresolution Bayesian nonparametric general regression (MR-BNGR), is proposed for structural model updating using modal data, that is, identified natural frequencies and mode shapes. In this method, the model updating problem is posed as a non-linear regression problem from the modal data to the structural parameters. The proposed method is nonparametric, so it does not require an explicit functional form of this mapping. Instead, it utilizes the input–output data to adaptively model its relationship. Its multiresolution nature allows to zoom into the significant region in stages to search the optimal point. Furthermore, the estimation uncertainty can be quantified. Training of the MR-BNGR network is very straightforward and computationally economical. Examples of a 20-storey shear building and a three-dimensional truss are provided to demonstrate the capabilities of the proposed MR-BNGR method, and the results confirm the effectiveness of this novel method.

Ambient vibration test-based deflection prediction of a posttensioned concrete continuous box girder bridge


Ambient vibration test generally only outputs basic modal parameters including frequencies, damping ratios, and unscaled mode shapes, which cannot directly support decision making of structural maintenance and management. In this article, structural deep-level parameters including unscaled and scaled flexibility identification of a posttensioned concrete continuous box girder bridge are studied by performing ambient vibration test, which is able to predict structural deflections by multiplying the static load with the identified flexibility. Ambient vibration test of the bridge and basic modal identification are firstly performed. Then, the method of unscaled flexibility identification is proposed by investigating the relationship between the frequency response function estimated from ambient test data and the analytical one. Finally, a mass-changing strategy is utilized to identify the scaled flexibility from output-only data, in which the key issue is to identify mass-normalized scaling factors by performing ambient vibration tests of tested structure before and after changing its mass. Numerical simulation of a simply supported beam and field test of a three-span bridge has been conducted to verify the capability and reliability of the proposed method. The good agreement between the predicted deflections from the identified flexibility and those measured from the static test successfully illustrates the effectiveness of the proposed method.

An improved equivalent force control algorithm for hybrid seismic testing of nonlinear systems


The equivalent force control (EFC) algorithm is a hybrid seismic testing method based on both an implicit integration algorithm and force feedback control. As it performs the computation of the numerical substructure with a fixed sampling number and some evaluations are not necessary, the EFC method is believed to be time-consuming for seismic testing of nonlinear systems with complicated numerical substructure model. In order to tackle this problem, the EFC method with varying sampling number (vEFC) has been conceived. The analysis of the vEFC method has shown that 2 traditional pseudodynamic testing (PDT) variants on the basis of implicit time integration schemes and numerical iteration, that is, the IPDT1 method and the IPDT2 method, can be recovered from the vEFC method. Moreover, the advantages of the vEFC method, such as fast response rate and compensation for control errors and possible slippage, are demonstrated.

Modeling method for predicting seepage of RCC dams considering time-varying and lag effect


This paper deduces the expressions for equivalent water level and equivalent rainfall. Different factors and methods were considered, such as the lag characteristics of the reservoir water level and rainfall on the seepage of roller-compacted concrete dams, combining the characteristics of layered pouring of the dam body, the time-varying effects of the factors affecting dam seepage, statistical regression, multilevel recursive method, and the numerical analysis method of the model with its corresponding implementation procedures. The safety monitoring model of spatial seepage, which can comprehensively reflect the seepage characteristics of roller-compacted concrete dams is set up. The engineering example shows that this model is obviously better than the statistical model in terms of fitting accuracy and searching ability. The forecast results of this model closely approach the actual monitoring state of the dam and can also be applied to the analysis of the foundation and bypass seepage of dams.

A statistical model of deformation during the construction of a concrete face rockfill dam


Monitoring data collected during dam construction are important in complete series of monitoring data. These data play a significant role in dam safety monitoring and the analysis of structural conditions. The traditional statistical model of the deformation of a concrete face rockfill dam (CFRD) with filling height and time factors is associated with serious multicollinearity issues during the construction phase. This study uses the Longbeiwan CFRD as an engineering model, and the internal settlement of the dam is the research focus. The traditional statistical model of deformation includes internal settlement data from the construction period and the filling height factor. Subsequently, the filling height component of the statistical model is established, and an improved statistical model is proposed with additional factors not included in the traditional statistical model. The model analysis indicates that the improved statistical model can effectively eliminate or reduce multicollinearity issues between the filling height and time factors in the traditional statistical model. The model analysis also provides a new and reasonable modeling approach for quantitatively analyzing deformation monitoring data during CFRD construction.

Identification framework for cracks on a steel structure surface by a restricted Boltzmann machines algorithm based on consumer-grade camera images


This paper proposes an identification framework based on a restricted Boltzmann machine (RBM) for crack identification and extraction from images containing cracks and complicated background inside steel box girders of bridges. The original images that include fatigue crack and other background information are obtained by a consumer-grade camera inside the steel box girder. The original images are cut into a number of elements with small size as the input dataset, and a state representation vector is artificially labeled to every image element used for the crack identification. A deep learning model or network consisting of multiple processing RBM layers to learn the abstract features is constructed to match the input image elements with corresponding state representation vectors. Next, a three-layer RBM with 500; 500; and 2,000 hidden units is trained as the hidden layers in the deep learning network. A contrastive divergence learning algorithm is employed for training the deep network to update and obtain the optimal parameters (i.e., the biases and weights). The new input image elements labeled as crack are sorted out and assembled to form an output image. A deep network is modeled through the consumer-grade camera images containing cracks and complicated background information using the proposed approach. The accuracy and ability to identify cracks from new images with different resolutions using the trained deep network are validated. Furthermore, effects of element size on reconstruction error and identification accuracy are investigated. The results show that there exists optimal element size; that is, too small and too large element sizes both increase the reconstruction error and decrease the identification accuracy.

Performance-based seismic design of multistory frame structures equipped with crescent-shaped brace


The primary objective of the “performance-based seismic design” is to provide stipulated seismic performances for building structures. However, a certain degree of design freedom is needed for matching a specific seismic response. This design freedom is not obtainable by the conventional lateral resisting systems because their stiffness and strength are coupled. Here, we put emphasis on the role of the unconventional lateral resisting systems in adding more flexibility to the design. In this paper, we seek to explore the seismic design of moment-resisting frame structures equipped with an innovative hysteretic device, known as “crescent-shaped brace.” One conspicuous feature of this device is its distinctive geometrical configuration, which is responsible for the enhanced nonlinear force-displacement behavior exhibited by the device. A new performance-based approach for the seismic design of the crescent-shaped brace is proposed. The performance of the device is evaluated, and its application in multistory shear-type structures is investigated. Two case studies were established to illustrate the design methodology. The first is a new two-story RC structure, and the second is an existing three-story RC structure. Nonlinear time history and pushover analyses are performed to evaluate the behavior of the controlled structures. The analyses show that for each of the two case studies, the acceleration–displacement capacity spectrum conforms to the performance objectives curve. This finding confirms the validity of the proposed design approach and the effectiveness of the new hysteretic device in resisting lateral forces.

Energy regenerative tuned mass dampers in high-rise buildings


This study investigates a novel energy regenerative tuned mass damper (TMD) with dual functions—vibration control and energy harvesting—in a high-rise building. The energy regenerative TMD consists of a pendulum-type TMD, an electromagnetic damper, and an energy-harvesting circuit. A simple optimal design method for energy regenerative TMD is proposed, in which a fixed duty-cycle buck-boost converter is employed as the energy-harvesting circuit to optimize the energy-harvesting efficiency and damping coefficient of the TMD. This study is organized into two main tasks: (a) characterizing and modeling the energy regenerative TMD through laboratory testing of a scaled prototype and (b) evaluating the vibration control and energy-harvesting performance of the energy regenerative TMD when applied in a 76-story wind-excited benchmark building in consideration of the nonlinearities in the energy regenerative TMD. The simulations reveal that the harvested electric power averages from hundreds of watts to kilowatts level when the mean wind speed ranges 8–25 m/s. Meanwhile, the building vibration is mitigated with the control performance comparable to the optimally designed passive TMD in a wide range of wind speed. The results in this study clearly demonstrate the effectiveness of the dual-function energy regenerative TMD when applied to building structures.

Wavelet energy ratio index for health monitoring of hysteretic dampers


This paper presents new contributions to evaluate the damage suffered on a particular type of hysteretic damper called web plastifying damper (WPD) for the passive control of structures subjected to earthquakes. WPDs consist of several I-section steel segments arranged to form a brace-type structural element. Energy input by the earthquake is dissipated by the WPD through plastic deformations of the web of the I-sections. These devices, properly installed in reinforced concrete test models, were tested under successive seismic simulations of increasing magnitude with a shaking table. To assess the damage of the web of the I-section after each seismic simulation, a new damage index called wavelet energy ratio (WER) was developed; it uses the signals collected by piezoelectric sensors in simple vibration tests. The index is based on wavelet package decomposition and energy calculation of properly chosen wavelet coefficients. It was correlated with a mechanical energy-based damage index—ID—proposed in past research, which has proven to accurately characterize the level of damage yet requires costly instrumentation to acquire the load–displacement curve needed for its computation. The experiments reported in this paper demonstrate a good correlation between WER and ID indices in a realistic seismic loading scenario. On the basis of this correlation, it is possible to estimate ID indirectly from the WER, which involves much simpler and less expensive instrumentation, easily applicable for in situ continuous monitoring of the dampers.

