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A challenging issue in design and implementation of an effective structural health monitoring (SHM) system is to determine where a number of sensors are properly installed. In this paper, research on the optimal sensor placement (OSP) is carried out on the Canton Tower (formerly named Guangzhou New Television Tower) of 610 m high. To avoid the intensive computationally-demanding problem caused by tens of thousands of degrees of freedom (DOFs) involved in the dynamic analysis, the three dimension finite element (FE) model of the Canton Tower is first simplified to a system with less DOFs. Considering that the sensors can be physically arranged only in the translational DOFs of the structure, but not in the rotational DOFs, a new method of taking the horizontal DOF as the master DOF and rotational DOF as the slave DOF, and reducing the slave DOF by model reduction is proposed. The reduced model is obtained by IIRS method and compared with the models reduced by Guyan, Kuhar, and IRS methods. Finally, the OSP of the Canton Tower is obtained by a kind of dual-structure coding based generalized genetic algorithm (GGA).

The GPS carrier phase observations are widely used for the high precision static and kinematic positioning applications. However, GPS signals are seriously distorted when passing through walls and other obstructions. This paper focuses on this issue and outlines the research carried out to investigate the effects of some commonly used construction materials on the GPS signals. For the purpose of generating the multipath in a controlled manner, an experimental set-up is designed to test the effect of typical building surface materials (toughened glass, wood board, PVC board and ceramic tile) on positioning accuracy. The effects of signal attenuation on the accuracy of the positioning solution are explored by an improved particle filtering algorithm and some statistical methods, and reasons for these effects are further analyzed. The findings of the experimental results may be used to enhance the performance of GPS technology.

SUMMARY Monitoring the response of structures, especially tall buildings, under severe loading conditions is an important requirement for the validation of their design and construction, as well as being a maintenance concern. This paper presents a review of current research and development activities (since 1995) in the field of high-rise structure health monitoring using the Global Positioning System (GPS). The GPS monitoring technology and its accurate assessment method are firstly briefly described. Then, the progresses on monitoring the displacement of the high-rise structure caused by the ambient effects including wind, thermal variation, and earthquake-induced responses are discussed in details. Following that, the states of the art of augmenting the GPS monitoring technology are reviewed. Finally, existing problems and promising research efforts in the GPS-based health monitoring are given. Copyright © 2012 John Wiley & Sons, Ltd.

The two kinds of statistical process control algorithms for detecting the small displacement shifts in the monitoring data obtained by the Global Position System (GPS) receiver are comparatively studied in this paper. The Shewhart and Cumulative Sum (CUSUM) charts are applied to the simulated and the experiment GPS coordinates, and their effectiveness in detecting the small and large persistent shifts are evaluated. The result shows that the Shewart chart is useful in detecting large shifts in GPS real-time data, but it can’t find small shifts. The CUSUM chart appears to be an ideal candidate for detecting the GPS coordinate changes in deformation monitoring since it can detect the small and persistent shifts hidden in a GPS time series data.

The determination of structural stiffness for the currently seismic design method depends on subjective experience of designers which is not rational and economical. A method that uses displacements as the basis for the stiffness design procedure is then presented: (1)By means of preliminary design, the initial elastic structure are obtained and the 1th mode shape, period etc are then calculated by modal analyses; (2) The target period and lateral equivalent stiffness of structure are determined according to target displacement used in seismic code; (3)The two periods for initial designed structure and target structure are compared and the lateral stiffness is adjusted to make the displacement responses of the structural weak members meet the limited displacements by adjustment parameter. An example is implemented for demonstrating the process and verifying the accuracy of the procedure.

Modal kinetic energy (MKE) method gives a measure of the dynamic contribution of each finite element model physical degree of freedom to each of the target mode shapes, and provides a rough idea where the maximum responses could be measured. It could help to select those sensor positions with possible large amplitudes, and to increase the signal to noise ratio, which is critical in harsh and noisy circumstances. Kammar proposed a new optimal placement method of triaxial accelerometers based up on the effective independence algorithm (EfI3), which places triaxial accelerometers as single units in an optimal fashion. On the basis of EfI3, this paper fully considers the mutual influence of three directions and makes some improvements for the traditional MKE method. A novel optimal placement method of triaxial accelerometers called MKE3 is proposed which is proved rational and effective by analysis the relationship between the EfI algorithm and MKE method.

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. In this paper, an optimal sensor placement (OSP) method based on a new intelligent algorithm, i.e., monkey algorithm (MA) is proposed. Considering the limitation of MA and the characteristics of OSP, the integer encoding to solve the location of the monkeys is proposed. The diversity of the monkeys is increased by introducing the hamming distance in the initial location, in order to improve the capacity of global search, and the random disturbance mechanism of the Harmony search is introduced in the process of climbing to improve the capacity of local search. Finally, taking the Dalian World Trade Building as an example, the OSP schemes are chosen. The numerical example demonstrated the feasibility and effectiveness of the proposed method.

