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Nonlinear energy sink (NES) devices have recently been introduced as a means of passive structural control and have been shown to effectively dissipate energy from structural systems during extreme vibrations. Due to their essential geometric nonlinearities, time domain based methods are often applied for identifying their system parameters, which is a challenging task. The unscented Kalman filter (UKF) has been shown in numerical studies to be robust to highly nonlinear systems with noisy data and therefore presents a promising option for identification. In this study, the UKF is used to determine the model parameters of an experimental NES device whose behavior is governed by a geometric nonlinearity in its stiffness and a friction-based nonlinearity in its damping. The standard implementation of the UKF is compared with two implementation methods developed by the authors, which vary in their use of experimental responses to train the NES device model. The impact of choosing different prior distributions on the parameters is also analyzed through Latin hypercube sampling to enhance the quality of the identification for practical implementation, where the prior distribution on the parameters is often ill-defined. The identified models generated using one of the proposed UKF implementation methods is shown to provide a robust model of the NES, demonstrating that the UKF can be used for parameter identification with this class of devices.

Real-time hybrid simulation (RTHS) is gaining acceptance as an efficient and cost-effective method for realistic structural evaluation. Advances in real-time computing and control methods have enabled research in the development of this novel methodology to progress rapidly. However, to explore effectiveness and accuracy, and thus build broader confidence in the use of this method as an alternative to shake table testing, there is a need to better understand and address the key features that determine the success of an RTHS. Here we discuss the design and analysis of a SDOF RTHS case study conducted in Purdue University’s Intelligent Infrastructure Systems Lab (IISL). We examine the key factors that determine the success, through configuration of the test using predictive indicators, design of an appropriately effective actuator controller, and a thorough comparison with shake table testing. The reference structure chosen for this case study is a single story, moment resisting frame structure. This particular specimen is of lab scale and well-known component properties, making it a suitable choice for such an investigation. However, noise, control–structure interaction and damping introduce numerous challenges typically faced in establishing an effective RTHS configuration. We investigate two key issues that lead to the design of a successful RTHS, specifically the partitioning between numerical and physical substructure for stability and performance, and the actuator motion control algorithm. Predictive indicators are demonstrated to be particularly helpful for properly configuring an RTHS experiment to meet a researcher’s specified objectives. Furthermore a direct comparison is conducted to examine the ability of RTHS to replicate a shake table test. The results demonstrate that with proper partitioning and actuator control design, successful RTHS can be implemented despite unfavorable transfer system properties.

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

The initiation and propagation of damage such as cracks in an engineering structure under dynamic loadings is a nonlinear process. Strictly speaking, conventional eigenvalue and eigenvector extraction-based damage identification approaches are suitable for linear systems only. Due to the unique nonlinearities associated with each civil engineering structure, it would be inefficient to attempt to express the nonlinear restoring force (NRF) of an engineering structure such as a reinforced concrete structure in a parametric form. Consequently, it is highly desirable to develop a general nonlinear identification approach to achieve structural damage detection in both qualitative and quantitative ways without the assumption on the parametric model of the hysteretic behavior. In this paper, based on a double Chebyshev polynomial function, a time-domain identification approach is proposed for identifying both the structural NRF and the mass distribution for multi-degree-of-freedom (MDOF) structures under incomplete dynamic loadings. As a typical nonlinear material, shape memory alloy (SMA) is introduced to a MDOF structural model to mimic the nonlinear behavior under dynamic loadings. The feasibility and robustness of the proposed approach is validated via (1) a numerical MDOF structure model equipped with a SMA damper whose restoring force is described by a double-flag-shaped nonlinear model, and (2) an experimental study on a four-story shear building structure model equipped with an in-house design of a SMA damper used to mimic the structural NRF under incomplete impact loadings. The identified NRF is compared with the theoretical values and the measurements in experiment. Both numerical and experimental results show that the proposed approach is capable of identifying both the mass distribution and structural nonlinearity under dynamic loadings, and could be potentially used for damage initiation and propagation monitoring during vibration of engineering structures under dynamic excitations.

