Variation of temperature is a primary environmental factor that affects the behavior of structures. Therefore, understanding the mechanisms of normal temperature-induced variations of structural behavior would help in distinguishing them from anomalies. In this study, we used the structural health monitoring data of the Shanghai Yangtze River Bridge, a steel girder cable-stayed bridge, to investigate the mechanisms of thermally induced vertical deflection ($D_T$) at mid-span of such bridges. The $D_T$ results from a multisource combination of thermal expansion effects of the cable temperature ($T_{Cab}$), girder temperature ($T_{Gir}$), girder differential temperature ($T_{Dif}$), and tower temperature ($T_{Tow}$). It could be approximated by multiple linear superpositions under operational conditions. The sensitivities of $D_T$ of the Shanghai Yangtze River Bridge to the above temperatures were in the following order: $T_{Cab}$ > $T_{Gir}$ > $T_{Tow}$ > $T_{Dif}$. However, the direction of the effect of $T_{Cab}$ was observed to be opposite to that of the other three temperatures, and the magnitudes of the effects of $T_{Cab}$ and $T_{Gir}$ were found to be almost one order greater than those of $T_{Dif}$ and $T_{Tow}$. The mechanisms of the thermally induced vertical deflection variation at mid-span of a cable-stayed bridge as well as the analytical methodology adopted in this study could be applicable for other long-span cable-stayed bridges.

Structural health monitoring of steel truss bridge based on changes in modal properties was investigated in this study. Vibration measurements with five sensors were conducted at an existing Warren truss bridge with partial fractures in diagonal members before and after an emergency repair work. Modal properties identified by the Eigensystem Realization Algorithm showed evidences of increases in modal damping due to the damage in diagonal member. In order to understand the dynamic behavior of the bridge and possible mechanism of those increases in modal damping, theoretical modal analysis was conducted with three dimensional frame models. It was found that vibrations of the main truss could be coupled internally with local vibrations of diagonal members and the degree of coupling could change with structural changes in diagonal members. Additional vibration measurements with fifteen sensors were then conducted so as to understand the consistency of those theoretical findings with the actual dynamic behavior. Modal properties experimentally identified showed that the damping change caused by the damage in diagonal member described above could have occurred in a diagonal-coupled mode. The results in this study imply that damages in diagonal members could be detected from changes in modal damping of diagonal-coupled modes.

The condition of the vehicular bridge network in New York City, as represented by ratings obtained during biennial inspections is reviewed over a period of three decades. Concurrently, the bridges comprising the network are considered as networks of structural elements whose condition defines the overall bridge condition according to New York State assumptions. A knowledge-based matrix of assessments is used in order to determine each element's vulnerability and impact within the network of an individual structure and the network of City bridges. In both networks expansion deck joints emerge as the weak link. Typical joint failures are illustrated. Bridge management options for maintenance, preservation, rehabilitation and replacement are examined in the context of joint performance.

The large number of long-span bridges constructed in China motivates the applications of structural health monitoring (SHM) technology. Many bridges have been equipped with sophisticated SHM systems in the mainland of China and in Hong Kong of China. Recently, SHM technology has been extended to field test systems. In this view, SHM can serve as a tool to develop the methods of life-cycle performance design, evaluation, maintenance and management of bridges; to develop new structural analysis methods through validation and feedback from SHM results; and to understand the behavior of bridges under natural and man-made disasters, rapidly assess the damage and loss of structures over large regions after disasters, e.g., earthquake, typhoon, flood, etc. It is hoped that combining analytical methods, numerical simulation, small-scale tests and accelerated durability tests with SHM could become the main engine driving the development of bridge engineering. This paper demonstrates the above viewpoint.

Damage quantification is a major goal of the SHM community. Methodologies to introduce a quantity for actual condition of a structure into the assessment process are desired. The idea that the condition of a structure is represented in the character of its dynamic response is fully accepted by the SHM community. The VCLIFE methodology quantifies condition analyzing input from monitoring.