The limitations of traditional inelastic response spectra are discussed. Considering a one-storey asymmetric plan system subjected to perpendicular bi-directional earthquake motions, the inelastic multi-dimensional strength reduction factor spectra is presented. The yield rule of the asymmetric plan system is determined by two-dimensional yield-surface plasticity function. The spectral equation is simplified by the relationship of strength reduction factors between x-direction and y-direction.The multi-dimensional spectra are analyzed based on 30 pair strong earthquake motion records for hard soil site, intermediate soil site and soft soil site. Analytic results shows that the strength reduction factor mean spectra for each soil site has its own characteristics, and the strength reduction factor spectra is affected strongly by ductility, normalized stiffness eccentricity, period and rotation frequency ratio.

Investment decisions are usually made on the basis of the subjective judgments of experts subjected to the information gap during the preliminary stages of a project. As a consequence, a series of errors in risk prediction and/or decision-making will be generated leading to out of control investment and project failure. In this paper, the variable fuzzy set theory and intelligent algorithms integrated with case-based reasoning are presented. The proposed algorithm manages the numerous fuzzy concepts and variable factors of a project and also sets up the decision-making process in accordance with past cases and experiences. Furthermore, it decreases the calculation difficulty and reduces the decision-making reaction time. Three types of risk correlations combined with different characteristics of engineering projects are summarized, and each of these correlations is expounded at the project investment decision-making stage. Quantitative and qualitative change theories of variable fuzzy sets are also addressed for investment risk warning. The approach presented in this paper enables the risk analysis in a simple and intuitive manner and realizes the integration of objective and subjective risk assessments within the decision-makers' risk expectation.

This paper focuses on the wind-induced vibration control of the Dalian international trade mansion (DITM) by using the tuned liquid dampers (TLDs). To avoid the intensive computationally demanding problem caused by tens of thousand of degrees of freedom (DOF) of the structure in the numerical analysis, the three-dimension finite element model of the DITM is first simplified to the equivalent series multi-DOF system. The wind loading is subsequently simulated by the Davenport model according to the structural environmental condition where the actual samples of wind speed are measured. Following that, the shallow- and deep-water wave theories are applied to model the liquid sloshing inside TLDs, the tank sizing, and required water depth, and numbers of TLDs are given according to the numerical results of different cases. Comparisons between uncontrolled and controlled displacement and acceleration responses of the DITM under wind forces show that the designed shallow tank has higher efficiency than the deep one, which can effectively reduce the structural response amplitudes and enhance the comfortableness of the mansion. The preliminary TLD design procedure presented in this paper could be applied as a reference to the analysis and design of the wind-induced vibration for high-rise buildings using the TLD.

An experimental study of C20, C25, C30, C40, and C50 big mobility concrete cubes that came from laboratory and construction site was completed. Nondestructive testing (NDT) was carried out using impact rebound hammer (IRH) techniques to establish a correlation between the compressive strengths and the rebound number. The local curve for measuring strength of the regression method is set up and its superiority is proved. The rebound method presented is simple, quick, and reliable and covers wide ranges of concrete strengths. The rebound method can be easily applied to concrete specimens as well as existing concrete structures. The final results were compared with previous ones from the literature and also with actual results obtained from samples extracted from existing structures.

SUMMARY Careful selection and placement of sensors are the critical issue in the construction and implementation of an effective structural health monitoring system. A hybrid method termed the optimal sensor placement strategy (OSPS) based on multiple optimization methods is proposed in this paper. The initial sensor placement is firstly obtained by the QR factorization. Then, using the minimization of the off-diagonal elements in the modal assurance criterion matrix as a measure of the utility of a sensor configuration, the quantity of the sensors is determined by the forward and backward sequential sensor placement algorithm together. Finally, the locations of the sensor are determined by the dual-structure coding-based generalized genetic algorithm (GGA). Taking the scientific calculation software matlab (MathWorks, Natick, MA, USA) as a platform, an OSPS toolbox, which is working as a black box, is developed based on the command-line compiling and graphical user interface-aided graphical interface design. The characteristic and operation method of the toolbox are introduced in detail, and the scheme selection of the OSP is carried out on the world's tallest TV tower (Guangzhou New TV Tower) based on the developed toolbox. The results indicate that the proposed method is effective and the software package has a friendly interface, plenty of functions, good expansibility and is easy to operate, which can be easily applied in practical engineering. Copyright © 2011 John Wiley & Sons, Ltd.

This paper considers the problem of locating sensors on the flexible structures with the aim of maximizing the data information so that structural dynamic behavior could be fully characterized. Since only translational degrees of freedoms (DOFs) are considered for possible sensor installation in the state-of-the-practice, a method which could avoid distinguishing the translational and rotational DOFs is presented. In order to realize the proposed method and to demonstrate its effectiveness, three different sensor placement techniques, EfI, EfI-DPR and Uniform, were employed to a super tall building. The calculation results showed that the proposed method is easy in understanding and could be used practically by civil engineers. EfI method provides a more effective method for optimal sensor placement than other ones to identify the vibration characteristics of the studied building.