Stability in Real Time Hybrid Simulation (RTHS) has been shown to be largely affected by system dynamics and associated phase lags. This lag typically originates in the physical components and considerable research has been conducted to compensate for it. Within the computational component of RTHS, different time integration algorithms are employed to achieve a more stable and accurate solution, mostly focusing on dissipating the high frequency content in the model. However, in RTHS, an inherent computational delay exists in the force measurement due to the sequential nature of communication between the numerical and experimental sub- structures. In this article, it is demonstrated that this computational delay affects performance and stability of closed loop RTHS even when no other delays or phase lags are present. This finding is validated through theoretical derivation and simulation results. A modified Runge-Kutta (MRK) integration algorithm is proposed to reduce the effect of computational delay.The ...

Summary Structural control systems offer an attractive approach to protect civil infrastructures from natural hazards such as earthquakes. Wireless structural control systems that utilize wireless sensors for sensing, communication, and control have drawn increased attention because of the flexible installation, rapid deployment, and reduced cost. Although there are studies of wireless control systems for civil structures, a benchmark problem that captures not only the dynamics of the plant but also the realistic features of a wireless network has not been available. In this paper, a benchmark model for an active mass driver system with a wireless sensor network is presented. This wireless control benchmark model combines a seismically excited building benchmark model developed with Simulink (Matlab, MathWorks, Inc., Natick, MA, USA) and a wireless sensor network implemented in simulation using a state-of-the-art wireless simulator TOSSIM (UC Berkeley, Berkeley, CA, USA). Wireless signal and noise traces collected from a real-world multistory building are used as inputs to TOSSIM to realistically simulate the wireless sensor network. Wireless control design issues such as network-induced delay, data loss, available sensor measurements, measurement noises, and control constraints can be studied with this benchmark model. A sample controller is provided to illustrate the wireless control design. Evaluation criteria have been provided to examine resources and control performances. Copyright © 2015 John Wiley & Sons, Ltd.

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.

In research on damage identification, conventional methods usually face difficulties in converging globally and rapidly. Therefore, a fast in-time damage identification approach based on the Kalman filter and energy equilibrium theory is proposed to obtain the structural stiffness, find the locations of damage, and quantify its intensity. The proposed approach establishes a relationship between the structural stiffness and acceleration response by means of energy equilibrium theory. After importing the structural energy into the Kalman filter algorithm, unknown parameters of the structure can be obtained by comparing the predicted energy and the measured energy in each time step. Numerical verification on a highway sign support truss with and without damage indicates that the updated Young’s modulus can converge to the true value rapidly, even under the effects of external noise excitation. In addition, the calculation time taken for each step of the approach is considerably shorter than the sampling period (1/256 s), which means that, this approach can be implemented in-time and on-line.

Visual assessment is a process to understand the state of a structure based on evaluations originating from visual data. Low-cost, high-performance vision sensors are providing new avenues for overcoming the spatial and temporal limitation in current human-based visual assessment when used in conjunction with aerial sensing platforms. However, past implementations are limited in their ability to deal with a high volume of images while only a small fraction of them are important for actual inspection. Such difficulty induces an unwanted high rate of false-positive and negative errors, reducing the trustworthiness and efficiency of their implementation. To overcome this challenge, we develop and validate a novel automated image localization and classification technique to extract regions-of-interest (ROIs) on each of images, which contain the target region of the structure for visual evaluation (TRI). First, ROIs are extracted based on the geometric relationship between the collected images and the TRIs using structure-from-motion algorithm. Second, unwanted ROIs corrupted by occlusion and image blur are effectively filtered by a robust image classification technique, called convolutional neural network. Then, a damage detection technique is applied only on such highly relevant and localized ROI images. The capability of the technique is demonstrated using a full-scale highway sign structure for the case of crack detection on weld connections.

This paper presents the problem definition and guidelines for a benchmark control problem in real-time hybrid simulation for a seismically excited building, to appear in a Special Issue of Mechanical Systems and Signal Processing. Benchmark problems have been especially useful in enabling a community of researchers to leap forward on a given topic, distill the lessons learned, and identify the capabilities and limitations of various approaches. The focus here is on the design of an effective transfer system displacement tracking controller which is a commonly used approach for ensuring that interface conditions between numerical and experimental substructures are satisfied. In this study, a laboratory model of a three-story steel frame is considered as the reference structure. Realistic numerical models are developed and provided to represent the numerical and experimental substructures and the transfer system, which is comprised of hydraulic actuation, sensing instrumentation, and control implementation hardware. Experimental components are identified and provided as Simulink models, which are executed in real-time using Simulink Desktop Real-Time capability to enable realistic virtual real-time hybrid simulation. The task of each participant of the Special Issue is to design, evaluate, and report on their proposed controller approaches using the numerical models and computational codes provided. Such approaches will be assessed for robustness and performance using the provided tools. This benchmark problem is expected to further the understanding of the relative merits, as well as provide a clear basis for evaluating the performance of various control approaches and algorithms for RTHS. To illustrate some of the design challenges, a sample control strategy employing a proportional-integral (PI) controller is included, in addition to the built-in control loop of the transfer system.

