In this paper, experimental data from tests of a helical fluid inerter are used to model the observed hysteretic behavior. The novel idea is to test the feasibility of employing mem‐models, which are time‐invariant herein, to capture the observed phenomena by using physically meaningful state variables. First, we use a Masing model concept, identified with a multilayer feedforward neural network to

Bridge infrastructure assets possess ultimate value for safe, resilient, and sustainable transportation networks. Monitoring of bridge structural characteristics is an essential process to minimize damage‐associated risk but requires expensive sensor instrumentation, manpower, and expert intervention. Besides, certain bridges' vitality exceeds practical needs due to their landmark identity with symbolic

No abstract is available for this article.

In this study, a toroidal tuned liquid column damper (TTLCD), which is composed of outer shell, inner shell, and L‐shaped baffles, is creatively proposed to control multidirectional vibration of structures. With a toroidal shape, the proposed TTLCD can act as several equivalent TLCDs in arbitrary directions due to its axial symmetry. First, the configuration of the TTLCD is illustrated in detail. Second

A novel multi‐resolution broad learning (MRBL) approach is proposed for model updating using identified modal data. Due to measurement noise and limited monitoring locations, the identified modal data are incomplete and noise corrupted. Besides, it is inevitable to have modeling errors in finite element models. Therefore, it is nontrivial to establish simple explicit relationship to represent the nonlinear

To analyze the multidimensional vibration reduction performance and torsional vibration characteristics of frame structures with magnetorheological damper (MRD), the space models of the reinforced concrete (RC) frame structure with and without MRD, based on the space beam element and shell element model, are established and programmed by using MATLAB software. Then, comparisons on results of modal

In this paper, a non‐parametric damage detection method for truss railroad bridges is presented which utilizes statistical analysis of bridge strain responses to operational train loading. Strain time‐history responses obtained under baseline and damaged bridge conditions are used to compute the coefficient of variation matrices. The results are presented in terms of the difference of the covariance

Research on structural health monitoring (SHM) is nowadays evolving from SHM‐based diagnosis towards SHM‐based prognosis. The structural strain response, as a localized response, has gained growing attention for application to structural condition assessment and prognosis in that continuous strain measurement can offer information about the stress experienced by an in‐service structure and is better

Nowadays, there is a considerable effort to develop technologies for smart cities. Smart buildings are a critical component of such smart cities, and their automated structural health monitoring is essential. This paper presents a new, efficient, and robust methodology for automated structural damage detection of shear‐type buildings. The proposed method uses output‐only acceleration response to separately

This study presents a damage localization method for building structures using dynamic displacement responses based on a convolutional neural network (CNN). The proposed method is based on the interrelation of dynamic displacement response measured from a building in a healthy state. Based on the interrelation constructed by CNN in advance, damaged stories are localized by investigating the discrepancy

The application of the particle damping technology in civil engineering is limited owing to the complex nonlinear mechanical properties and lack of a reasonable mechanical model. The existing equivalent single‐particle model cannot include the interactions between particles. In addition, an appropriate determination of parameters is required. In this study, to consider the influence of the interactions

Adding a virtual mass is an effective method for damage identification. It can be used to obtain a large amount of information about structural response and dynamics, thereby improving the sensitivity to local damage. In the current research approaches, the virtual mass is determined first, and then the modal characteristics of the virtually modified structure are identified. This requires a wide frequency

Structural health monitoring (SHM) on railway tunnels is increasingly demanding inspection methodologies based on full‐field image‐based techniques. The relevance of adequate inspection methodologies to signal potential problems that need increased attention is at the forefront of any monitoring system for problems that can disturb tunnel's integrity. Detecting defects is decisive for an efficient

Structural health monitoring (SHM) has been becoming a key element of monitoring and maintenance in modern and smart cities with critical infrastructures. Within the past decade, SHM approaches are widely used in bridges, roads, skyscrapers, critical facilities, and buildings to enhance the public safety and cost efficiencies of infrastructure maintenance under extreme events, such as earthquakes.