Today, long-span bridges are being designed to be more flexible and to resist extensive impacts from changes in temperature, severe wind gusts and earthquake tremors. Structural responses (especially displacement) of bridge structures are becoming increasingly important for the finite element (FE) modal updating, structural response prediction and safety evaluation. Methods of global displacement sensing were developed for these needs. This paper presents an overview of current research and development activities in the field of bridge health monitoring using the global positioning system (GPS). The GPS monitoring technology and its accuracy assessment method are also briefly described. Finally, existing problems and promising research efforts in the GPS based bridge health monitoring are discussed.

The fatigue assessment of orthotropic bridge decks under routine traffic loading is a significant task to ensure the serviceability and safety of steel bridges. The sequential law computes fatigue damages using whole-range [Formula: see text]–[Formula: see text] curves and sequential stress histories and has been proven to provide more realistic results than Miner’s rule under variable amplitude loading. In this paper, a whole-range [Formula: see text]–[Formula: see text] curve covering the very low-cycle region, the low-cycle region, the finite life region, the high-cycle region, and the very high-cycle region is proposed for the sequential law to evaluate the fatigue performance of steel orthotropic bridge decks. The mathematical model of the whole-range [Formula: see text]–[Formula: see text] curve is first deduced based on the partially known [Formula: see text]–[Formula: see text] curve recommended in steel bridge design codes. The properties of the whole-range [Formula: see text]–[Formula: see text] curve are then explained from the geometrical point of view in the double logarithm coordinates system. Finally, rib-to-deck joints in steel orthotropic bridge decks are used as a case study. Fatigue test data are used to validate the proposed model. The whole-range [Formula: see text]–[Formula: see text] curve, with a 97.5% survival limit, is established for fatigue assessment of rib-to-deck joints in real bridges. The results show that the proposed whole-range [Formula: see text]–[Formula: see text] curve allows a good fit of experimental data and excellent agreement with code [Formula: see text]–[Formula: see text] curves in the finite life region and provides an effective extrapolation from the finite life region to the whole range of cycle numbers.

Nowadays, there are many larger and taller engineering structures than in the past. These structures are commonly designed to be more flexible. Thus, they are sensitive to severe wind gust and earthquake tremor. For the dynamic response prediction, finite element (FE) modal updating and structural health monitoring, the dynamic characteristics of a structure are becoming increasingly important. The aim of this paper is to show an emerging tool-the real time kinematic (RTK) global positioning system (GPS), which is used to measure and monitor the low-frequency vibration of Dalian BeiDa Bridge, a medium span suspension bridge. The modal analysis is firstly performed on the developed three-dimensional FE model according to the original blue prints of the bridge to provide the analytical frequencies and mode shapes. The field ambient vibration tests using the accelerometers on the bridge deck are conducted just prior to the use of the GPS system in order to validate the FE model. And then, the calibration test is done to assess the dynamic displacement measurement accuracy of the GPS in three orthogonal directions. The GPS signal properties, such as the amplitude, standard deviations (STD), power spectral density (PSD), and probability density functions (PDF), are studied in details. After that, a structural health monitoring system based on the GPS is devised and installed on the bridge to provide real-time measurement of deck movement. The output-only modal parameter identification is carried out by using the Periodogram method to investigate the responses of the bridge. The result shows that the spectral densities of the displacements measured by the GPS correspond well with the results by the FEM analysis and the accelerometer vibration test. It is concluded that the GPS method is reliable and useful to clarify the ambient vibration response behaviors of the flexible structures. The integration of the GPS and accelerometer methods results in a hybrid arrangement that can help to eliminate some disadvantages of the two devices used separately.

This paper presents a new technique for input reconstruction based on the explicit fourth-order Runge–Kutta (RK4) method. First, the state-space representation of the dynamic system is discretized by the explicit RK4 method under the assumption of linear interpolation for the dynamic load, leading to a recurrence equation between the current state and the previous state. Then, the mapping from the sequences of input to output is established through the recursive operation of the system equation and observation equation. Finally, the stabilized force information is recovered using the Tikhonov regularization method. This approach makes use of the good stability and high precision of the RK4 method; in addition, the computational efficiency is enhanced by avoiding the computation of the inverse stiffness matrix. The proposed method is numerically illustrated and validated with various excitations on a simple four-story shear building and a more complicated 2D truss structure, along with a detailed parametric study. The simulation studies show that the external loads can be reconstructed with high efficiency and accuracy under a low noise environment.

A wavelet energy method is presented to search the critical incidence of earthquake excitation in a multi-dimensional seismic response of offshore platforms. The total effective energy and the instantaneous effective energy input rate of an earthquake can be obtained by wavelet transformation to predict the critical incidence of the earthquake and then the maximum dynamic response of the platform can be calculated. The critical incidence is determined using this method for an actual platform and a group of single degree-of-freedom systems. Numerical results show that the application of wavelet transform in a multi-dimensional seismic response of structures is convenient and reliable.