Real-time hybrid simulation (RTHS) is a promising cyber-physical technique used in the experimental evaluation of civil infrastructure systems subject to dynamic loading. In RTHS, the response of a structural system is simulated by partitioning it into physical and numerical substructures, and coupling at the interface is achieved by enforcing equilibrium and compatibility in real-time. The choice of partitioning parameters will influence the overall success of the experiment. In addition, due to the dynamics of the transfer system, communication and computation delays, the feedback force signals are dependent on the system state subject to delay. Thus, the transfer system dynamics must be accommodated by appropriate actuator controllers. In light of this, guidelines should be established to facilitate successful RTHS and clearly specify: (i) the minimum requirements of the transfer system control, (ii) the minimum required sampling frequency, and (iii) the most effective ways to stabilize an unstable simulation due to the limitations of the available transfer system. The objective of this paper is to establish a stability switch criterion due to systematic experimental errors. The RTHS stability switch criterion will provide a basis for the partitioning and design of successful RTHS.

Summary In this paper, we propose a new actuator control algorithm that achieves the design flexibility, robustness, and tracking accuracy to give real-time hybrid-simulation users the power to achieve highly accurate and robust actuator control. The robust integrated actuator control (RIAC) strategy integrates three key control components: loop shaping feedback control based on H∞ optimization, a linear-quadratic-estimation block for minimizing noise effect, and a feed-forward block that reduces small residual delay/lag. The combination of these components provides flexible controller design to accommodate setup limits while preserving the stability of the H∞ algorithm. The efficacy of the proposed strategy is demonstrated through two illustrative case studies: one using large capacity but relatively slow actuator of 2500 kN and the second using a small-scale fast actuator. Actuator tracking results in both cases demonstrate that the RIAC algorithm is effective and applicable for different setups. Real-time hybrid-simulation validation is implemented using a three-DOF building frame equipped with a magneto-rheological damper on both setups. Results using the two very different physical setups illustrate that RIAC is efficient and accurate. Copyright © 2014 John Wiley & Sons, Ltd.

In a typical Real-time Hybrid Simulation (RTHS) setup, servo-hydraulic actuators serve as interfaces between the computational and physical substructures. Time delay introduced by actuator dynamics and complex interaction between the actuators and the specimen has detrimental effects on the stability and accuracy of RTHS. Therefore, a good understanding of servo-hydraulic actuator dynamics is a prerequisite for controller design and computational simulation of RTHS. This paper presents an easy-to-use parametric identification procedure for RTHS users to obtain re-useable actuator parameters for a range of payloads. The critical parameters in a linearized servo-hydraulic actuator model are optimally obtained from genetic algorithms (GA) based on experimental data collected from various specimen mass/stiffness combinations loaded to the target actuator. The actuator parameters demonstrate convincing convergence trend in GA. A key feature of this parametric modeling procedure is its re-usability under different testing scenarios, including different specimen mechanical properties and actuator inner-loop control gains. The models match well with experimental results. The benefit of the proposed parametric identification procedure has been demonstrated by (1) designing an H ∞ controller with the identified system parameters that significantly improves RTHS performance; and (2) establishing an analysis and computational simulation of a servo-hydraulic system that help researchers interpret system instability and improve design of experiments.

SUMMARY Real-time hybrid simulation (RTHS) is increasingly being recognized as a powerful cyber-physical technique that offers the opportunity for system evaluation of civil structures subject to extreme dynamic loading. Advances in this field are enabling researchers to evaluate new structural components/systems in cost-effective and efficient ways, under more realistic conditions. For RTHS, performance metric clearly needs to be developed to predict and evaluate the accuracy of various partitioning choices while incorporating the dynamics of the transfer system, and computational/communication delays. In addition, because of the dynamics of the transfer system, communication delays, and computation delays, the RTHS equilibrium force at the interface between numerical and physical substructures is subject to phase discrepancy. Thus, the transfer system dynamics must be accommodated by appropriate actuator controllers. In this paper, a new performance indicator, predictive performance indicator (PPI), is proposed to assess the sensitivity of an RTHS configuration to any phase discrepancy resulting from transfer system dynamics and computational/communication delays. The predictive performance indicator provides a structural engineer with two sets of information as follows: (i) in the absence of a reference response, what is the level of fidelity of the RTHS response? and (ii) if needed, what partitioning adjustments can be made to effectively enhance the fidelity of the response? Moreover, along with the RTHS stability switch criterion, this performance metric may be used as an acceptance criteria for conducting single-degree-of-freedom RTHS. Copyright © 2014 John Wiley & Sons, Ltd.