Multisource information fusion-based approach diagnosing structural behavior of dam engineering


Considering the effect of many factors on structural behavior, the diagnosing problem on structural behavior of dam engineering is investigated. Dempster–Shafer theory of evidence (DST) and set pair theory (SPT) are combined to fuse the multisource space–time information on dam safety. The structural behavior of dam engineering is identified and its development is forecasted by implementing the information fusions with 3 levels, namely, data fusion, feature fusion, and decision fusion. First, a multisource information fusion system on dam safety is built and an information fusion-based flowchart is presented to diagnose the dam structural behavior. Second, the batch estimation algorithm is adopted to implement the data fusion on same type information. Third, DST and SPT are applied to the decision fusion on heterogeneous information of dam safety. The index connection number and partial connection number in SPT are introduced to determine the basic probability assignment in DST and identify the dam structural behavior, respectively. Last, one actual dam undergoing structural reinforcements is taken as an example. Its structural behavior is diagnosed, and the reinforcement effect is assessed. It is indicated that the proposed approach is more suitable to be used to evaluate the safety status and reinforcement effect of dangerous dam.

Hybrid simulation of structural systems with online updating of concrete constitutive law parameters by unscented Kalman filter


Online model updating in hybrid simulation (HS) can represent an effective technique to reduce modeling errors of parts numerically simulated, that is, numerical substructures, especially when only a few critical components of a large system can be tested, that is, physical substructures. As a result, in an enhanced HS with online model updating, parameters of constitutive relationship can be identified based on experimental data provided by physical substructures and updated in numerical substructures. This paper proposes a novel method to identify constitutive parameters of concrete laws with unscented Kalman filter (UKF). In order to implement UKF, parts of the source codes of the OpenSEES software were modified to compute estimated measurements. Prior to experimental HS, a parametric study of UKF constitutive law parameters was conducted. As a result, the effectiveness of the UKF combined with OpenSEES was validated through numerical simulations, a monotonic loading test on a concrete column and real-time HSs of a reinforced concrete frame run with both standard and model-updating techniques based on UKF.

Active detection of block mass and notch-type damages in metallic plates using a refined time-reversed Lamb wave technique


A recently proposed refined time-reversed Lamb wave method for baseline-free damage detection is tested experimentally for detecting block mass and notch-type damages in isotropic plates. The experimental results were compared with finite element simulations. The frequency of best reconstruction has been determined experimentally for the actuator–plate–sensor system by performing the time reversal process for a range of frequency, which is found to be very different from the sweet spot frequency exciting a single mode, hitherto recommended for improving the performance of the time reversal process-based techniques. It is shown that the damage indices (DIs) computed by using the conventional main wave packet of the reconstructed signal are less sensitive to the presence of damage, which is consistent with some recently reported experimental results by other groups. The present method with extended wave packet shows excellent sensitivity to damage for both block mass and notch-type damages and also ensures a low threshold for the undamaged case when used at the best reconstruction frequency. The refined DIs reflect the true severity of damage. It was observed that a putty on the plate has no significant change in the DIs in the present method, whereas a baseline method would identify it as a damage due to very significant scattering by the putty.

Free parameter search of multiple tuned mass dampers by using artificial bee colony algorithm


In optimization of multiple tuned mass dampers (MTMDs), certain restrictions or preconditions such as uniform distribution of stiffness, mass, or frequency spacing had been applied for simplification, but in turn, solution of individual stiffness and damping parameters are not the true optima. The main purpose of this paper is to obtain the true optima of individual stiffness and damping parameters of MTMD system. In the proposed method, parameters of TMD units are treated as free search optimization variables, and an efficient optimization algorithm, namely, artificial bee colony algorithm has been utilized in obtaining optimum parameters of MTMDs. Performance proposed method with respect to uncontrolled structure is verified through numerical analyses and compared with other reported methods. Comparisons show a superior performance of proposed approach. The basic properties of optimum design, the effectiveness, and robustness with respect to number of dampers are also discussed.

Structural control with tuned inertial mass electromagnetic transducers


This paper investigates the validity of the tuned inertial mass electromagnetic transducer (TIMET) applied to building structures subjected to seismic motions. The TIMET is a device inspired by two innovative structural control devices proposed recently, that is, tuned viscous mass damper and electromagnetic transducer. The TIMET consists of a spring, an inertial mass produced by a ball screw mechanism, and an electromagnetic transducer part composed of a motor and an electrical circuit. The stiffness of the spring is tuned such that the inertial mass resonates with the vibrating building. This makes the motor installed in parallel with the inertial mass run up in an efficient way, and the vibration energy is converted to electrical energy effectively. As a result, vibration of the building decays fast and electrical energy is stored. This generated energy that is reusable for the self-powered control systems, structural health monitoring, emergency power source, and so on. In this paper, through numerical simulation studies employing the scaled three-story building model proposed for benchmark studies, the vibration reduction and energy harvesting capabilities of the TIMET is explored and the application potentiality to civil structures is discussed.

Investigation of wind load on 1,000 m-high super-tall buildings based on HFFB tests


This paper studies the wind load on 1,000 m-high super-tall buildings and provides basic reference for design, including the utilization of passive and active control devices. High-frequency force balance wind tunnel tests of super-tall buildings with different height are carried out to investigate the effects of building height and wind flow on the wind load. Both monsoon and typhoon climate wind flows are simulated based on target models suggested in literatures. The simulation of typhoon climate wind flows is carried out by a newly developed technique. The analysis of the experimental results confirms that the aerodynamic force is very sensitive to both building height and wind flow. In monsoon climate, the turbulence intensity decreases on increasing the height above ground. Thus, on increasing the building height, vortex shedding becomes increasingly intense and excites stronger structural vibrations in the across-wind direction, though the across-wind fluctuating overturning moment coefficient is almost the same. In typhoon climate, both the mean and the fluctuating overturning moment coefficients increase with the building height. This is mainly caused by the decreasing mean wind speed. The vortex excitation becomes weaker on increasing the building height, and this phenomenon is different from that observed in the monsoon climate. In order to better explain vortex-shedding excitation, a new parameter referred to as the characteristic turbulence intensity is defined herein as a weighted mean value of the turbulence intensity in the range of the building height. It provides a robust interpretation of the vortex excitation of super-tall buildings located in different wind flow and climate conditions.

Enhanced hybrid active tuned mass dampers for structures


Based on the recent research by Li and Cao in 2015, now taking the stroke mitigation as a target, the enhanced hybrid active tuned mass dampers (EHATMD) have been proposed in order to attenuate undesirable oscillations of structures under the ground acceleration. In accordance with the mode generalized system in the specific vibration mode being controlled (simply referred herein to as the structure) and continuing to make use of the negative normalized acceleration feedback gain factors scheme, the dynamic magnification factor (DMF) has been formulated for the structure furnished with an EHATMD. Then, the criterion for the optimum searching can be determined as the minimization of the minimum values of the maximum DMF (min.min.max.DMF). Employing the genetic algorithm, the effects of varying the key parameters on the optimum performance of EHATMD have been scrutinized in order to capture the expected performance. Furthermore, for a comparison, the optimum results of hybrid active tuned mass dampers (HATMD) with the same initial design parameters using both the genetic algorithm and negative normalized acceleration feedback gain factor scheme are also taken into consideration. Results of analysis have demonstrated that EHATMD outperforms HATMD and thereby may be regarded as a novel extension of HATMD.

Damage imaging in composites using nonlinear vibro-acoustic wave modulations


The paper deals with the application of nonlinear vibro-acoustic modulation technique for detection and localization of impact damage in a laminated composite plate. An imaging procedure—based on the nonlinear vibro-acoustic modulation sidebands—is proposed. The procedure relies on simultaneous low-frequency modal and high-frequency ultrasonic excitations. Laser scanning vibrometry is used to analyze the amplitude of modulation sidebands in vibro-acoustic responses. This analysis is performed for different positions on monitored structure to reveal the location and shape of damage. The method is illustrated using a simple example of impact damage detection in a composite plate. The experimental damage detection results are compared with the results obtained from the previously used approach on the basis of higher harmonic generation. The proposed method demonstrates better ability to locate damage in these comparative tests without the need to increase the measurement bandwidth to the higher harmonics regime. The work shows that the local defect resonance analysis can improve damage detection results of both compared approaches.

Monitoring the behavior of segment joints in a shield tunnel using distributed fiber optic sensors


Shield tunneling is a popular tunnel construction technique for its efficiency and speed. However, uncertainties associated with site soil conditions, past loading histories and analytical modeling, can result in performance issues. To monitor shield tunnels and ensure performance and safety, fiber optic sensing technique is proposed. Based on Brillouin optical frequency domain analysis, the technique can monitor the opening and closing of segmental joints in shield tunnels with high sensitivity. To determine tunnel lining segment displacement, different fixed-point spacings have been tested in the lab. The test results show that the difference in fixed-point distances had no impact on the test accuracy and the sensing cable with 0.9-mm polyurethane sheath coater has the best performance. For demonstration, the Brillouin optical frequency domain analysis-based monitoring technique is applied to the Suzhou Metro Line 1 tunnel for tunnel lining segment joint monitoring. The technique detected minor deformation of the segment joints in tunnels in operation and located leakages within the tunnel. The technique further identified that the minor deformations of the segment joints and track bed expansion were closely associated with temperature variations.