The dynamic behavior of inelastic structures during an earthquake is a complicated non-stationary process that is affected by the random characteristics of seismic ground motions. The conventional Fourier analysis describes the feature of a dynamic process by decomposing the signal into infinitely long sine and cosine series, which loses all time-located information. However, both time and frequency localizations are necessary for the analysis of an evolutionary spectrum of non-stationary processes. In this paper, an analytical approach for seismic ground motions is developed by applying the wavelet transform, which focuses on the energy input to the structure. The procedure of identification of the instantaneous modal parameters based on the continuous wavelet transform (CWT) is given in detail. And then, a novel method using the auto-regressive moving average (ARMA), called “prediction extension”, is presented to remedy the edge effect during the numerical computation of the CWT. The effectiveness of the method is verified by the use of the benchmark model developed by the American Society of Civil Engineers (ASCE). Finally, a scale model with three-storey reinforced concrete frame-share wall structure is made and tested on a shaking table to investigate the relation between the dynamic properties of structures and energy accumulation and its change rates during the earthquake. The results have shown that the wavelet transform is able to provide a deep insight into the identity of transient signals through time-frequency maps of the time variant spectral decomposition.

The Global Positioning System (GPS) has been used in the health monitoring of large structures in recent years since it is weather independent, capable of autonomous operation, and does not require a line-of-sight between target points. In this paper, a structural health monitoring system based on the GPS is devised for a high-rise building. The field data, such as wind speed, wind direction and displacement responses were simultaneously and continuously measured under strong wind conditions. The relation between velocity components of the atmospheric wind and pressure fluctuations on the roof of the building are analyzed using the wavelet scalogram and wavelet coherence method, and a statistical significance level estimation method based on Monte Carlo simulation is presented to isolate the meaningful coherence from the spurious noise map. Finally, the responses of the high-rise building are investigated using the Periodogram method to conclude that the identified results agree well with the results computed by the Finite Element Method (FEM).

Wireless sensor networks (WSNs) are promising technology in structural health monitoring (SHM) applications for their low cost and high efficiency. The limited wireless sensors and restricted power resources in WSNs highlight the significance of optimal wireless sensor placement (OWSP) during designing SHM systems to enable the most useful information to be captured and to achieve the longest network lifetime. This paper presents a holistic approach, including an optimization criterion and a solution algorithm, for optimally deploying self-organizing multi-hop WSNs on large-scale structures. The combination of information effectiveness represented by the modal independence and the network performance specified by the network connectivity and network lifetime is first formulated to evaluate the performance of wireless sensor configurations. Then, an information-fusing firefly algorithm (IFFA) is developed to solve the OWSP problem. The step sizes drawn from a L?vy distribution are adopted to drive fireflies toward brighter individuals. Following the movement with L?vy flights, information about the contributions of wireless sensors to the objective function as carried by the fireflies is fused and applied to move inferior wireless sensors to better locations. The reliability of the proposed approach is verified via a numerical example on a long-span suspension bridge. The results demonstrate that the evaluation criterion provides a good performance metric of wireless sensor configurations, and the IFFA outperforms the simple discrete firefly algorithm.

Nondestructive testing technology is essential in the quality inspection of repair, alteration, and renovation of the existing engineering, especially for concrete structure in severe environment. The objective of this work is to deal with the behavior of ultrasonic velocity and mechanical properties of plain concrete and air-entrained concrete subjected to freeze-thaw cycles (F-T-C). The ultrasonic velocity and mechanical properties (tensile strength, compressive strength, cubic compressive strength, and splitting strength) of C30 air-entrained concrete and plain concrete with different water-cement ratio (water-cement ratio was 0.55, 0.45, and 0.50, resp.) after F-T cycles were measured. The influences of F-T cycles on ultrasonic velocity and mechanical properties of C30 air-entrained concrete and plain concrete were analyzed. And the relationship between mechanical properties and ultrasonic velocity was established. The experimental results can be useful for the design of new concrete structure, maintenance and life prediction of existing concrete structure such as offshore platform and concrete dock wall.