In this study, the robust optimum design of a recently developed passive control device, i.e., tuned mass damper inerter (TMDI) is investigated to control a 10‐story base‐excited shear building benchmark. The H2 and H∞ of three different objective functions (i.e., minimizing roof displacement, minimizing 7th‐story displacement, and maximizing the TMD stroke) are selected as objective functions for

The installation of a damping bracing system is regarded as an effective means to upgrade the seismic capacity of steel moment‐resisting frames (MRFs), a common structural form for buildings. However, conventional damping braces are incapable of eliminating residual deformation demand. Shape memory alloy (SMA) braces present an emerging seismic upgrading solution to this problem. However, the corresponding

Output‐only identification of civil structures is a challenging yet in escapable task, as input excitations are unmeasurable in many real‐world situations. This paper presents a new output‐only technique to jointly identify the model parameters of adjacent buildings from their recorded seismic responses. Classic output‐only identification techniques are based on various limiting assumptions about the

This paper demonstrates the potential to use measured deflection responses of a bridge to random traffic as a means of monitoring its structural health. Three displacement transducers are simulated on the bridge at different locations, providing absolute deflection data. The stiffness profile through the length of the bridge is calculated using these data. Vehicle axle loads are calculated as well

The mathematical monitoring model‐based interpretation of recorded quantities, especially of displacements, is essential for the structural health diagnosis of concrete dams. In practice, dam displacements are frequently interpreted and predicted by the hydraulic, seasonal, and time model, which considers the thermal deformation effect of a dam body by the periodic harmonic factor. The main purpose

In this paper, damage indicators are presented for bridges based on measured data collected under uncontrolled traffic conditions. The test bridge considered is a small stiff concrete culvert with low dynamics, making it suboptimal for monitoring with accelerometers. Largely static strain responses are measured, with the variability in the vehicle weights and configurations addressed by handling the

Crack detection is an important issue in the health monitoring and performance evaluation of concrete structures. Based on the heat transfer theory, a temperature tracer method and a monitoring system for crack detection in underwater concrete structures are presented in this paper. The system is composed of an integrated sensing and heating system, a monitoring tube, and multiple casing tubes. The

Dampers with negative stiffness behavior have been widely investigated for structural vibration control due to their superior performance. In practical applications, a support in series with these dampers might have some flexibility, that is, the stiffness is positive but finite. This paper investigates the effects of that flexibility on the performance of a passive negative stiffness damper (PNSD)

Visual inspections is a common approach for the network‐scale monitoring of bridges. One of the main challenges when interpreting visual inspections is the observations being subjective and thus the observation uncertainty varies among different inspectors. In addition, observations uncertainties can be dependent on the structural element condition. These two factors introduce difficulties in differentiating

This paper presents a novel and accurate model‐reference health monitoring system for the location of damage to building structures using the dissipated energy approach, frequency domain convolutional neural networks (CNNs), and principal component analysis (PCA). Due to the fact that the earthquake introduces several stress cycles in different directions in the structure, load–strain curves can be

This paper presents a technique for vibration‐based damage detection and localization in engineering structures based on the high‐speed three‐dimensional Digital Image Correlation (HS 3D‐DIC) and local modal filtration. The efficacy of the proposed procedure is demonstrated on a frame structure with different severities of localized damage. The full‐field vibration data acquired under the white noise

The paper introduces a procedure to automatically identify key vehicle characteristics from vibrations data collected on a suspension bridge. The primary goal is to apply a model of the dynamic displacement response of a long‐span suspension bridge to traffic loading, suitable for automatic identification of the vehicle passage over the bridge. The second goal is to improve the estimation of the structural

This paper proposes a bolt looseness detection method based on the ultrasonic wavefield energy in the Lamb wave reflected from a target bolt. The full wavefield inside the area of the specimen containing the target bolt was first visualized. The ultrasonic wave propagation imaging (UWPI) approach was used for visualizing the interaction of the wavefield with the elements on the specimen such as the

To assess the current conditions of bridges in practice, a manual visual inspection is commonly used for maintenance purposes. Because manual visual inspection is time consuming, expensive, and laborious, computer vision with deep learning techniques has recently been introduced as a promising tool for automatic damage detection and classification. However, damage localization is difficult in that

No abstract is available for this article.