Static structural system identification for beam-like structures using compatibility conditions


Due to the inevitable noise existing in the measured responses, structural system identification is often a challenging task in terms of the accuracy of the estimations. Structural system identification by the observability method, which is characterized by the analysis of null spaces, is a powerful tool to determine the observability of structural parameters. However, it did not cope well with measurement errors so far. In this paper, for the first time, functional relations among displacements, denoted by the term compatibility conditions, in beam-like structures are derived by the observability method. Then, compatibility conditions are imposed in an optimization procedure to minimize the discrepancy between the measured response and the compatible one. The compatible response obtained by the optimization is used to obtain the final estimations of the parameters. In a simply supported bridge example, the proposed method is thoroughly evaluated regarding the number of measurements, error levels, and load cases. In an example of a continuous bridge, different load cases are used to estimate the bending stiffnesses of different zones. The accuracy and the efficacy of the proposed method are verified by the numerical results.

Mode decomposition of structures with closely distributed modes and nonclassical damping


It is difficult to apply traditional modal analysis methods to structures with nonclassical damping or closely distributed modes, because the damping matrix is not diagonalized by the modal matrix obtained from the mass and stiffness matrices. In this paper, a new mode decomposition method for structures with nonclassical damping and very closely distributed modes is proposed. This method defines the generalized modes in state space and uses differential state variables constructed from measured acceleration responses to decompose modal responses. A Kalman filtering approach is utilized to calculate the linear transformation matrix of governing modes, and the linear transformation matrix is updated in the optimization process of the objective functions integrated with the power spectral density of a target mode. The two performance functions are proposed to maximize the energy at a certain mode and to minimize the differences between the decomposed modal power spectrum and averaged power spectrum, assuming that each mode has a monochromatic signature with one natural frequency and one damping ratio. To verify the proposed method, a numerical simulation is performed using a single degree of freedom system coupled with a tuned mass damper that represents a nonclassically damped system with closely distributed modes. The results from the simulations show that the proposed method estimates the modal responses more precisely than conventional mode decomposition methods such as the independent component analysis method.

Contactless safety evaluation of damaged structures through energetic criteria


The reinforced concrete structures need to be monitored to ensure their structural integrity, but sometimes those measurements are very local, and the instrument is complex to locate physically in the structure and may interfere on it. Digital Image Correlation is a noncontact and nondestructive experimental technique capable to measure the displacement field in a big region of a structure with a great accuracy. This allows extracting valuable information from the fracture processes of reinforced concrete structures, critical for the evaluation of the structural integrity. The measurement of the energy dissipated by the structure is essential for the identification of the strength mechanisms that are failing in the structure and to identify a proper repair. Also, using fracture mechanics, other valuable information are extracted from the fracture processes of the reinforced concrete beam, such as the Modes I and II fracture energy released at each loading step, which is essential to evaluate the elastic energy that the structure can accumulate before collapse. The examples enable to anticipate the importance of Digital Image Correlation for future large scale studies of fracture in concrete and other materials related to construction.

Overhead water tank shapes with depth-independent sloshing frequencies for use as TLDs in buildings


Sloshing water in the overhead water tank of a multi-storeyed building may be utilized to act as a tuned liquid damper for vibration control under wind and earthquake excitation. In conventional rectangular or circular water tanks, tuning presents difficulties as the sloshing frequency varies significantly with change in the depth of water in the tank. To address this issue, in this paper, we find shapes of tanks wherein the sloshing frequency is essentially independent of water depth over a large and useful range of water levels. Both two-dimensional as well as axisymmetric (three-dimensional) tank shapes are found. We use a direct boundary element method to find the sloshing frequencies in each case. In each case, a tentative simple analytical form for the tank shape is chosen with three free parameters, and these parameters are adjusted to obtain shapes where the first lateral sloshing frequency has negligible variation with water depth. For axisymmetric tanks, the circumferential (azimuthal) variation in field variables is restricted to the first harmonic, in the interest of lower computational effort. For both planar and axisymmetric cases, the working range of water depths is taken to be from 0.2 to 2 times the tank width. In both cases, the variation in first lateral sloshing mode frequency is found to be under 0.2% over the working range. In comparison, for constant width tanks such as the rectangular or circular ones, over the same range of water depths, the corresponding variation is more than 60 times greater.

Automated damage detection in miter gates of navigation locks


Navigation locks are critical infrastructure components, and their closure for maintenance and repair can have significant impacts on the global economy. The current state of inspection and monitoring of lock components is generally to close the lock and perform a visual inspection. Whereas structural health monitoring of navigation locks is gaining acceptance, automation of the structural health monitoring process is lacking. This paper reports on efforts to develop an automated damage detection system for miter gates of navigation locks. The study focuses on using strain gage measurements to identify the redistribution of load throughout lock gates in the presence of damage. To eliminate the environmental variability in the data, a new damage-sensitive feature is introduced, termed here as “slope” and defined as the derivative of the strain with respect to the water levels in the lock chamber. The slopes form a new, stationary time series effectively purged of environmental effects. A principal component analysis, a method of analyzing multivariate, stationary time series, is then used to detect significant changes in the statistics of slopes as an indication of damage. To validate the approach, damage is simulated in a finite element model, and the resulting changes in strain from the finite element model are superimposed on the measured data. The results demonstrate the potential of the proposed approach for detecting damage in navigational lock gates.

Active neural predictive control of seismically isolated structures


An online identification and control scheme based on a wavelet neural network (WNN) and model predictive control (MPC) are presented. The WNN comprises a backpropagation neural network with wavelet activation functions and a parallel feedforward term. The WNN is used to identify the structural system, and the model is used to provide the predictions for MPC. The backpropagation network parameters and the controller are trained by the gradient descent algorithm to minimize performance indices. The feedforward component is trained using recursive least squares. The latter is found to drastically reduce the number of hidden layer neurons and significantly reduce the computational load of the neural network. Due to the general structure of the controller, its performance is satisfactory even under the strict condition imposed by a fixed learning rate. The efficacy of the control was demonstrated through a series of computational simulations of a 5-story seismically isolated structure with conventional lead-rubber bearings. Significant reductions of all response amplitudes were achieved for both near-field (pulse) and far-field ground motions, including reduced deformations along with corresponding reduction in acceleration response. In particular, the controller effectively regulated the apparent stiffness at the isolation level.

Theoretical evaluation of the measurement accuracy of fiber Bragg grating strain sensors within randomly filled asphalt mixtures based on finite element simulation


Strain sensor is a crucial component in pavement response monitoring, and its measuring accuracy is vital to the evaluation and prediction of pavement performance. However, measurement variability and biases are unavoidable in nature due to the inherent granular characteristics of the asphalt mixture and the inclusion of the embedded strain sensor, respectively. In this study, a certain amount of 4-point bending beams, which were filled with random aggregates and asphalt mortar utilizing the finite element method, were constructed to represent the variability of the conventional dense asphalt mixture AC-13. Fiber Bragg grating sensor models of various lengths, anchor radii, and encapsulating moduli were then inserted into these bending beams to analyze the inclusion effect of the embedded strain sensor. The simulation results illustrated the diverse effects of the different geometries and moduli of embedded sensors on the stress and strain states of the asphalt mixture. From a purely theoretical perspective, a calibration equation was proposed between the theoretical value that represented the equivalent strain of the asphalt mixture and the measured value that was calculated from the sensor model. Multifactor variance analysis and multiple comparison procedure were applied to evaluate the measurement accuracy and to optimize the geometries and moduli of sensors. This research provides a basis for optimizing strain sensors employed in asphalt pavements and offers a novel insight toward the response measurement for granular materials.

Acoustic emission source locating in two-layer plate using wavelet packet decomposition and wavelet-based optimized residual complexity


Health monitoring based on acoustic emission principle needs precise time delay estimation in two-layered plate-type structures. In this paper, the theories of wavelet packet decomposition, wavelet-based optimized residual complexity (WORC), and frequency-varying velocities were used to acoustic emission source locating. A rectangular array of the four sensors was used to locate acoustic emission source. By wavelet packet decomposition, specific packets with frequency range of 0–250 kHz were selected for more signal processing. Then WORC of specific packets of captured signals was calculated as a similarity measure technique. The time delay was estimated when WORC function reached the minimum value. The group velocity was obtained using dispersive curves. The experiments were carried out, and the results of locating error showed the high precision of the proposed algorithm.

An enhanced energy vibration-based approach for damage detection and localization


This paper addresses the enhanced identification and localization of structural damage by means of the recorded response induced by ambient excitation. Damage detection is based purely on the vibration energy in structural acceleration records, deriving thereof the normalized cumulative power spectral density as the characteristic damage sensitive quantity. As key aspect of this contribution, a method for “correction” of the recorded response is proposed, to account for deviations from perfect stationary white noise excitation. Based on an overdetermined system of equations, recorded spectra are modified to better fit previously recorded spectra. This fitting affects broader frequency ranges, while the damage sensitive feature captures changes in narrow frequency bands. Thus, the proposed “correction” method does not mask or remove the effects of structural changes in the response. Subsequent damage localization in cantilever-like structures is based on the changes of the drift of the fundamental mode shape amplitudes. The efficiency of the proposed two-step damage identification procedure is tested on a small-scale shear frame model in various damaged conditions. It is shown that the defined normalized cumulative power spectral density damage index is suitable to indicate most of the imposed damages, in particular when the proposed response correction methodology is applied. The spots of damage are successfully identified by the utilized mode shape damage indicator.