Structural health monitoring (SHM) has gained a significant number of attentions from the engineering communities in the past two decades, which integrates the knowledge of a variety of disciplines including structural engineering, material science, computer science, signal processing, and data management [1–3]. A main purpose of the development of an SHM system is deemed to facilitate the routine inspection and maintenance activities of the targeted engineering infrastructures. With the aid of an instrumented long-term SHM system, the structural behavior and safety performance of the structure can be promptly evaluated by use of the huge amount of measurement data, and the optimal maintenance schedules can be executed by the infrastructure managers [4]. It includes the connectivity and information exchange between the participating institutions and individual members, the awareness of the SHM and integrity maintenance disciplines and tools among end users, and essential reference materials for the situations where a ranking of structures to be rehabilitated is necessary because of insufficient budget available. Therefore, in the light of these considerations, this special issue was launched in this journal, an SCI-indexed international journal. The papers in this special issue present the most recent advances, progress, and ideas in the field of the SHM and integrity maintenance and its application. It includes smart, bioinspired, nanometer, wireless, and remote sensing technology, sensor placement and optimization strategies, data compression, cleaning, mining and fusing technology, pattern recognition, feature extraction and damage detection and assessment, design, retrofit, maintenance, renewal and risk management of civil infrastructure, and application of SHM for heritage structures, historical monuments, and old bridges. After two-round peer reviewing, totally 55 research articles are received and 28 out of them are finally accepted for publication in this special issue. Among them, four papers are review articles. The paper “Structural health monitoring of civil infrastructure using optical fiber sensing technology: a comprehensive review” by X. W. Ye et al. presents a summary of the basic principles of various optical fiber sensors, innovation in sensing and computational methodologies, development of novel optical fiber sensors, and the practical application status of the optical fiber sensing technology in civil infrastructure monitoring. The paper “Dynamic responses and vibration control of the transmission tower-line system: a state-of-the-art review” by B. Chen et al. reviews the dynamic responses and vibration control of the transmission tower line system as well as the disaster monitoring and mitigation of the system subjected to dynamic excitations. The paper “Recent research and applications of numerical simulation for dynamic response of long-span bridges subjected to multiple loads” by Z. Chen and B. Chen addresses the key issues involved in dynamic response analysis of long-span multiload bridges based on numerical simulation technologies and the engineering applications of newly developed numerical simulation technologies for safety assessment of long-span bridges. The paper “A review on strengthening steel beams using FRP under fatigue” by M. Kamruzzaman et al. summarizes the existing FRP reinforcing techniques for fatigue damaged structural steel elements. The following papers address the research work on structural damage detection. The paper “Damage identification for large span structure based on multiscale inputs to artificial neural networks” by W. Lu et al. proposes a structural damage identification method by combining the measured results from strain sensors and accelerometers in the noisy environment based on the artificial neural network. The paper “Damage assessment of two-way bending RC slabs subjected to blast loadings” by H. Jia et al. investigates the blast response and damage assessment of a two-way bending RC slab subjected to blast loadings. The paper “Structural damage identification based on rough sets and artificial neural network” by C. Liu et al. conducts the research on potential applications of the rough sets theory and the artificial neural network method for structural damage detection. The paper “Damage detection on sudden stiffness reduction based on discrete wavelet transform” by B. Chen et al. presents the damage detection on sudden stiffness reduction of building structures based on the discrete wavelet transform. The paper “Damage detection of structures identified with deterministic-stochastic models using seismic data” by M.-C. Huang et al. addresses a deterministic-stochastic subspace method for damage identification which has been experimentally verified to detect the equivalent single-input-multiple-output system parameters of the discrete time state equation. Other papers focus on the research related to the development of integrated SHM systems and novel sensing technologies. The paper “Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge” by B. Chen et al. describes the integrated system for structural monitoring and intelligent management of the cable-stayed Zhijiang Bridge, China. The paper “Full-scale measurements and system identification on Sutong Cable-stayed Bridge during typhoon Fung-Wong” by H. Wang et al. analyzes the wind data and the structural vibration responses obtained from the SHM system installed on the cable-stayed Sutong Bridge, China, during a typhoon. The paper “Study on typhoon characteristic based on bridge health monitoring system” by X. Wang et al. investigates the typhoon characteristics by use of the measured data from the bridge health monitoring system instrumented on the Jiubao Bridge, China. The paper “Numerical simulation of monitoring corrosion in reinforced concrete based on ultrasonic guided waves” by Z. Zheng et al. predicts the location of the pitting corrosion in reinforced concrete based on the ultrasonic guided waves. The paper “Study on dynamic response measurement of the submarine pipeline by full-term FBG sensors” by J. Zhou et al. measures the dynamic responses of the submarine pipeline by use of the FBG sensing technology. The paper “Case study on the maintenance of a construction monitoring using USN-based data acquisition” by S. Kim et al. develops a ubiquitous sensor network for monitoring and maintenance of the building structure. The paper “In-line ultrasonic monitoring for sediments stuck on inner wall of a polyvinyl chloride pipe” by H. Seo et al. verifies the applicability and effectiveness of the ultrasonic monitoring of sediments stuck on the inner wall of polyvinyl chloride pipes. The subsequent papers present the investigations on the structural performance under seismic excitations. The paper “Numerical simulation on slabs dislocation of Zipingpu concrete faced rockfill dam during the Wenchuan earthquake based on a generalized plasticity model” by B. Xu et al. investigates the slab dislocation phenomenon of the Zipingpu concrete faced rockfill dam during earthquake. The paper “An improved multidimensional MPA procedure for bidirectional earthquake excitations” by F. Wang et al. develops an improved multidimensional modal pushover analysis method for estimating the response demands of structures subjected to bidirectional earthquake excitations. The paper “A methodology for multihazards load combinations of earthquake and heavy trucks for bridges” by D. Sun et al. presents a modified model considering the advantages of Ferry Borges-Castanheta's model and Turkstra's rule in converting the random process into the random variables for earthquake analysis. The paper “Experimental study of the seismic performance of L-shaped columns with 500 MPa steel bars” by T. Wang et al. addresses the experimental results of six L-shaped RC columns with 500 MPa steel bars for seismic performance assessment. The remaining papers in this special issue introduce the research outcomes on monitoring of hydraulic and geotechnical structures. The paper “Effects of outlets on cracking risk and integral stability of super-high arch dams” by P. Lin et al. presents the outlet cracking in the Goupitan and Xiaowan arch dams by use of the nonlinear finite element method. The paper “Real-time safety risk assessment based on a real-time location system for hydropower construction sites” by H. Jiang et al. proposes a method for real-time safety risk assessment for the hydropower construction site. The paper “Ant colony optimization analysis on overall stability of high arch dam basis of field monitoring” by P. Lin et al. conducts a dam ant colony optimization analysis of the overall stability of the high arch dam on the complicated foundation. The paper “Displacement back analysis for a high slope of the Dagangshan hydroelectric power station based on BP neural network and particle swarm optimization” by Z. Liang et al. presents a displacement back analysis for the slope using an artificial neural network model and particle swarm optimization model. The paper “Uplifting behavior of shallow buried pipe in liquefiable soil by dynamic centrifuge test” by B. Huang et al. carries out the dynamic centrifuge model test to investigate the uplifting behavior of the shallow buried pipeline subjected to seismic vibration in the liquefied site.