Our deteriorating civil infrastructure faces the critical challenge of long-term structural health monitoring for damage detection and localization. In contrast to existing research that often separates the designs of wireless sensor networks and structural engineering algorithms, this paper proposes a cyber-physical codesign approach to structural health monitoring based on wireless sensor networks. Our approach closely integrates 1) flexibility-based damage localization methods that allow a tradeoff between the number of sensors and the resolution of damage localization, and 2) an energy-efficient, multilevel computing architecture specifically designed to leverage the multiresolution feature of the flexibility-based approach. The proposed approach has been implemented on the Intel Imote2 platform. Experiments on a simulated truss structure and a real full-scale truss structure demonstrate the system's efficacy in damage localization and energy efficiency.

The development of smart structures involves the use of various types of controllable damping devices by integrating them into structural systems for energy dissipation. An optimal feedback control law that can consider the nonlinearity embedded in the systems and the random characteristics of the external inputs is desirable to control such dissipation mechanism. This paper proposes an innovative numerical technique to obtain the optimal feedback control strategy of nonlinear stochastic systems. The systems under investigation are modeled as mechanical oscillators and a damping device. The numerical approach proposed to obtain the optimal control strategy involves solving a nonlinear partial differential equation—the Hamilton–Jacobi–Bellman equation. Because civil engineering structural systems may exhibit nonlinear hysteretic behavior under extreme loading conditions, the application of the obtained control strategy could provide an optimal feedback control law to reduce the system response under random excitations (such as earthquakes, wind load and sea waves). Several numerical examples are presented to verify optimality and demonstrate the efficacy of the proposed optimal control solution. First, a linear oscillator is used to verify that the obtained solution is indeed the optimal solution by comparing it to the closed-form optimal solution. Then the proposed method is applied to several nonlinear systems. In each nonlinear example, control optimality is demonstrated by comparing the system responses and control costs obtained using the proposed optimal controls with those obtained using corresponding linearized optimal controls.

This paper presents comparisons of the performances of three semiactive control algorithms for use with multiple magnetorheological (MR) dampers. The three controllers are (1) the clipped-optimal controller, (2) the decentralized output feedback polynomial controller, and (3) the simple passive controller. These controllers use different types of inputs to calculate control signals for the MR dampers, based on different control mechanisms. To investigate the advantages of each controller, a three-degree-of-freedom steel moment-resisting frame, designed using a performance-based design methodology, was developed. The performance was investigated by using four different earthquakes utilized during the design of the building frame. Comparisons of the controllers’ performance were carried out in terms of reduction in the maximum interstory drifts, displacements, absolute accelerations, and control forces. Real-time hybrid tests were carried out to validate these comparisons.

Model updating procedures are traditionally performed off-line. With the significant recent advances in embedded systems and the related real-time computing capabilities, online or real-time, model updating can be performed to inform decision making and controller actions. The applications for real-time model updating are mainly in the areas of (i) condition diagnosis and prognosis of engineering systems; and (ii) control systems that benefit from accurate modeling of the system plant. Herein, the development of a cyber-physical real-time model updating experimental platform, including real-time computing environment, model updating algorithm, hardware architecture and testbed, is described. Results from two challenging experimental implementations are presented to illustrate the performance of this cyber-physical platform in achieving the goal of updating nonlinear systems in real-time. The experiments consider typical nonlinear engineering systems that exhibit hysteresis. Among the available algorithms capable of identification of such complex nonlinearities, the unscented Kalman filter (UKF) is selected for these experiments as an effective method to update nonlinear dynamic system models under realistic conditions. The implementation of the platform is discussed for successful completion of these experiments, including required timing constraints and overall evaluation of the system.