In many of the industrialized countries an increasing amount of infrastructure is ageing. This has become specifically critical to bridges which are a major asset with respect to keeping an economy alive. Life of this infrastructure is scattering but often little quantifiable information is known with respect to its damage condition. This article describes how a damage tolerance approach used in aviation today may even be applied to civil infrastructure in the sense that operational life can be applied in the context of modern life cycle management. This can be applied for steel structures as a complete process where much of the damage accumulation behavior is known and may even be adopted to concrete structures in principle, where much of the missing knowledge in damage accumulation has to be substituted by enhanced inspection. This enhanced and continuous inspection can be achieved through robotic systems in a first approach as well as built in sensors in the sense of structural health monitoring (SHM).

Management of infrastructure stock is essential in sustainability of society, and its analysis and optimization are studied in the light of control system modeling in this paper. At the first part of the paper, cost of stock management is analyzed based on macroscopic statistics on infrastructure stock and economical growth. Stock management burden relative to economy is observed to become larger at low economic growth periods in developed economies. Then, control system modeling of stock management is introduced and by augmenting maintenance actions as control input, dynamic behavior of stock is simulated and compared with existing time history statistics. Assuming steady state conditions, applicability of the model to cross sectional data is also demonstrated. The proposed model is enhanced so that both preventive and corrective maintenance can be included as system inputs, i.e., feedforward and feedback control inputs. Optimal management strategy to achieve specified deteriorated stock level with minimal cost, expressed in terms of preventive and corrective maintenance actions, is derived based on estimated parameter values for corrosion of steel bridges. Relative cost effectiveness of preventive maintenance is shown when target deteriorated stock level is lower.

Negative stiffness, previously emulated by active or semi-active control for cable vibration mitigation, is realized passively using a self-contained highly compressed spring, the negative stiffness device (NSD).The NSD installed in parallel with a viscous damper (VD) in the vicinity of cable anchorage, enables increment of damper deformation during cable vibrations and hence increases the attainable cable damping. Considering the small cable displacement at the damper location, even with the weakening device, the force provided by the NSD-VD assembly is approximately linear. Complex frequency analysis has thus been conducted to evaluate the damping effect of the assembly on the cable; the displacement-dependent negative stiffness is further accounted by numerical analysis, validating the accuracy of the linear approximation for practical ranges of cable and NSD configurations. The NSD is confirmed to be a practical and cost-effective solution to improve the modal damping of a cable provided by an external damper, especially for super-long cables where the damper location is particularly limited. Moreover, mathematically, a linear negative stiffness and viscous damping assembly has proven capability to represent active or semi-active control for simplified cable vibration analysis as reported in the literature, while in these studies only the assembly located near cable anchorage has been addressed. It is of considerable interest to understand the general characteristics of a cable with the assembly relieving the location restriction, since it is quite practical to have an active controller installed at arbitrary location along the cable span such as by hanging an active tuned mass damper. In this paper the cable frequency variations and damping evolutions with respect to the arbitrary assembly location are then evaluated and compared to those of a taut cable with a viscous damper at arbitrary location, and novel frequency shifts are observed. The characterized complex frequencies presented in this paper can be used for preliminary damping effect evaluation of an adaptive passive or semi-active or active device for cable vibration control.

Recently, an indirect displacement estimation method using data fusion of acceleration and strain (i.e., acceleration-strain-based method) has been developed. Though the method showed good performance on beam-like structures, it has inherent limitation in applying to more general types of bridges that may have complex shapes, because it uses assumed analytical (sinusoidal) mode shapes to map the measured strain into displacement. This paper proposes an improved displacement estimation method that can be applied to more general types of bridges by building the mapping using the finite element model of the structure rather than using the assumed sinusoidal mode shapes. The performance of the proposed method is evaluated by numerical simulations on a deck arch bridge model and a three-span truss bridge model whose mode shapes are difficult to express as analytical functions. The displacements are estimated by acceleration-based method, strain-based method, acceleration-strain-based method, and the improved method. Then the results are compared with the exact displacement. An experimental validation is also carried out on a prestressed concrete girder bridge. The proposed method is found to provide the best estimate for dynamic displacements in the comparison, showing good agreement with the measurements as well.