Time series models have been popularly used in structural damage identification because the model coefficients and residual errors are sensitive to structural damages. As the direct relationship between the time series model coefficients (or residual errors) and damage severity is hard to be established, these methods provide limited information about the location or severity of damage. This study

The aim of this study is to develop a Hamiltonian Monte Carlo‐based algorithm for finite element model updating in the Bayesian framework. The proposed algorithm uses adaptive prior‐based approach, which helps to generate the intermediate pdf s. Numerical analysis is carried out with different coefficient of variations of the prior for model updating. Guidelines for their proper selection procedure

No abstract is available for this article.

The present article provides a state‐of‐the‐art review of imaging techniques used for defect detection of fiber reinforced polymer (FRP)‐bonded civil engineering structures. Compared to the conventional techniques by equipping a structure with stress wave sensors, the contactless imaging techniques feature efficient instrumentation, convenient data acquisition, and rapid evaluation in the procedures

Deep neural networks (DNNs) are a powerful tool for structural health monitoring because they can automatically identify features that are useful for classifying and recognizing damage patterns of a target structure with high accuracy. However, it can misclassify input data of an unlearned damage pattern as any of the learned damage patterns. To address this shortcoming, this paper presents a method

No abstract is available for this article.

Research on the process and its mechanism of dam failure is a long‐term focus in dam engineering field. The reasonable analysis and prediction of dam failure are of great significance to improve the level of dam emergency management and reduce the risk of dam break. A cellular automata (CA)‐based approach is introduced to implement the simulation analysis for the process of piping failure and its induced

This study investigates multimode damping effects of a long cable attached with a viscous‐shear damper (VSD). A typical VSD comprises a casing box containing viscous medium and shearing plates with parts submerged in the medium. It dissipates vibration energy through shear deformation of the viscous medium. The VSD is low‐cost and invulnerable to leakage or increasing joint play and hence requires

In this paper, a new sensitivity‐based model updating method is presented based on the changes of principal components (PCs) of frequency response function (FRF). Structural damage estimation, identification of damage location and severity, is conducted by an innovative sensitivity relation. The sensitivity relation is derived by incorporating PC analysis (PCA) data obtained from the incomplete measured

Periodic road crack monitoring is an essential procedure for effective pavement management. Highly efficient and accurate crack measurements are key research topics in both academia and industry. Automatic methods gradually replaced traditional manual surveys for more reliable evaluation outputs and better efficiency, whereas the devices are not available to all functional classes of pavements and

This paper develops a disc spring (DS) device to improve the self‐centering capability of a conventional reinforced concrete (RC) shear wall. In particular, the DS devices are installed at the foot of the RC shear wall, thus forming a self‐centering RC shear wall (SCSW) system. The DS devices used in the SCSW system are expected to protect the RC wall from damage and provide restoring force for the

Precast buildings have been becoming popular in China in these 5 years since they have many merits such as effectiveness, safety, high quality, and environmental friendliness. In some cities of China, it is required to make the proportion of precast buildings account for 30% in newly built construction areas. Following the rapid development, their vibration behaviors are attracting more attention since

The long‐term safety and health monitoring of large dams has attracted increasing attention. In this paper, coupling prediction models based on long short‐term memory (LSTM) network are proposed for the long‐term deformation of arch dams. Principal component analysis (PCA) and moving average (MA) method, adopted to make dimension reduction for the input variables, are respectively combined with the