Particle impact dampers: Past, present, and future


Particle damping, an effective passive vibration control technology, is developing dramatically at the present stage, especially in the aerospace and machinery fields. The aim of this paper is to provide an overview of particle damping technology, beginning with its basic concept, developmental history, and research status all over the world. Furthermore, various interpretations of the underlying damping mechanism are introduced and discussed in detail. The theoretical analysis and numerical simulation, together with their pros and cons are systematically expounded, in which a discrete element method of simulating a multi-degree-of-freedom structure with a particle damper system is illustrated. Moreover, on the basis of previous studies, a simplified method to analyze the complicated nonlinear particle damping is proposed, in which all particles are modeled as a single mass, thereby simplifying its use by practicing engineers. In order to broaden the applicability of particle dampers, it is necessary to implement the coupled algorithm of finite element method and discrete element method. In addition, the characteristics of experimental studies on particle damping are also summarized. Finally, the application of particle damping technology in the aerospace field, machinery field, lifeline engineering, and civil engineering is reviewed at length. As a new trend in structural vibration control, the application of particle damping in civil engineering is just at the beginning. The advantages and potential applications are demonstrated, whereas the difficulties and deficiencies in the present studies are also discussed. The paper concludes by suggesting future developments involving semi-active approaches that can enhance the effectiveness of particle dampers when used in conjunction with structures subjected to nonstationary excitation, such as earthquakes and similar nonstationary random excitations.

Novel procedure for reliability-based cost optimization of seismically isolated structures for the protection of critical equipment: A case study using single curved surface sliders


The optimized reliability-based design of seismic isolated structures requires a consideration of the failure probability of the system, in addition to the optimization objectives. The stochastic nature of a given system (e.g., the probable input ground motion) must therefore be properly included in the analysis model. To address this challenge, a novel procedure is developed and examined on a 3-story isolated concrete building model, to minimize the total construction cost of the system with regards to protecting sensitive equipment located within the structure. In this procedure, the structure performance and reliability were first evaluated using time-consuming Monte Carlo simulations. We then employed artificial neural networks as a response surface to facilitate the prediction of the failure probability for the supposed structure. To simulate seismic excitations, we generated artificial ground motion combining random high-frequency and long-period components. Also, a newly developed sensitivity analysis method was used to identify the critical uncertain parameters of the system. Finally, by using a simulated annealing algorithm, we determined the optimal design variables of the structure and isolation system for a range of desired probabilities of failure. The optimal results indicate that, for different target failure probability ranges, some design variables are more significant than others.

Structural health monitoring of maglev guideway PC girders with distributed long-gauge FBG sensors


Health monitoring for maglev guideway PC girders is critical to ensure the safe operation of a high-speed maglev train. A long-gauge fiber Bragg grating (FBG) sensor has been recently developed to achieve the high-precision distributed macro-strain measurements and the capability of dynamic testing. This paper presents an integrated strategy for health monitoring of maglev PC girders equipped with the developed FBG sensors. Using the quasi-static measurements under the maglev train load that is uniformly distributed over the span, the deflection and the flexural stiffness of the PC girder can be evaluated. Using the dynamic measurements of the free vibration after the quick passing of the maglev train, the modal parameters of the girder is determined, based on which the flexural stiffness can be calculated in a different way. Using the long-term quasi-static measurements with no maglev train passing by, the deflection can be estimated due to the other effects such as temperature variation, concrete creep, or prestress loss. If assuming that the prestress loss is the only cause of the long-term deflection, the prestress loss can be determined according to its quantitative relation with the strain variation. Through analytical investigations and field testing on a typical maglev PC girder, the ability of the FBG sensors to evaluate the deflection, stiffness, modal parameters and prestress loss is validated.

The performance characteristics of misaligned bidirectional dynamic vibration absorbers


Bidirectional dynamic vibration absorbers (DVAs) can simultaneously reduce the resonant response of two perpendicular modes of lightly damped structures. The performance of the DVA is affected if its directions of motion are not aligned with the structural modes. When the DVA is misaligned, the 2D structure–DVA system is represented as a coupled 4-degree-of-freedom system. The efficacy of a DVA is often quantified using the concept of added effective damping. Novel formulae are derived that relate the added effective damping for each structural mode to the response covariance of the structure and DVA. It is shown experimentally and numerically that these expressions can be used to determine the added effective damping of a DVA using the responses of the structure and DVA. These expressions can be used to verify the in situ performance of a DVA, which has previously been challenging to do. Lastly, contour plots are created to investigate the performance characteristics of a 2D structure–DVA system for various DVA orientation angles, structural frequency ratios, and excitation amplitudes. The influence of these parameters on the added effective damping, reduction of the resultant root mean square structural response, and correlation between the two structural responses are considered. The trends shown in these contour plots enable the possible influence of DVA misalignment to be rapidly assessed.

Constrained observability method in static structural system identification


Identifiability of parameters in structural system identification (SSI) is of primary importance in any SSI method. It depends on the number and the location of the measurements, which is linked with sensor configuration. In this paper, under the framework of SSI by observability method (OM), the number of necessary measurements to identify all parameters of structural system was clarified first. Then, an example was solved step by step to show the lacking constraints among unknowns in SSI by OM. In a frame example, it was found that no measurement set having as many measurements as the number of unknowns was able to identify all parameters. To further understand this phenomenon, the observability of a simply supported beam was analyzed in an exhaustive way using 252 possible measurement sets. Three quarters of these sets were not able to identify all the parameters. In order to solve this issue, for the very first time, SSI by constrained observability method (COM), which appends the nonlinear constraints to SSI by OM, was proposed. With SSI by COM applied, the observability of the structural parameters with respect to the 252 sets was greatly improved. Finally, the efficacy of SSI by COM was verified by a 13-story frame building.

Mode shape-based damage identification for a reinforced concrete beam using wavelet coefficient differences and multiresolution analysis


In this paper, the structural mode shapes extracted from the finite element model of a simply supported reinforced concrete beam are employed for damage identification using different types of wavelets. To start with, the parity of signals, wavelets, and their convolution, that is, wavelet transform properties, are verified. In light of the mathematical modeling complexity of modal frequency, which relates to the localization and quantification of damage in the reinforced concrete beam, the maximum curves based on multiresolution wavelet transform coefficient differences and the corresponding theoretical assumptions are described and analyzed. It is concluded that the maximum curve reaches a peak value at a specific scale for a specific case, based upon which, a new mode shape based algorithm and damage index are proposed for damage identification. The accuracy of localization as well as the sensitivity of quantification is further discussed.

An energy harvesting and damage sensing solution based on postbuckling response of nonuniform cross-section beams


Postbuckling response of elastic beams has been widely used in many systems to develop efficient energy harvesting and damage sensing mechanisms under quasistatic excitations. In particular, the snap-through behavior of bilaterally constrained beams can be used to transform low-frequency and low-rate excitations into high-rate motions. Using a piezoelectric energy harvester, these motions are converted into electric power. However, the efficiency of buckling-based energy harvesters highly depends on the postbuckling behavior of the buckled elements. Inadequate control over the beam's response critically impedes the application of the mechanism. This study aims to control the location of the snap-throughs and the spacing between the transitions in order to increase the levels of the harvested energy and tune the sensitivity of the sensor. As uniform prismatic beams do not allow for such control, nonprismatic cross-section beams are herein investigated. An energy-based theoretical model is developed in this study to investigate the effect of different shapes and geometries on the postbuckling response of nonuniform beams. The total potential energy of the system is minimized under constraints that represent the physical confinement between the lateral boundaries. Experimental results prove that the theoretical model is accurate and can be used to optimize the buckling elements. Results show that the spacing between the transitions can be tuned. Furthermore, an optimal buckling element can improve the energy conversion efficiency by more than 290%.

Shear building stiffness estimation by wave traveling time analysis


A novel damage identification technique to estimate stiffness in a multistory building supported on solid ground is presented. Based on a shear building model, a 1-dimensional wave equation for a vertically propagating shear wave is derived. A Ricker pulse is used as excitation signal and propagated through the building. Wave propagation in the building is based on the Thomson–Haskell method, where each story is represented as a single layer in a multiple stratum model. The wave arrival times of the pulse at each story are used to calculate the stiffness of the columns. The involved calculations in this method grow only linearly with the number of stories, as opposed to other identification methods, as modal analysis, that grow geometrically; this makes this approach an interesting alternative method to asses building integrity. Simulation result for a building with heterogeneous characteristics across the stories confirms the feasibility of the proposal.

Demand-based optimal design of oscillator with parallel-layout viscous inerter damper


In this study, a demand-based optimal design method is proposed for an oscillator (a single-degree-of-freedom system) with a parallel-layout viscous inerter damper (PVID). The proposed design method overcomes some deficiencies of the existing method, which is based on the fixed-point theory and is mainly suitable for tuned mass dampers. Moreover, for the fixed-point method, the inherent damping of the primary structure is neglected, and the global optimal solution cannot be obtained. The proposed method can obtain a more rational and practical design for the actual design by minimizing both the response and the cost. The design problem of a PVID-equipped oscillator is transformed into a multi-objective optimization problem that can be solved using the ε-constraint approach, which is consistent with the concept of demand-based design. The dynamic response of the oscillator and the force of the PVID (i.e., the cost factor) are evaluated according to theories of random vibration to reduce the number of calculations required. A computer program is developed to perform demand-based parametric design of a PVID-equipped oscillator. Several design cases were examined under different excitation conditions using the computer program, and dynamic time history analyses were then conducted to verify the designs obtained. The results show that the proposed optimal design method identifies satisfactory designs more effectively than the existing method by obtaining PVID design parameter values that better meet the performance demand and simultaneously minimize the cost.