The shift of modal parameters induced by temperature fluctuation may mask the changes of vibration properties caused by structural damage and result in false structural condition identification. Thoroughly understanding the temperature effects on vibration properties of long-span bridges becomes an especially important issue before vibration-based damage detection methodologies are applied in real bridges. This paper presents an overview of current research activities and developments in the field of correlations between temperatures and vibration properties of long-span bridges. The theoretical derivation methods using classical structural dynamics and closed-form formulations are first briefly introduced. Then the trend analysis methods that are intended to extract the degree of variability in vibration property under temperature variation for different bridges by numerical analysis, laboratory test, or field monitoring are reviewed in detail. Following that, the development of quantitative models to quantify the temperature influence on vibration properties is discussed including the linear model, nonlinear model, and learning model. Finally, some promising research efforts for promoting the study of correlations between temperatures and vibration properties of long-span bridges are suggested.

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods’ effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Structural health monitoring (SHM) systems have shown great potential to sense the responses of a bridge system, diagnose the current structural conditions, predict the expected future performance, provide information for maintenance, and validate design hypotheses. Wireless sensor networks (WSNs) that have the benefits of reducing implementation costs of SHM systems as well as improving data processing efficiency become an attractive alternative to traditional tethered sensor systems. This paper introduces recent technology developments in the field of bridge health monitoring using WSNs. As a special application of WSNs, the requirements and characteristics of WSNs when used for bridge health monitoring are firstly briefly discussed. Then, the state of the art in WSNs-based bridge health monitoring systems is reviewed including wireless sensor, network topology, data processing technology, power management, and time synchronization. Following that, the performance validations and applications of WSNs in bridge health monitoring through scale models and field deployment are presented. Finally, some existing problems and promising research efforts for promoting applications of WSNs technology in bridge health monitoring throughout the world are explored.

For use in fire resistance calculations, the relevant thermal properties of high-performance concrete (HPC) with fly ash were determined through an experimental study. These properties included compressive strength, cubic compressive strength, cleavage strength, flexural strength, and the ultrasonic velocity at various temperatures (20, 100, 200, 300, 400 and 500∘C) for high-performance concrete. The effect of temperature on compressive strength, cubic compressive strength, cleavage strength, flexural strength, and the ultrasonic velocity of the high-performance concrete with fly ash was discussed according to the experimental results. The change of surface characteristics with the temperature was observed. It can serve as a reference for the maintenance, design, and the life prediction of high-performance concrete engineering, such as high-rise building, subjected to elevated temperatures.