The detection of changes in vibrational behavior has long been applied as a potential means of damage detection. However, existing damage diagnosis techniques are primarily limited to linear models in which the stiffness of some of the elements is reduced to represent damage. Although these methods appear to be adequate for locating and quantifying the present damage in the structure, they are not sufficient for determining future performance of the structure, which can only be determined using nonlinear models. This paper focuses on the challenging task of updating nonlinear models for reinforced concrete civil engineering structures. A nonlinear hysteretic material model is applied to accurately portray the fundamental hysteretic behavior of concrete structures. A systematic methodology to perform damage detection and, more importantly, update the nonlinear model for prediction is proposed. This new method is designed to use low-level ambient vibration data to detect changes in the modal parameters. With the acquired modal information, the damage parameters that control the nonlinear material model are updated. The final updated nonlinear model may be utilized not only to evaluate the structure’s current damage state but also to predict its future behavior. A concrete shear wall is analyzed numerically to demonstrate the proposed method.

Currently, construction tendencies tend to design flexible structures, such as footbridges, slabs and grandstands, due to the increased resistance of new materials and the regulation gap in building codes. These flexible structures are susceptible of excessive vibrations induced by human activities, producing serviceability failures and, sometimes, collapse. It is essential to improve the understanding of the effect of anthropic loads over the structures to mitigate serviceability problems and the risk of structural damage and, therefore, economic and human loses.

Prior to each payment to contractors and suppliers, measurements are made to document the actual amount of pay items placed at the site. This manual process has substantial risk for personnel, and could be made more efficient and less prone to human errors. In this project a customized software tool package has been developed to address these concerns. The Pay Item Measurement (PIM) tool package is provided as two complementary tools, the Orthophoto Generation Tool and the Graphical Measurement Tool. PIM has been developed in close cooperation with the advisory committee and field engineers from INDOT, and is specifically designed to incorporate the typical actions that INDOT personnel follow. PIM is intended to generate orthophotos for measurements on a planar surface. User guidelines explain the process of how to collect suitable high-quality images, which is a critical step for successful orthophoto construction. INDOT will also use PIM to identify features and make annotations, and to readily compute distances, perimeters, and areas for documenting and recording. This customized tool package will be most useful, and accurate, when the user guidelines are followed. Several examples are included to demonstrate the characteristics of high-quality image sets that will be successful, and to also provide examples of sets that would fail. Step-by-step instructions are provided to demonstrate the correct use of the tool. An instructional video and sample digital image sets complement this report and tool package.

Data are one of the main assets of earthquake engineering. Laboratory experiments can be extremely expensive and time consuming to replicate and, therefore, long-term preservation of experimental data and sharing the data with users has become one of the disciplinary priorities. There is a growing demand for international partnerships, which creates a need for data sharing, in an attempt to maximise research impact and to tackle experimental set-ups that could not be realised otherwise. However, there is a patent lack of interoperability between the institutions forming the earthquake engineering community, which inhibits efficient collaboration between them. In this paper, we discuss a vision about the directions that experimental data should take in the coming years, focusing on two aspects: enhanced international collaborations and implementation of open data access. We also describe the progress that has been made towards this vision, by establishing an open platform for the integration of earthquake hazard mitigation resources called Celestina. Celestina is supported by Semantic Web technologies, and uses an ontology as its integration data model. A prototype of the platform has been developed and tested between NEES (Purdue University, in the US), the University of Oxford (in UK) and EUCENTRE (in Italy), and a small proof of concept has enabled integrated experimental data from Oxford and EUCENTRE through the NEES cyberenvironment. This demonstration provides an example which has the potential to catalyze a new generation of research progress enabled by international data sharing.

The multi-time-step method of time integration for problems in structural dynamics allows one to decompose the problem domain into small subdomains and use different time steps within each subdomain to reduce the computational cost of solving such problems. However, the number of possible decompositions and their associated time steps for a given model is huge and grows exponentially with the number of elements. To find an optimal decomposition that minimizes error in the solution while maintaining a bound on the computational cost is challenging. In this work, existing multi-time-step methods are used and, for the first time, a systematic approach for traversing the space of possible decompositions to characterize the nature of how solution errors and computational costs vary for different decompositions is devised. Through numerical examples for three different types of structures, trusses, frames, and continuum solid bodies, it is shown that the characteristics of these error and cost functions...