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

A modal parameter based damage sensitive feature (DSF) is defined to mimic the relative change in any diagonal element of the stiffness matrix of a model of a structure. The damage assessment is performed in a statistical pattern recognition framework using empirical complementary cumulative distribution functions (ECCDFs) of the DSFs extracted from measured operational vibration response data. Methods are discussed to perform probabilistic structural health assessment with respect to the following questions: (a) "Is there a change in the current state of the structure compared to the baseline state?", (b) "Does the change indicate a localized stiffness reduction or increase?", with the latter representing a situation of retrofitting operations, and (c) "What is the severity of the change in a probabilistic sense?". To identify a range of normal structural variations due to environmental and operational conditions, lower and upper bound ECCDFs are used to define the baseline structural state. Such an approach attempts to decouple "non-damage" related variations from damage induced changes, and account for the unknown environmental/operational conditions of the current state. The damage assessment procedure is discussed using numerical simulations of ambient vibration testing of a bridge deck system, as well as shake table experimental data from a 4-story steel frame.

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

Although timber structures have been extensively used in underground temporary supporting system, their actual performance is poorly understood, resulting in potentially conservative and over-engineered design. In this paper, a novel wireless sensor technology, SmartPlank, is introduced to monitor the field performance of timber structures during underground construction. It consists of a wooden beam equipped with a streamlined wireless sensor node, two thin foil strain gauges and two temperature sensors, which enables to measure the strain and temperature at two sides of the beam, and to transmit this information in real-time over an IPv6 (6LowPan) multi-hop wireless mesh network and Internet. Four SmartPlanks were deployed at the London Underground's Tottenham Court Road (TCR) station redevelopment site during the Stair 14 excavation, together with seven relay nodes and a gateway. The monitoring started from August 2013, and will last for one and a half years until the Central Line possession in 2015. This paper reports both the short-term and long-term performances of the monitored timber structures. The grouting effect on the short-term performance of timber structures is highlighted; the grout injection process creates a large downward pressure on the top surface of the SmartPlank. The short and long term earth pressures applied to the monitored structures are estimated from the measured strains, and the estimated values are compared to the design loads.

Due to corrosion, a large number of belt conveyors support structure in industrial plants have deteriorated. Severe corrosion may result in collapse of the structures. Therefore, practical and effective structural assessment techniques are needed. In this paper, damage identification methods based on two specific local vibration modes, named periodic and isolated local vibration modes, are proposed. The identification methods utilize the facts that support structures have many identical members repeated along the belt conveyor and there exist some local modes within a small frequency range where vibrations of these identical members are much larger than those of the other members. When one of these identical members is damaged, this member no longer vibrates in those modes. Instead, the member vibrates alone in an isolated mode with a lower frequency. A damage identification method based on frequencies comparison of these vibration modes and another method based on amplitude comparison of the periodic local vibration mode are explained. These methods do not require the baseline measurement records of undamaged structure. The methods is capable of detecting multiple damages simultaneously. The applicability of the methods is experimentally validated with a laboratory model and a real belt-conveyor support structure.

When a building structure requires both health monitoring system and vibration control system, integrating the two systems together will be cost-effective and beneficial for creating a smart building structure with its own sensors (nervous system), processors (brain system), and actuators (muscular system). This paper presents a real-time integrated procedure to demonstrate how health monitoring and vibration control can be integrated in real time to accurately identify time-varying structural parameters and unknown excitations on one hand, and to optimally mitigate excessive vibration of the building structure on the other hand. The basic equations for the identification of time-varying structural parameters and unknown excitations of a semi-active damper-controlled building structure are first presented. The basic equations for semi-active vibration control of the building structure with time-varying structural parameters and unknown excitations are then put forward. The numerical algorithm is finally followed to show how the identification and the control can be performed simultaneously. The results from the numerical investigation of an example building demonstrate that the proposed method is feasible and accurate.