A new semi-active control based on nonlinear inhomogeneous optimal control for mixed base isolation


This paper presents a control algorithm for seismic mixed base isolation, combining passive isolators and semi-active viscous dampers. The objective is to limit base displacement while avoiding undesirable amplification of the response of the non-isolated modes. To this end, the proposed algorithm takes into account the constraints on the damping coefficient of the semi-active damper and information on the excitation. It is based on the approximate iterative solution, at each control time step, of a nonlinear inhomogeneous constrained optimal control problem. An autoregressive model is used to obtain, at each control time step, a prediction of the upcoming excitation in a short time interval ahead. Numerical simulation results demonstrate the efficacy of the above method, especially in improving floor response spectra, and its superiority with respect to clipped-optimal algorithms.

Damage detection in shear buildings using different estimated curvature


This study investigates the damage localization employing the curvature of the lateral displacement envelope in shear building structures. Both the finite difference method and the proposed interpolation method are applied to evaluate the curvature of mode shapes and frequency response functions (FRFs) in a 12-story shear building. The interpolated displacement function used in the proposed method considers appropriate continuity and boundary conditions for the shear buildings. Numerical studies show that using the curvature by the proposed method could reduce the occurrences of false damage localization when the vibration responses include small simulated noise. Moreover, the existing FRF curvature method could perform worse than random guessing to find correct damage locations at the cost of the considerable number of false alarms. However, the poor detection performance of the existing method may be enhanced significantly by using the proposed method to evaluate the curvature of the FRFs if the simulated noise is under a small level. The proposed method is shown to perform better than the finite difference method to improve the effectiveness of the curvature-based methods for damage detection.

Time synchronization for acceleration measurement data of Jiangyin Bridge subjected to a ship collision


State-space (SS) model is proposed to identify the time lag between the asynchronous accelerations at different locations of the Jiangyin Bridge measured during a ship–bridge collision. One of the accelerations is chosen as the reference signal, and the time axis of the rest of them are shifted relative to that of the reference signal with a series of shifting times. For each pair of reference and time shifted signals, SS models in correspondence to the shifting time series are formulated. Their system matrices are identified with data-driven stochastic subspace identification algorithm, and their model order is determined by Akaike's information theoretic criterion and final prediction error. If the 2 accelerations for model fitting are asynchronous, errors may be introduced into the SS model and its prediction error is expected to be greater than the counterpart obtained with synchronous accelerations. Therefore, the actual time lag between them is identified from the shifting time that corresponds to the minimum of loss function, which is used to map the prediction error vector sequence to a real number. In addition, asynchronous acceleration data measured 2 hr ahead of the ship–bridge collision and synchronous acceleration data measured long after the ship–bridge collision are also analyzed. The former dataset is exploited to evaluate the reproducibility of the SS model for time synchronization, and the latter dataset is utilized to examine its anti-false-identification capability. The results show that the SS model achieves a satisfactory performance in the identification of time lag for both asynchronous and synchronous measurement data.

Electromagnetic actuators for controlling flexible cantilever beams


Electromagnetic actuators are very important for scientific and industrial applications. Their use may vary within a wide range of possibilities due to their most important feature: the ability to apply known and controllable forces to elements or structures without contact. In this article, an application within this range is analyzed: a proportional-integral-derivative (PID) controller is used with a pair of actuators to control the dynamic forced response of a flexible cantilever metallic beam and to keep it at a given reference position. In order to achieve this objective, both the actuators and the controller need to be adjusted. For the actuators, the main parameters evaluated consider mounting particularities, such as the differential assembly and the influence of the air-gap distance over the magnetic flux density and the magnetic force provided. Next, a brief review of PID controllers is presented, highlighting 5 tuning methods, and their effects on relevant parameters of the electromagnetic system (such as the cutoff frequency). Finally, results focus on the comparative efficiency of the PID tuning methods to reduce the vibration amplitude of the beam bending modes. The results show that the Ziegler–Nichols modified for some-overshoot and no-overshoot methods are the best choices.

Investigation on a curvature-based damage detection method using displacement under moving vehicle


Detection of potential damages is of much significance for aging bridges, which has attracted extensive attention in recent years. In this paper, a damage detection method is proposed utilizing dynamic displacement of a bridge under a moving vehicle. First, the theoretical basis of this method is elaborated. The idea is to use the static component of displacement measurements under a moving vehicle, and to use the calculated curvature change to identify damage in bridges. In order to obtain the static component, a technique is proposed for curvature calculation. Second, the proposed method is verified with two examples. In the first example, a finite element model of a single span bridge under a moving vehicle is used to show reliability of the method. Both vehicle–bridge interaction and road surface roughness are considered in the analysis. Parametric study on damage intensity, data acquisition location, vehicle passing path, and damping ratio provides guidance for application in real bridges. In the second example, a field test on a prestressed concrete viaduct is conducted to calibrate its finite element model. Artificial damage, that is, concrete crack and tendon rupture, was created, and the proposed method is used to identify the damage. Analysis results show capability of the method. Finally, conclusions are drawn, and suggestions are given for application of the proposed method on damage detection of real bridges.

A novel model of dam displacement based on panel data


Deformation monitoring is the main program in the area of dam safety. Because statistical model is simple and intuitive, it is widely used in dam safety monitoring. However, in dam's displacement statistic model, there is a high degree of linear relationship between influence factors. Due to the influence of multicollinearity, models calculated with traditional methods are not accurate and stable. Besides, because of dam integrity, each part of dam is interrelated and interactive. Currently, single point or multipoints displacement monitoring models cannot accurately reflect the actual dam running state. In this paper, the theory of panel data is introduced to dam deformation analysis. Panel data contain time series data and cross section data, which is able to solve serious multicollinearity problem of traditional regression method. Moreover, all measuring points are classified into several groups according to their similar deformation law. Based on the random-coefficient model of panel data, potential relationship between different measuring points is built. Take 1 hydropower station, for example, to examine that random-coefficient model is able to improve the modeling situation that estimators are not significant and simultaneously provide a stable model, which explores a new approach for the research of dam displacement monitoring.

Generalized active disturbance rejection control of structures under seismic disturbance considering time delays


The active disturbance rejection control of a delayed 2-degree-of-freedom structure against earthquake motion force is investigated. A shaking table that resembles the acceleration profiles of most known earthquakes is used to generate the horizontal force. To compensate the motions caused by the earthquake simulator, an active tuned mass and damper system is attached to the structure. Due to the strong effects of the motion forces as a disturbance input, an active disturbance rejection controller including an extended state observer is designed and implemented. The controller designed is modified with including a state predictor to address the control input delays induced by the remote networked control or actuator delays. The stability of the whole system is verified via Lyapunov analysis and tested on the structure sample including shaking table. The results show the effectiveness of the proposed approach to regulate the structure motions in different earthquake scenarios.

Seismic retrofit of frame structures using passive systems based on optimal control


This paper proposes a new seismic modification methodology for optimal design of multistory frame structures to avoid damage and attain a robust response to extreme hazards. The methodology determines added damping devices of optimal size at strategic locations and modifies story stiffnesses, by solving a newly formulated constrained optimization problem. The objective is to minimize a cost function representing total energy while satisfying the equations of motion and allowable interstory drifts for given severe ground motions. The proposed methodology combines the classical linear quadratic regulator, which searches for an optimal gain matrix, with an analysis-redesign iterative procedure to produce a robust analysis redesign (RAR) iterative approach. A new algorithm approximates the equivalent stiffness to fit the displacement gains. At convergence, the RAR procedure will yield optimal sizing and new topology for the designed system. The RAR procedure is developed here for shear structures. However, RAR can be utilized for complex structures by modeling them first as equivalent shear-type structures having stiffness properties that yield the same maximum interstory drifts for the given records. Two numerical examples of shear-type structures are examined. These examples use structures already having an “optimal” configuration, which are further optimized using the methodology developed herein. In addition, a numerical example comprised of a 10-story moment resisting frame structure is presented to illustrate the use of the equivalent shear structure approach. The results of the exemplified retrofitted moment resisting frame structure show great improvements in its dynamic response.

Experimental and finite element investigation of temperature distributions in concrete-encased steel girders


The structural performance of bridge structures is temporal and is mainly controlled by the types of the applied loads. To continuously observe the structural performance of bridges, structural health monitoring sensors that include among many temperature sensors are used. The impact of nonuniform temperature distributions in bridge girders due to the environment thermal loads has been recognized by former researchers and bridge design codes. To evaluate these and other effects on the structural behavior of bridge structures, many field and experimental structural health monitoring studies were carried out. However, more researches are required to investigate the temperature distributions in other girder configurations. This work is directed to investigate the impact of air temperature and solar radiation on temperature gradient distributions in concrete-encased composite girders. For this purpose, an experimental concrete-encased steel girder segment was instrumented with thermocouples and other sensors. The experimental data recording continued for 6 months during the hot and cold seasons. Furthermore, a thermal finite element (FE) parametric study was conducted to investigate the effect of the girder size. The test results showed that the vertical and lateral temperature gradient distributions and the variation of the temperature gradients with time are controlled by the amount and location of the received solar radiations. The FE analysis showed that the daily temperature variations are higher in smaller girders, whereas the temperature gradients are smaller than in larger girders. Moreover, the FE results showed that the thickness of the girder's concrete members has an important impact on temperature gradients and temperature distributions.