Large and complex civil infrastructures are especially susceptible to random vibrations, whether they are from high ground accelerations, strong wind forces, or abnormal loads such as explosions. Thus, it is imperative that the robust and continuous health monitoring system needs to be designed and implemented so as to meet the demanding goals of increasing structural safety and reliability, while reducing its operating and maintenance costs. The efficiency of a structural health monitoring system (SHMS) relies on the sensitivity of the acquired data to structural changes that may be obtained by an extended sensor network on structures as shown in “Methodology developments in sensor placement for health monitoring of civil infrastructures” and [1]. Recent advances in sensing technologies have enabled the use of large numbers of sensors for health monitoring of civil infrastructures. The sensors utilized in an SHMS are required to monitor not only the structural status including the stress, displacement, and acceleration but also those influential environmental parameters, such as the wind speed, temperature, and quality of its foundation. Since a large sensor network needs to be involved in an SHMS, how to deploy it in a complicated, spatially extended structure so that the data acquired from those locations will result in the best identification of structural characteristics will be a challenging task. On the other hand, a high cost of data acquisition systems (sensors and their supporting instruments) and accessibility limitation constrain in many cases the wide distribution of a large sensor networks on a structure. Especially, many civil structures have to be tested under operational conditions, in which the sensors are not easily amenable to be removed or changed [2, 3]. It is, therefore, of increasing interests to seek rational placement and design a method of sensor networks that contain as much information as possible about the health state of a structure. This special issue aims to aggregate the latest research efforts contributing to theoretical, methodological, and technological advances in the integration of various aspects of SHMS applications within a broad range of disciplines. Some research topics towards this target include intelligent and efficient algorithms in the design of sensor networks; evaluation criteria for different sensor networks placement methods; inherent relationship between different sensor networks placement methods; uncertainty, sensitivity, reliability, and redundancy in sensor networks; application of large scale sensors for civil infrastructures and others related. A total of 26 peer-reviewed papers have been presented in this special issue. These include identifying the optimal number and location of sensors, as well as the robustness, which aims at maintaining the stability of the sensor network when some sensors malfunction, and so forth. Without a doubt, the papers reflect the state-of-the-art researches and developments of this subject. The Guest Editor would like to express his sincere appreciation to all the authors who have contributed their work to this special issue.

Summary Optimal triaxial sensor placement plays a crucial role in tridimensional modal identification; however, few studies have been conducted on this topic. In this paper, a holistic approach, including a tridimensional optimal criterion and solution method, is proposed for finding the optimal locations to deploy triaxial sensors. The tridimensional optimal criterion is established by combining the tridimensional modal assurance criterion and the redundancy function. The tridimensional modal assurance criterion is deduced from the one-dimensional modal assurance criterion by using the widely accepted Fisher information matrix, adopted to ensure the linear independence of identified tridimensional mode shapes. The redundancy function, which is defined by the similarity index among nodes, is developed to measure the information redundancy and to maintain effective visualization of the identified tridimensional mode shapes. To efficiently find the optimal triaxial sensor configuration with the proposed tridimensional optimal criterion, the hierarchic wolf algorithm (HWA) is developed by imitating the swarm intelligence embedded in the wolf pack. Five strategies, which are termed as coding and spreading wolves, searching behaviors, attacking behaviors, hierarchic population, and distributing food process, are employed to enhance the global searching ability of the HWA. The proposed approach is verified by a benchmark bridge model. The results indicate that the established tridimensional optimal criterion has the capability of ensuring optimal triaxial sensor configurations that make the identified tridimensional mode shapes have features of excellent linear independence and good visualization, and the HWA has strong ability and high efficiency in determining the global optimal triaxial sensor configuration.

Timely and correctly evaluating the quality of Global Positioning System (GPS) data is essential for reduction in the number of false alarms and missed detection of a GPS-based bridge deformation monitoring system. This paper investigates how to use the statistical process control technique, known as the cumulative sum (CUSUM) chart, for the detection of small but persistent shifts in the high-rate GPS carrier-phase measurements. First, a mathematical model for the shift detection based on the continuous hypothesis testing is established. The main features and implementation procedure of the CUSUM chart for the shift detection are then summarized, and the corresponding parameter selection method is discussed in detail. To meet the normality requirement of the CUSUM chart, a novel method that transfers the data to the Q-statistic by the estimated cumulative distribution functions is proposed according to the probability integral transform theory. This is followed by a simulation carried out to evaluate the detection performance of the CUSUM chart and exploit its advantages to the commonly used Shewhart chart for the high-rate GPS monitoring data with different shift sizes. Experimental results have showed that the CUSUM chart is sensitive to small persistent shifts compared to the Shewhart chart although it has a delay problem. The integration of CUSUM chart and Shewhart chart would be a reliable approach for the shift detection. Finally, an on-site dynamic monitoring experiment is carried out on a long-span bridge to validate the proposed approach’s effectiveness in detecting an actual deformation shift, and the experimental results proved to be very encouraging.

The peripheral structure of Dalian stadium is a long-span spatial truss structure. To ensure the safety of the peripheral structure during construction and operation period, the permanent structure health monitoring system is implemented. This paper first introduces the structural features of the Dalian stadium, and then illustrates the permanent monitoring program from the aspects of the hardware, the monitoring scheme and the function. This developed monitoring system is utilized to monitor the stress of the truss, and the dynamic response of the structure. Large amounts of data are obtained through the health monitoring system, and thus the safe condition of the structure can be evaluated based on data analysis.