This paper introduces a new and unique full‐scale testbed site for structural health monitoring and soil–structure system identification studies being developed in southwest China. The site is a 48‐story skyscraper with an extended four‐level basement, supported by piles, located in Kunming, the capital of Yunnan Province. Located in the diffused zone of collision of the Indian and Eurasian tectonic

Diagnostics and elimination of airflow separation effects draw essential attention of researchers in the areas of energy generation, civil engineering, and aerospace due to unwanted and harmful interaction of separated airflow with different structures. In aviation, distortion of the intake airflows of an aircraft engine, known as intake separation, not only reduces the efficiency of the engine due

An innovative semiactive device, named the spindle adaptive tuned vibration absorber (SATVA), is proposed herein, having the potential of attenuating unfavorable vibrations of the host systems. The proposed device includes a preferably spindle‐shaped body of mass, whose mass moment of inertia can be altered simply by moving a pair of rotating supports. Therefore, the natural frequency of the device

An effective and reliable approach to updating finite element (FE) models of real structures is to utilize a sensitivity‐based strategy. A challenging issue concerning the sensitivity‐based finite element model updating (FEMU) is to create a well‐established framework for updating the inherent structural properties of FE models under incomplete noisy modal data. When noise contaminates the measured

Expansion joints of bridges are vulnerable to damage due to the thermal expansion and contraction, vehicle traffic, and so forth. Currently, the temperature–displacement relationship model may be the only qualitative method for condition evaluation of bridge expansion joints using the field monitoring data. The quantitative assessment based on the finite element model updating techniques is heavy computational

During strong earthquakes, structural pounding may occur between structures (buildings, bridges, strategic facilities, critical equipment, etc.) and the surrounding moat wall because of the limited separation distance and the deformations of the isolator. An arrangement that favors the solution of this problem is the interposition of shock absorbers. Thus, the influence of geometrical and mechanical

The aim of this paper is to identify, both through microtremor analysis and visual inspection, the collapse mechanisms of the Nepalese wood‐masonry monuments damaged by the 2015 seismic event that struck Kathmandu and its valley. The research analyses two case studies as the “Radha Krishna” temple located in Teku, a district in Kathmandu, and the “Pancha Deval complex” in Pashupati area. More specifically

Interactions among an inerter, spring, and energy dissipation element (EDE) in an inerter system can result in a higher energy dissipation efficiency compared to a single identical EDE, which is referred to as the damping enhancement effect. Previous studies have mainly concentrated on the vibration mitigation effect of the inerter system without an explicit consideration or utilization of the damping

The accuracy of structural damage identification is affected by the uncertainties in the vibration measurements and the finite element modeling. This paper proposes a novel approach based on sparse deep belief network (DBN) for structural damage identification with uncertain and limited data. Vibration characteristics, that is, natural frequencies and mode shapes, are extracted as the input to the

When operating a wind turbine, damage of rotor blades is a serious problem. Undetected damages are likely to increase overtime, and therefore, the safety risks and economical burdens also increase. A monitoring system, which detects reliably defects in early stages, gives scope for action and is therefore a key element to avoid damage increase and to optimize the efficiency of wind turbines. One promising

In this study, a method of predicting the seismic responses of building structures based on a convolutional neural network (CNN) is proposed. In the method, the time histories of acceleration responses previously measured in a building during earthquakes are used in the CNN input layer, with the corresponding time histories of the displacement responses being used in the CNN output layer. The correlations

Nonlinear ultrasonic experiments typically require digital pass‐band filters and advanced signal processing tools to highlight low‐amplitude nonlinear elastic effects such as harmonics, subharmonics, and sidebands, which are used as signatures for the presence of damage. However, current signal processing techniques cannot be used with dual periodic excitation without reducing signal frequency resolution

Sliding bearings of a bridge are important sliding elements that accommodate the bridge movement caused by temperature action and vehicle/wind load. The sliding life of sliding bearings is determined by the wear of the sliding materials in the bearing. However, the wear of sliding bearings primarily results from a large amount of cumulative sliding displacement experienced by the sliding bearing, even