Initial service life data towards structural health monitoring of a concrete arch dam


This paper presents a statistical framework to monitor the performance of an operational concrete arch dam using sensory data acquired during its initial service life. One of the major challenges in dealing with a newly constructed dam is to predict its long-term behaviour by forecasting appropriate thresholds using limited data exhibiting nonstationarity. In this paper, a hybrid model is implemented to predict dam responses using environmental—hydrostatic, seasonal, and temperature—as well as age-related variables. The data from multiple sensors are first analyzed using principal component analysis to incorporate overall dam behaviour into a prediction model. The proposed prediction framework is then employed to estimate the residuals and control limits required to calculate thresholds under nonstationary operating conditions during its initial service life. The dam performance is then monitored using statistical control charts and anomalies are detected by comparing the test statistics, square prediction error, and Hotelling T-squared, calculated from the residuals with the preset control limits. The issue of limited data is addressed by updating the model parameters and thresholds periodically, which is aimed at minimizing the false alarm rate. The proposed method is demonstrated using a 130-m-high double-arch concrete dam located in Bulgaria.

Battery capacity degradation prediction using similarity recognition based on modified dynamic time warping


Battery degradation prediction is a significant recent challenge given the complex physical and chemical processes that occur within batteries, various working conditions, and limited performance degradation data and/or ground test data. In this study, we describe an approach called dynamic spatial time warping, which is used to determine the similarities of two arbitrary curves. Unlike classical dynamic time warping methods, this approach can maintain the invariance of curve similarity to the rotations and translations of curves, which is vital in curve similarity search and can recognize the intrinsic relationship between two curves. Moreover, it can be applied for battery degradation prediction even when rare data are available and do not require special assumptions, which fulfill the requirements of degradation prediction for batteries subject to extreme limited available data. The accuracy of this approach is verified by using both simulation data and NASA battery datasets. Results suggest that the proposed approach provides a highly accurate path of predicting battery degradation even with very limited data.

Bayesian structural model updating using ambient vibration data collected by multiple setups


Structural model updating aims at calculating the in-situ structural properties (e.g., stiffness and mass) based on measured responses. One common approach is to first identify the modal parameters (i.e., natural frequencies and mode shapes) and then use them to update the structural parameters. In reality, the degrees of freedom that can be measured are usually limited by number of available sensors and accessibility of targeted measurement locations. Then, multiple setups are designed to cover all the degrees of freedom of interest and performed sequentially. Conventional methods do not account for identification uncertainty, which becomes critical when excitation information is not available. This is the situation in model updating utilizing ambient vibration data, in which the excitations, such as wind, traffic, and human activities, are random in nature and difficult to be measured. This paper develops a Bayesian model updating method incorporating modal identification information in multiple setups. Based on a recent fundamental two-stage Bayesian formulation, the posterior uncertainty of modal parameters is incorporated into the updating process without heuristics that are commonly applied in formulating the likelihood function. Synthetic and experimental data are used to illustrate the proposed method.

Proof of concept of wireless TERS monitoring


Temporary earth retaining structures help prevent collapse during construction excavation. To ensure that these structures are operating within design specifications, load forces on supports must be monitored. Current monitoring approaches are expensive, sparse, off-line, and thus difficult to integrate into predictive models. This work aims to show that wirelessly connected battery powered sensors are feasible, practical, and have similar accuracy to existing sensor systems. We present the design and validation of ReStructure, an end-to-end prototype wireless sensor network for collection, communication, and aggregation of strain data. ReStructure was validated through a 6-month deployment on a real-life excavation site with all but one node producing valid and accurate strain measurements at higher frequency than existing ones. These results and the lessons learnt provide the basis for future widespread wireless temporary earth retaining structure monitoring that increase measurement density and integrate closely with predictive models to provide timely alerts of damage or potential failure.

“Total displacement of curved surface sliders under nonseismic and seismic actions: A parametric study”


The re-centring capability is recognized as a fundamental function of any effective isolation system, not only because it is associated to small or negligible deformation at the end of the earthquake but rather because it prevents displacement build up that may limit the capability of the structure to withstand aftershocks and future earthquakes. The current Eurocode recommends to estimate the maximum total displacement of the isolated system as the superposition of the nonseismic offset displacement resulting from permanent actions, long-term deformations and thermal movements of the structure, and of the amplified seismic displacement induced by the design earthquake. For systems endowed with low re-centring capability, the estimation shall also account for the possible accrual of displacements during the lifetime of the structure. However, the aforementioned criteria have never been evaluated for curved surface sliders, which are characterized by an inherent nonlinear behaviour. The study aims at giving more insight into the matter by conducting a parametric study based on one-directional nonlinear response time history analyses and considering a variety of seismic scenarios. The first part of the study investigates the effect of a nonseismic displacement on the earthquake-induced displacement and formulates a criterion to evaluate the capability of curved surface sliders to provide a seismic response independent of the offset displacement. The response of the isolation system to natural sequences of earthquakes, where the offset displacement is the residual displacement from the previous shake, is addressed in the second part of the paper. The provisions of the Eurocode are eventually checked against the observed data.

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Utilization of structural health monitoring in long-span bridges: Case studies


Structural health monitoring (SHM) of bridges has gained rapid development in the past few years. This paper describes application of SHM on long-span bridges in China, with the aim to illustrate its practical value. A short review of its development and practice is firstly introduced. Three case studies are subsequently presented on utilization of SHM data in engineering practice. In the first case study, a ship collision incident is analyzed using SHM data. An alarm is sent and confirmed when the collision occurred, and mode parameters are identified with GPS measurements to evaluate the bridge condition. In the second case study, damage of expansion joints in a suspension bridge is assessed with girder end displacement measurements. Malfunction of viscous damper is found to correlate with cumulative displacement. The results show that cumulative displacement can be used for condition assessment of expansion joints. In the third case study, the performance of tuned mass dampers is evaluated with wind and vibration measurements before and after tuned mass damper installation. Through explanation of these case studies, the paper illustrates how to distill useful insights from SHM data, which could be instructive for further research in this field.

Experimental image and range scanner datasets fusion in SHM for displacement detection


Optical images and signals can be used to detect displacement in civil engineering structures. This paper presents a technical experimentation of a vision-based technology and artificial intelligence algorithms methodology for structural health monitoring of new and aging structures, by a noncontact and nondestructive system. The experimental study emphasis is on the outdoor urban environment, by the detection of spatial coordinate displacement on the structures, in order to perform a damage assessment. Also, the experimental study contains both theoretical and experimental aspects of the fusion of image and range scanner datasets created using intelligent algorithms. A camera and an optical scanning system were used to generate high resolution and quality images for 2D imaging, and 3D accuracy range data from optoelectronic sensor signals. Scans at a specific area of an engineering structure were performed to measure spatial coordinates displacements, successfully verifying the effectiveness and the robustness of the proposed non-contact and non-destructive monitoring approach.

Structural time-dependent reliability assessment of the vibration active control system with unknown-but-bounded uncertainties


The active control system for structural vibration is extremely sensitive to the parametric uncertainty so that more and more concerns of its reliability estimation have been given recently. In view of the insufficiency of the uncertainty information in practical engineering, a non-probabilistic time-dependent reliability method that combines the active vibration control theory with interval analysis is proposed in this paper to effectively estimate the dynamic safety of the controlled structures, in which circumstances the unknown-but-bounded uncertainties in structural parameters are considered. The uncertain structural responses based on the closed-loop control are firstly analyzed and embodied by the interval process model. By virtue of the first-passage theory, an integral procedure of non-probabilistic time-dependent reliability analysis of the active control system for structural vibration is then conducted. Two engineering examples and one experimental application are eventually presented to demonstrate the validity and applicability of the methodology developed.

Damage detection in beam and truss structures by the inverse analysis of the static response due to moving loads


The detection and the localization of damages in a bridge have been always one of the major concerns of infrastructure managers, engineers, and researchers. In addition to the dynamic techniques that were well imposed in the diagnosis of bridges, several static methods have been developed. The idea of this work is to exploit the measurement results about a bridge deflection submitted to a moving load. By using the displacements response, important data about the displacement of a structural point could be gathered. When the structure's geometry and the material characteristics are known, a finite element model, supposed to be the most similar, could be developed. The numerical structural model and the static displacements data are used to develop an equilibrium equations system where unknowns are the possible stiffness changes in the finite element model. Thus, the global stiffness matrix of the studied structure is a polynomial matrix. The equilibrium equations system is a static inverse problem requiring resolution. To facilitate the mathematical development, the inverse of the global stiffness matrix is expressed by a Neumann series. Then, the resolution of the system is done by a code developed in Matlab. To confirm the good convergence of the developed mathematical method, numerical tests are carried out by considering beams and a 3D truss bridge subjected to a moving load. Thereafter, an analysis concerning the influence of the noise in the displacements data on the accuracy of the inverse analysis and the convergence of the results is made. It has been shown that the large number of data reduces the noises effect and the damages detection can be ensured.