This study investigated the safety and stability of light-rail trains that run on multispan simply supported bridges (MSSBs) and have experienced some settling and girder deformation caused by both foundation settlement and girder deflection/camber. A three-dimensional dynamic nonlinear finite-element model for a light-rail train track–MSSB interaction system, which took into account rail irregularities, girder deformation, wheel–rail contact, and coupling effects, was developed. A case study analyzed a four-car light-rail train rolling on a MSSB, and the relationships between the girder deformation and running performance under various speeds were obtained. The results indicate that speed is the dominant factor that contributes to the safety and stability of the light-rail train when girder deformation is present. In addition, the influence of girder deformation was found to be greater on safety than on stability. In real applications, it is recommended to pursue advanced monitoring and evaluatio...

Scientific research has experienced a transformation over the last several decades. To tackle today’s grand challenges in science and engineering, researchers today must leverage and integrate the skills and knowledge of team members with computational resources and infrastructure that include data, computing, communications, and high performance computing resources.

Summary Structural control systems based on wireless sensors offer a convenient, flexible and cost-effective alternative to their wired counterparts. Although wireless control systems (WCSs) have several attractive features, some challenges do remain related to the persistent presence of network-induced time delays, and potential for sensor data losses and in extreme cases, sensor failures. The consequences of these challenges should be investigated, and solutions should be developed to achieve highly effective and robust control systems. The availability of such solutions will also encourage the adoption of WCSs in real structures. Here, an estimator switching method intended to minimize the influence of potential faults is developed and validated for WCSs. In this method, the switching gains are pre-calculated to enable real-time implementation. The proposed method is verified through numerical simulations of a seismically excited, three-story structure considering various sensor data loss and sensor failure scenarios. The robustness of this estimation method in the presence of measurement noise and modeling uncertainty is also investigated. In addition, the estimation switching method is incorporated into a closed-loop WCS in experiment. The results demonstrate the effectiveness of the proposed state estimation method in mitigating the impact of sensor data loss and sensor failure. Copyright © 2016 John Wiley & Sons, Ltd.

Wireless sensor networks (WSNs) have become an increasingly compelling platform for structural health monitoring (SHM) applications, since they can be installed relatively inexpensively onto existing infrastructure. Existing approaches to SHM in WSNs typically address computing system issues or structural engineering techniques, but not both in conjunction. In this paper, we propose a holistic approach to SHM that integrates a decentralized computing architecture with the damage localization assurance criterion algorithm. In contrast to centralized approaches that require transporting large amounts of sensor data to a base station, our system pushes the execution of portions of the damage localization algorithm onto the sensor nodes, reducing communication costs by an order of magnitude in exchange for moderate additional processing on each sensor. We present a prototype implementation of this system built using the TinyOS operating system running on the Intel Imote2 sensor network platform. Experiments conducted using two different physical structures demonstrate our system's ability to accurately localize structural damage. We also demonstrate that our decentralized approach reduces latency by 64.8% and energy consumption by 69.5% compared to a typical centralized solution, achieving a projected lifetime of 191 days using three standard AAA batteries. Our work demonstrates the advantages of a holistic approach to cyber-physical systems that closely integrates the design of computing systems and physical engineering techniques.

SUMMARY Real-time hybrid structural testing is a novel method that is gaining acceptance for examination of civil engineering structures. This method facilitates testing of an unknown physical component coupled with an analytical model of the remainder of the structure. A primary challenge in performing real-time hybrid testing to accurately reproduce the behavior of the complete system is the appropriate compensation of actuator dynamics. Accounting for the magnitude roll-off while also reducing the time lags to a minimal value is critical to ensure both accuracy and stability of a real-time hybrid structural test. Here, a new compensation scheme is proposed that integrates the best features of two commonly used approaches. The proposed method, simply called integrated compensation, uses online delay estimation to improve on the performance of inverse compensation method for problems in which the effective time delay is not constant over the frequency band of interest. Two real-time experiments are conducted to examine the capabilities of the approach for achieving good displacement tracking. Both experiments focus on the use of a device as the physical component. One experiment uses a linear spring as the physical component, and one uses a controllable, nonlinear damping device. The actuator displacement tracking results are compared with the results using other compensation approaches. The results from these experiments demonstrate that the proposed integrated compensation method is very effective and suitable for real-time hybrid testing using a device as the physical component. Copyright © 2012 John Wiley & Sons, Ltd.