Magneto-Rheological (MR) dampers are being used increasingly because of their adaptability to control algorithms and reliability of passive systems. In this paper, an extensive investigation on performance of MR dampers in semi-active and passive modes has been carried out. It is observed that the overall energy dissipation by MR dampers in passive-on modes is higher than that in semi-active modes for most of the competitive semi-active controllers. Based on the energy dissipation pattern, a novel semi-active controller, termed as "Simple Passive Semi-Active Controller", has been proposed for MR dampers. This controller can be emulated by a simple passive hardware proposed in this paper. The proposed concept of controller "hardware emulation" is innovative and can also be implemented for other semi-active devices for control algorithms of certain form. The effectiveness and reliability of the proposed controller has been investigated extensively through numerical simulations. It has been demonstrated that the proposed controller is competitive to or more effective than other widely used / investigated semi-active controllers.

Typical base isolated buildings are designed so that the superstructure remains elastic in design-level earthquakes, though the isolation layer is often quite nonlinear using, e.g., hysteretic elements such as lead-rubber bearings and friction pendulum bearings. Similarly, other well-performing structural control systems keep the structure within the linear range except during the most extreme of excitations. Design optimization of these isolators or other structural control systems requires computationally-expensive response simulations of the (mostly or fully) linear structural system with the nonlinear structural control devices. Standard nonlinear structural analysis algorithms ignore the localized nature of these nonlinearities when computing responses. This paper proposes an approach for the computationally-efficient optimal design of passive isolators by extending a methodology previously developed by the authors for accelerating the response calculation of mostly linear systems with local features (linear or nonlinear, deterministic or random). The methodology is explained and applied to a numerical example of a base isolated building with a hysteretic isolation layer. The computational efficiency of the proposed approach is shown to be significant for this simple problem, and is expected to be even more dramatic for more complex systems.

This paper experimentally investigates the effectiveness and applicability of the time delay control (TDC) algorithm, which is simple and robust to unknown system dynamics and disturbance, for an active mass damper (AMD) system to mitigate the excessive vibration of a building structure. To this end, the theoretical background including the mathematical formulation of the control system is first described; and then, a thorough experimental study using a shaking table system with a small-scale three-story building structural model is conducted. In the experimental tests, the performance of the proposed control system is examined by comparing its structural responses with those of the uncontrolled system in the free vibration and forced vibration cases. It is clearly verified from the test results that the TDC algorithm embedded AMD system can effectively reduce the structural response of the building structure.

The authors' research group has developed a noncontact type of sensors which directly measure the inter-story drift displacements of a building during a seismic event. Soon after that event, such seismically-induced drift displacement data would provide structural engineers with useful information to judge how the stories have been damaged. This paper presents a scheme of estimating the story cumulative plastic deformation ratios based on such measured drift displacement information toward the building safety monitoring. The presented scheme requires the data of story drift displacements and the ground motion acceleration. The involved calculations are rather simple without any detailed information on structural elements required: the story hysteresis loops are first estimated and then the cumulative plastic deformation ratio of each story is evaluated from the estimated hysteresis. The effectiveness of the scheme is demonstrated by utilizing the data of full-scale building model experiment performed at E-defense and conducting numerical simulations.

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

Hybrid simulation is increasingly being recognized as a powerful technique for laboratory testing. It offers the opportunity for global system evaluation of civil infrastructure systems subject to extreme dynamic loading, often with a significant reduction in time and cost. In this approach, a reference structure/system is partitioned into two or more substructures. The portion of the structural system designated as 'physical' or 'experimental' is tested in the laboratory, while other portions are replaced with a computational model. Many researchers have quite effectively used hybrid simulation (HS) and real-time hybrid simulation (RTHS) methods for examination and verification of existing and new design concepts and proposed structural systems or devices. This paper provides a detailed perspective of the enabling role that HS and RTHS methods have played in advancing the practice of earthquake engineering. Herein, our focus is on investigations related to earthquake engineering, those with CURATED data available in their entirety in the NEES Data Repository.