Crack propagation monitoring using an image deformation approach


An image deformation method is herein proposed to monitor the crack propagation in structures. The proposed approach is based on a computational algorithm that uses displacements measured by photogrammetry or image correlation to generate a virtual image of the surface, from an initial input to any given stage of analysis. This virtual image is then compared with the real image of the specimen to identify any discontinuities that appeared or evolved during the monitored period. The procedure was experimentally validated in the characterisation of crack propagation in concrete specimens. When compared with other image processing techniques, for instance, based on edge detectors, the image deformation approach showed insensitiveness to any discontinuity previously existing on the surface, such as cracks, stains, voids, or shadows, and did not require any specific surface treatments or lighting conditions. With this approach, the global crack maps could be extracted from the surface of the structure and extremely small changes occurring within a given time interval could be characterised, such as the movement associated with the opening of cracks. It is highlighted that the proposed procedure is general and therefore applicable to detect and characterise surface discontinuities in different materials and test set-ups.

Damage detection in elastic properties of masonry bridges using coda wave interferometry


Structures may be subjected to damage and deterioration over different timescales, and monitoring their health status may allow to perform maintenance actions before the functionality limit is reached. Masonry arch bridges, in particular, are sensitive to the bearings loss produced by scour of the streambed soil at the pier foundations. In this study, we measured the changes in the elastic properties of a 1:2 scaled model of a masonry arch bridge built in the laboratory to study the evolution of the damage mechanism related to the application of foundation movements. Specifically, the bridge is realized to model the effect of erosion of the ground underneath the central pier. We analysed the accelerometric records acquired along the structure generated by a sledgehammer hitting the bridge walls. We used the method of coda wave interferometry to detect the changes in the elastic properties of the medium. After selecting the specific frequency band exciting coda waves, we progressively measured the time lag between signals acquired in the intact and two damaged stages of the bridge for each source–receiver couple, and we fit the data to get the relative wave velocity changes. We found that the average relative velocity changes for the two damaged steps are Δv/v = −5.08 ± 0.08% and Δv/v = −8.2 ± 0.6%, consistently measured at all the analysed source–receiver couples. These values correspond to an average estimation of the velocity changes occurred within the structure, because the associated wavelengths are comparable with the bridge size and the damage is spread over a large portion of the structure.

Shake table real-time hybrid simulation techniques for the performance evaluation of buildings with inter-story isolation


Interstory isolation systems have recently gained popularity as an alternative for seismic protection, especially in densely populated areas. In inter-story isolation, the isolation system is incorporated between stories instead of the base of the structure. Installing inter-story isolation is simple, inexpensive, and disruption free in retrofit applications. Benefits include nominally independent structural systems where the accelerations of the added floors are reduced when compared to a conventional structural system. Furthermore, the base shear demand on the total structure is not significantly increased. Practical applications of inter-story isolation have appeared in the United States, Japan, and China, and likewise new design validation techniques are needed to parallel growing interest. Real-time hybrid simulation (RTHS) offers an alternative to investigate the performance of buildings with inter-story isolation. Shake tables, standard equipment in many laboratories, are capable of providing the interface boundary conditions necessary for this application of RTHS. The substructure below the isolation layer can be simulated numerically while the superstructure above the isolation layer can be tested experimentally. This configuration provides a high-fidelity representation of the nonlinearities in the isolation layer, including any supplemental damping devices. This research investigates the seismic performance of a 14-story building with inter-story isolation. A model-based acceleration-tracking approach is adopted to control the shake table, exhibiting good offline and online acceleration tracking performance. The proposed methods demonstrate that RTHS is an accurate and reliable means to investigate buildings with inter-story isolation, including new configurations and supplemental control approaches.

Using water hammer to enhance the detection of stiffness changes on an out-of-round pipe with distributed optical-fibre sensing


Over the last few decades, distributed optical fibre sensor (DOFS) has been introduced to monitor the structural health of water pipelines. Most of the previous studies show that DOFS is very effective as a static measurement and monitoring platform. However, there is still a lack of research being done using DOFS to monitor the dynamic response of the pipeline. This paper will first demonstrate the dynamic capability of optical frequency domain reflectometry-based DOFS on a pipe. To be specific, the primary monitoring work is conducted on an out-of-round plastic pipe subjected to water hammer. It is important to monitor the dynamic response of the pipe as it is well known that water hammer can occur in any pressurised pipeline system due to changes in the operating conditions. The ability to detect local stiffness irregularity on the noncircular pipe subjected to water hammer is also demonstrated. The result shows that the presence of the local stiffness change is accentuated when the pipe is subjected to water hammer. The dynamic capability of DOFS facilitates the application of water hammer as a stimulus and hence shows the potential to enhance pipeline health monitoring.

Performance of tuned tandem mass dampers for structures under the ground acceleration


It is widely acknowledged that the tuned mass damper (TMD) is one of the most effective and simplest passive control devices, but its limited control performance is still a troubling problem. In order to surmount the shortage of TMD, the tuned tandem mass dampers (referred herein to as TTMD) have been proposed for mitigating the undesirable oscillation of structures under the ground acceleration. Based on the formulation of the mode-generalized system in the specific vibration mode being controlled, the analytical expression is then derived for the dynamic magnification factor of the structure furnished with a TTMD. The optimum criterion can thereby be defined as minimization of the minimum values of the maximum dynamic magnification factor with a set of optimization variables embedded so as to give full play to the control device potential. The optimization implementation of TTMD is carried out by the MATLAB-based coding and debugging. For the purpose of a mutual authentication to the optimization results, three metaheuristic algorithms, namely, genetic algorithm, particle swarm optimization, and simulated annealing, are concurrently taken into consideration. Results demonstrate that the proposed TTMD endows with the superior stroke performance with respect to TMD.

Eulerian-based virtual visual sensors to measure dynamic displacements of structures


Vibration measurements provide useful information about a structural system's dynamic characteristics and are used in many fields of science and engineering. Here, we present an alternative noncontact approach to measure dynamic displacements of structural systems using digital videos. The concept is that intensity measured at a pixel with a fixed (or Eulerian) coordinate in a digital video can be regarded as a virtual visual sensor. The pixels in the vicinity of the boundary of a vibrating structural element contain useful frequency information, which we have been able to demonstrate in earlier studies. Our ultimate goal, however, is to be able to compute dynamic displacements, i.e., actual displacement amplitudes in the time domain. In order to achieve that, we introduce the use of simple black-and-white targets that are mounted on locations of interest on the structure. By using these targets, intensity can be directly related to displacement, turning a video camera into a simple, computationally inexpensive, and accurate displacement sensor with notably low signal-to-noise ratio. We show that subpixel accuracy with levels comparable to computationally expensive block matching algorithms can be achieved using the proposed targets. Our methodology can be used for laboratory experiments, on real structures, and additionally, we see educational opportunities in K-12 classroom. In this paper, we introduce the concept and theory of the proposed methodology, present and discuss a laboratory experiment to evaluate the accuracy of the proposed black-and-white targets, and discuss the results from a field test of an in-service bridge.

Control of underground blast induced building vibration by shape-memory-alloy rubber bearing (SMARB)


This paper focuses on the performance of shape-memory-alloy rubber bearings (SMARBs) compared to conventional lead-plug or New-Zealand (N-Z) bearings in control of building vibration due to underground blast induced ground motion (BIGM). The performance is evaluated with regard to maximum acceleration and isolator displacement obtained by nonlinear time history analysis. In doing so the Bouc–Wen's model is used to represent the nonlinear behaviour of the N-Z bearing and the superelastic behaviour of nickel–titanium-based shape-memory alloy is represented by the Graesser–Cozzarelli model. The underground BIGM input is modelled by exponentially decaying function. It is observed that though the N-Z bearing is fairly effective in controlling the structural accelerations due to BIGM without excessive bearing displacements, there remains a problem with the residual bearing displacements. The latter, however, is found to be dealt with very effectively by the SMARB. Furthermore, the procedure to obtain the optimum design parameters of the base isolators under study is obtained by optimizing two mutually conflicting objective functions, that is, the minimization of peak acceleration as well as peak bearing displacement by converting the multiobjective optimization problem to a single composite objective function. The improved and robust control performance of SMARB compared to N-Z bearing is elucidated through numerical study by considering a five-storied shear building frame.

Detecting structural damage to bridge girders using radar interferometry and computational modelling


The process for assessing the condition of a bridge involves continuously monitoring changes to the material properties, support conditions, and system connectivity throughout its life cycle. It is known that the structural integrity of bridges can be monitored by measuring their vibration responses. However, the relationship between frequency changes and structural damage is still not fully understood. This study presents a bridge condition assessment framework which integrates computational modelling and noncontact radar sensor techniques (i.e., IBIS-S) to predict changes in the natural frequencies of a bridge girder as a result of a range of parameters that govern its structural performance (e.g., elastomeric bearing stiffness, concrete compressive stiffness, and crack propagation). Using a prestressed concrete bridge in Australia as a case study, the research outcomes suggest that vibration monitoring using IBIS-S is an efficient way for detecting the degradation of elastomeric bearing stiffness and shear crack propagation in the support areas that can significantly affect the overall structural integrity of a bridge structure. However, frequency measurements have limited capability for detecting the decrease in the material properties of a bridge girder.