SUMMARY Real-time hybrid simulation (RTHS) has increasingly been recognized as a powerful methodology to evaluate structural components and systems under realistic operating conditions. It is a cost effective approach compared with large scale shake table testing. Furthermore, it can maximally preserve rate dependency and nonlinear characteristics of physically tested (non)structural components. Although conceptually very attractive, challenges do exist that require comprehensive validation before RTHS should be employed to assess complicated physical phenomena. One of the most important issues that governs the stability and accuracy of an RTHS is the ability to achieve synchronization of boundary conditions between the computational and physical substructures. The objective of this study is to propose and validate an H∞ loop shaping design for actuator motion control in RTHS. Controller performance is evaluated in the laboratory using a worst-case substructure proportioning scheme. A modular, one-bay, one-story steel moment resisting frame specimen is tested experimentally. Its deformation is kept within the linear range for ready comparison with the reference closed-form solution. Both system analysis and experimental results show that the proposed H∞ strategy can significantly improve both the stability limit and test accuracy compared with several existing strategies. Another key feature of the proposed strategy is its robust performance in terms of unmodeled dynamics and uncertainties, which inevitably exist in any physical system. This feature is essential to enhance test quality for specimens with nonlinear dynamic behavior, thus ensuring the validity of the proposed approach for more complex RTHS implementations. Copyright © 2012 John Wiley & Sons, Ltd.

Highway sign support structures enhance traffic safety by allowing messages to be delivered to motorists related to directions and warning of hazards ahead, and facilitating the monitoring of traffic speed and flow. These structures are exposed to adverse environmental conditions while in service. Strong wind and vibration accelerate their deterioration. Typical damage to this type of structure includes local fatigue fractures and partial loosening of bolted connections. The occurrence of these types of damage can lead to a failure in large portions of the structure, jeopardizing the safety of passing traffic. Therefore, it is important to have effective damage detection approaches to ensure the integrity of these structures. In this study, an extension of the Angle-between-String-and-Horizon (ASH) flexibility-based approach [32] is applied to locate damage in sign support truss structures at bay level. Ambient excitations (e.g. wind) can be considered as a significant source of vibration in these structures. Considering that ambient excitation is immeasurable, a pseudo ASH flexibility matrix constructed from output-only derived operational deflection shapes is proposed. A damage detection method based on the use of pseudo flexibility matrices is proposed to address several of the challenges posed in real-world applications. Tests are conducted on a 17.5-m long full-scale sign support truss structure to validate the effectiveness of the proposed method. Damage cases associated with loosened bolts and weld failures are considered. These cases are realistic for this type of structure. The results successfully demonstrate the efficacy of the proposed method to locate the two common forms of damage on sign support truss structures instrumented with a few accelerometers.

System identification is becoming more important in structural dynamic applications including structural model update, damage detection primarily due to the rapid increase in the number of damaged or deteriorated engineering structures, and load identification for remaining service life forecasting. Time-domain identification techniques based on measured vibration data, e.g. the least-squares estimation (LSE), have been studied for a relatively long time and shown to be useful. However, the traditional least-squares techniques require that all the external excitation measurements should be available, which may not be the case for many practical applications. In this paper, by introducing a weighted positive definite matrix to the objective function and a learning coefficient using the information in the previous iterations in the identification approach to improve the convergence performance, an alternative iterative approach for both structural parameters and dynamic loading identification, referred to as weighted adaptive iterative least-squares estimation with incomplete measured excitations (WAILSE-IME), was proposed. The accuracy, convergence, and robustness of the proposed approach was demonstrated via numerical simulation on a six-story shear building model with noise-free and different levels of noise-polluted structural dynamic response measurements. The effects of the positive weight matrix, the learning coefficient, and the sampling duration on the convergence and the accuracy of the proposed approach were discussed and the results were compared with available related literature results. Results show that the proposed approach can simultaneously identify structural parameters and unknown excitations within very limited iterations with high accuracy and shows its robustness even noise-polluted dynamic response measurements are utilized. Furthermore, the approach was validated via available experimental measurements for a four-story frame structure excited by impact excitations. The results show that the proposed approach is capable of identifying both structural parameters and the unmeasured excitations with acceptable accuracy and improved convergence.

This study presents a smart system design to enhance the seismic performance of base-isolated buildings using modal LQG control strategies and smart devices, magnetorheological dampers. The advantages of applying the modal LQG approach for base isolation are discussed, including the explicit physical interpretation, simple weighting selection, and easy controller order reduction. 2DOF base isolation systems and the well-known, community-driven, benchmark base isolation problem focusing on structural control are employed to demonstrate the technique as realistic examples. This study analyzes the underlying interaction between structural dynamic properties and control forces that makes the modal approach effective and smart base isolation control possible and shows the seismic performance gain of the benchmark base isolation system offered by the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.