The project of Hangzhou Metro Line 1 is the first metro line of the urban rapid rail transit system in Hangzhou, China, which is one of the largest municipal projects of Hangzhou and is being constructed commencing from March 28, 2007 and expected to be completed by October 1, 2012. This metro line has a total length of 48 km and 34 stations, connecting Hangzhou downtown with the suburban area of the city. Owing to the complex geological condition, harsh construction situation, and immature computational methodology, construction of metro systems is often subjected to considerable sources of uncertainties. To ensure the safety of the adjacent building structures, it is a vital necessity to monitor deep excavations of metro tunnels at their in-construction stage. This paper introduces the instrumentation system for settlement monitoring of a metro-tunnel airshaft of the project of Hangzhou Metro Line 1 during the construction of deep excavation. The long-term settlement data monitored by the measurement markers installed at the surface ground and in the depth direction of the airshaft excavation construction site are analyzed and presented in detail. The obtained results indicate that the settlements at the instrumented locations of the construction site during different construction steps vary steadily in an allowable variation range.

Presently, the researches of displacement-based seismic design almost belong to two dimensions analysis. Both theoretical researches and seismic disasters indicate that the torsion responses can aggravate destroying of the asymmetry-plan buildings. Furthermore, the determinations of structural stiffness in the current procedure are almost dependent on subjective experience of designers which is not rational and economical. So, a method that uses displacement as the basis for the stiffness design of asymmetric-plan buildings is then presented: (1)By means of conceptual design, the initial structure are designed, the mode shapes and periods are then calculated by modal analysis and the weak members of the building are found out by dynamic analysis; (2) The target period and lateral equivalent stiffness are determined according to target displacement; (3) The lateral stiffness of initial designed structure is adjusted to make the displacement responses of the weakness members meet the limited displacements by the parameter of stiffness adjustment. Finally, an example is implemented in the paper for demonstrating the process and verifying the accuracy of the procedure.

In recent years, China has been undergoing a metro railway construction boom in order to alleviate the urban traffic congestion problem resulting from the rapid urbanization and population growth in many metropolises. In the construction of metro systems, deep excavations and continuous dewatering for construction of the metro tunnels and stations remain a challenging and high risk task in densely populated urban areas. Intelligent computational methods and techniques have exhibited the exceptional talent in dealing with the complicated problems inherent in the deep excavation and dewatering practice. In this paper, an intelligent risk assessment system for deep excavation dewatering is developed and has been applied in the project of Hangzhou Metro Line 1 which is the first metro line of the urban rapid rail transit system in Hangzhou, China. The specific characteristics and great challenges in deep excavation dewatering of the metro-tunnel airshaft of Hangzhou Metro Line 1 are addressed. A novel design method based on the coupled three-dimensional flow theory for dewatering of the deep excavation is introduced. The modularly designed system for excavation dewatering risk assessment is described, and the field observations in dewatering risk assessment of the airshaft excavation of Hangzhou Metro Line 1 are also presented.

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. Based on the criterion of the OSP for the modal test, an improved genetic algorithm, called “generalized genetic algorithm (GGA)”, is adopted to find the optimal placement of sensors. The dual-structure coding method instead of binary coding method is proposed to code the solution. Accordingly, the dual-structure coding-based selection scheme, crossover strategy and mutation mechanism are given in detail. The tallest building in the north of China is implemented to demonstrate the feasibility and effectiveness of the GGA. The sensor placements obtained by the GGA are compared with those by exiting genetic algorithm, which shows that the GGA can improve the convergence of the algorithm and get the better placement scheme.

1 School of Civil Engineering, Dalian University of Technology, Dalian 116023, China 2 School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China 3Medway School of Engineering, The University of Greenwich, Kent ME4 4TB, UK 4Marand Faculty of Engineering, University of Tabriz, Tabriz 51368, Iran 5 School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA

To attain high accuracy results from GPS, the carrier phase observables have to be used to update the filter's states. However, a cycle slip that remains uncorrected will significantly degrade the filter's performance. In this paper, a novel method that can effectively detect and identify the small cycle slip is presented. First, the location of the cycle slip is detected by ascertaining the point of modulus maximal value of the wavelet coefficients since the cycle slip can be regarded as the singular point of the signal. Secondly, two kinds of prediction models based on artificial neural network (ANN) are established to correct the cycle slip. Experimental results with real data sets indicate that the method is effective and feasible.

In this paper, the control approach to irregular structures excited by multi-dimensional ground motions is presented by using semi-active tuned liquid column damper (TLCD). A back propagation Artificial Neural Network (ANN) is used to predict the responses of structure due to two-dimensional seismic inputs. The semi-active control strategy is established and implemented based on ANN. The numerical examples have shown that it is an effective method presented for controlling the translational and rotational responses of irregular structures.

In order to attain high precision positioning and navigation results with GPS, cycle slips must be correctly detected and repaired at the data preprocessing stage. Based on the characteristics of cycle slip we analyzed, a novel two-stage method was developed. Firstly, the wavelet multi-resolution analysis (MRA) is carried out and then the location of the cycle slip can be detected by ascertaining the point of modulus maximal value of the wavelet coefficients since the cycle slip can be regarded as the singular point of the signal. Secondly, two prediction models based on artificial neural network (ANN) are established respectively at the both side of the cycle slip. The actual number of cycle slip can be determined through comparing the difference of forecasting data of the two prediction models. Finally, test results are presented to demonstrate the feasibility and validity of the method.