Inertial mass damper for mitigating cable vibration


Stay cables used in cable-stayed bridges are prone to vibration due to their low-inherent damping characteristics. Many methods have been implemented in practice to mitigate such vibration. Recently, negative stiffness dampers have gained attention because of their promising energy dissipation ability. The viscous inertial mass damper (VIMD) has been shown to have properties similar to negative stiffness dampers. This paper examines the potential of the VIMD to enhance the damping, and mitigate the vibration, of stay cables. First, a control-oriented model of the cable is employed to formulate a system level model of the cable–VIMD system for small in-plane motion. After carefully classifying and labeling the mode order, the modal characteristics of the system are analyzed, and the optimal damper parameters for the several lower frequency modes are determined numerically. The results show that the achievable modal damping ratio can be up to nearly an order of magnitude larger than that of the traditional linear viscous damper; note that the optimal parameters of the VIMD are distinct for each mode of interest. These results are further validated through analysis of the cable responses due to the distributed sinusoidal excitation. Finally, a case study is conducted for a cable with a length of 307 m, including the design of practical damper parameters, modal-damping enhancement, and vibration mitigation under wind loads. The results show that the VIMD is a promising practical passive damper that possesses greater energy dissipation capacity than the traditional viscous damper for such cable–damper systems.

Seismic resilience timber connection—adoption of shape memory alloy tubes as dowels


This study investigates a novel timber dowel-type connection system using superelastic shape memory alloy (SMA) bar and tubes as dowels, in order to provide self-centering effect. Double-shear connections with SMA and mild steel dowels were tested under dynamic loadings at different displacement levels. The results showed that SMA dowel-type connections have good self-centering behaviours and can mitigate the residual deformation effectively compared with steel dowel-type connections after excessive deformation; although the steel dowel-type connections present higher strength. These tests reveal that the connection with tube dowels show higher equivalent viscous damping ratio than those use solid bar as tube would allow larger deformation to dissipate energy. To demonstrate application of the benefit of this system, an analytical model of a 3-storey timber framed structure was built for parametric study. The results showed that the structures with conventional dowel-type type connections exhibit large unrecoverable deformation after timber framed structures experience an earthquake. In comparison, those with the connections developed in this project show limited unrecoverable deformation due to the self-centering capacity of the connections.

Radial basis function neural network algorithm for semi-active control of base-isolated structures


Curved surface slider (CSS) is considered as an effective isolation device for structures subjected to earthquake ground motions. Due to constant frequency, CSS may encounter a resonance problem when subjected to near-fault earthquake ground motions. To overcome this problem, we propose CSS combined with a control device in this study. The control device consists of variable orifice fluid damper, and its damping coefficient is controlled by a radial basis function-based neural network algorithm. Numerical simulations are performed to evaluate the effectiveness of the proposed technique for only one-directional horizontal seismic excitations without any evaluation concerning the durability of CSSs. The results of the investigation demonstrate that the proposed technique is effective to reduce both the base shear and the sliding displacement of the isolated structure. In addition, the response predicted by the proposed technique is almost similar to the response of isolated structure with passive damper at optimum damping ratio.

Structural damage diagnosis with uncertainties quantified using interval analysis


The in situ structural assessment by means of structural health monitoring (SHM) has received a great attention in all sorts of civil engineering applications. However, SHM implementations especially damage detections for real-world infrastructures are always overwhelmed with uncertainties of high dimensionality. A nonprobabilistic uncertainty-quantification-enhanced damage diagnosis method is proposed in this study with respect to interval analysis on SHM features. The diagonal elements of the vector auto-regressive model, constructed from the data measurements, are firstly extracted to form a vector, and this vector's Mahalanobis distance between pristine and unknown conditions is used as a damage-sensitive feature. Subsequently, the uncertainty sources, such as measurement inaccuracy and physical variability, are considered as influencing variables. A differential evolution algorithm is thereby introduced to convert the fluctuating interval of those variables into the uncertainty interval of Mahalanobis distance estimation. Finally, inspired by the idea of receiver operating characteristics when probability of detection is available, a modified mathematic metric is defined suited for interval analysis, and area under the modified receiver operating characteristics curve is employed to detect and localize damages. A contrived numerical mass-spring system and a laboratory-scale frame structure are used to validate the proposed framework; and in addition, the damage severity is able to be quantified via a proposed interval distance between pristine and inspection conditions.

Monitoring of masonry historical constructions: 10 years of static monitoring of the world's largest oval dome


This paper presents the analyses conducted on the data acquired by the monitoring system of the “Regina Montis Regalis” Basilica of Vicoforte (Italy) in the decade 2004–2014. The Basilica is a building of great historical, architectural, and structural significance, owing its fame to its impressive masonry oval dome, the world's largest of this shape (internal axes of 37.23 by 24.89 m). The dome-drum system of the Basilica has suffered over the years of significant structural problems, partly due to the settlements of the building induced progressively by newly built masses and also to the sliding of the underground. In 1983, concerns over the severe settlements and cracking phenomena affecting the structure prompted the decision to undertake strengthening interventions. A special hooping system, consisting of 56 tie bars, placed around the oval perimeter of the dome, was thus conceived to limit the crack opening. The monitoring system of the Basilica installed in the early 1980s underwent several renovations, and in 2004, its acquisition procedure was automatized. One hundred twelve instruments, consisting of temperature sensors, crackmeters, load cells, pressure cells, wire gauges, hygrometer, piezometers, and hydrometer, are currently installed on the Basilica. This study is primarily focused on data acquired by the crackmeters, the extensometers along the main axes of dome, and the load cells placed at the ends of the tie bars. The main aim of the reported analysis is to evaluate the possible progression of the cracks on the Basilica, and the structural performance of the strengthening interventions put in place in 1985–1987.

A passive electromagnetic eddy current friction damper (PEMECFD): Theoretical and analytical modeling


The focus of this paper is on analytical modeling of a novel type of passive friction damper for seismic hazard mitigation of structures. The proposed seismic damping device, which is termed as passive electromagnetic eddy current friction damper, utilizes a solid-friction mechanism in parallel with an eddy current damping mechanism to maximize the dissipation of input seismic energy through a smooth sliding in the damper. In this passive damper, friction force is produced through magnetic repulsive action between two permanent magnetic sources magnetized in the direction normal to the friction surface, and the eddy current damping force is generated because of the motion of the permanent magnetic sources in the vicinity of a conductor. The friction and eddy current damping parts are able to individually produce ideal rectangular and elliptical hysteresis loops, respectively; which, when combined in the proposed device, are able to accomplish a higher input seismic energy dissipation than that only by the friction mechanism. This damper is implemented on a two-degree-of-freedom system to demonstrate its capability in reducing seismic responses of frame building structures. The numerical results show that the seismic performance of the proposed damper is comparable with that of passive magnetorheological damper of the same force capacity. However, the cost of the device is likely to be quite lesser than that of a magnetorheological damper.

Concrete dam deformation prediction model for health monitoring based on extreme learning machine


Structural health monitoring via quantities that can reflect behaviors of concrete dams, like horizontal and vertical displacements, rotations, stresses and strains, seepage, and so forth, is an important method to evaluate operational states of concrete dams correctly and predict the future structural behaviors accurately. Traditionally, statistical model is widely applied in practical engineering for structural health monitoring. In this paper, an extreme learning machine (ELM)-based health monitoring model is proposed for displacement prediction of gravity dams. ELM is one type of feedforward neural networks with a single layer of hidden nodes, where the weights connecting inputs to hidden nodes are randomly assigned. The model can produce good generalization performance and learns faster than networks trained using the back propagation algorithm. The advantages such as easy operating, high prediction accuracy, and fast training speed of the ELM health monitoring model are verified by monitoring data of a real concrete dam. Results are also compared with that of the back propagation neural networks, multiple linear regression, and stepwise regression models for dam health monitoring.

New results concerning structural health monitoring technology qualification for transfer to space vehicles


This article reports the results of recent complex tests on the survival, in view of space applications, of structural health monitoring (SHM) methodology that uses piezo wafer active sensors (PWAS) and the electromechanical impedance spectroscopy (EMIS) method. Successive and then concomitant actions of the harsh conditions of outer space, including extreme temperatures and radiation, were simulated in a laboratory. The basis of the method consists in the fact that the real part of the bonded PWAS impedance spectrum, the so-called EMIS structure signature, follows the resonance behaviour of the structure vibrating under the PWAS excitation and, consequently, the onset and progress of structural damage with fidelity. The tests were conducted on the PWAS separately and aluminium discs with PWAS bonded on them as structural specimens. The conclusion of the tests is that the cumulative impact of severe conditions of temperature and radiation did not result in the decommissioning of the sensors or adhesive, which would have meant that the methodology was compromised. This conclusion occurs as a result of applying two new analysis methods to EMIS signatures. The first method, based on systematic observation of EMIS signatures during tests, makes it possible to distinguish between real damage with a mechanical origin and false damage, which is reversible and caused by the harsh environmental factors. A second method, based on the concept of entropy, shows how to identify mechanical damage at a certain distance from the PWAS. Moreover, an offline analysis of the EMIS “entropy” signatures supports the conclusion that the SHM technology survived the harsh environmental conditions.