After a disaster strikes an urban area, damage to the fa&ccedil, ades of a building may produce dangerous falling hazards that jeopardize pedestrians and vehicles. Thus, building fa&ccedil, ades must be rapidly inspected to prevent potential loss of life and property damage. Harnessing the capacity to use new vision sensors and associated sensing platforms, such as unmanned aerial vehicles (UAVs) would expedite this process and alleviate spatial and temporal limitations typically associated with human-based inspection in high-rise buildings. In this paper, we have developed an approach to perform rapid and accurate visual inspection of building fa&ccedil, ades using images collected from UAVs. An orthophoto corresponding to any reasonably flat region on the building (e.g., a fa&ccedil, ade or building side) is automatically constructed using a structure-from-motion (SfM) technique, followed by image stitching and blending. Based on the geometric relationship between the collected images and the constructed orthophoto, high-resolution region-of-interest are automatically extracted from the collected images, enabling efficient visual inspection. We successfully demonstrate the capabilities of the technique using an abandoned building of which a fa&ccedil, ade has damaged building components (e.g., window panes or external drainage pipes).

This paper presents the results of a series of experiments conducted to model a magnetorheological damper operated in shear mode. The prototype MR damper consists of two parallel steel plates; a paddle covered with an MR fluid coated foam is placed between the plates. The force is generated when the paddle is in motion and the MR fluid is reached by the magnetic field of the coil in one end of the device. Two approaches were considered in this experiment: a parametric approach based on the Bingham, Bouc-Wen and Hyperbolic Tangent models and a non parametric approach based on a Neural Network model. The accuracy to reproduce the MR damper behavior is compared as well as some aspects related to performance are discussed.

An improved parameter subset selection method based on a dynamic residual force measure is proposed for damage localization. Often the original subset selection using the fundamental modal characteristics requires a single damage location and the use of many smaller model updating processes for detecting multiple damage locations. A new approach to subset selection proposed herein is demonstrated to be efficient for identifying multiple damaged elements. Cases in which damage detection must be achieved using incomplete measurements of the structural responses are also considered. Modal expansion is incorporated to deal with this challenge. An advantage of employing this new approach is that it can reliably identify multiple damage locations. The effect of measurement noise on the performance of the proposed subset selection method has also been investigated. Through a series of illustrative examples considering different types of structures, the proposed method is demonstrated and shown to be very efficient in detecting multiple damage locations. Copyright © 2008 John Wiley & Sons, Ltd.

Recent interest in the use of wireless sensor networks for structural health monitoring (SHM) is mainly due to their low implementation costs and potential to measure the responses of a structure at unprecedented spatial resolution. Approaches capable of detecting damage using distributed processing must be developed in parallel with this technology to significantly reduce the power consumption and communication bandwidth requirements of the sensor platforms. In this investigation, a damage detection system based on a distributed processing approach is proposed and experimentally validated using a wireless sensor network deployed on two laboratory structures. In this distributed approach, on-board processing capabilities of the wireless sensor are exploited to significantly reduce the communication load and power consumption. The Damage Location Assurance Criterion (DLAC) is used for localizing damage. Processing of the raw data is conducted at the sensor level, and a reduced data set is transmitted to the base station for decision-making. The results indicate that this distributed implementation can be used to successfully detect and localize regions of damage in a structure. To further support the experimental results obtained, the capabilities of the proposed system were tested through a series of numerical simulations with an expanded set of damage scenarios.

An analytical comparison between three techniques for the identification of modal properties of structures when subjected to ambient vibrations is performed. The algorithms examined include the eigensystem realization algorithm with data correlations, the prediction error method through least squares, and the stochastic subspace identification (SSI) technique. Both analytical and experimental data from a four-storey building scaled at 1:3 are used to perform these evaluations. The level of noise added to the simulated data is varied to study the robustness of the techniques. All techniques are fully automated, allowing for assessments to be conducted through Monte Carlo simulations. The results indicate that the SSI technique provides the most accurate identification of natural frequencies and mode shapes even with high noise levels, all while requiring the least amount of experience for implementation.

Because a structure’s modal parameters (natural frequencies and mode shapes) are affected by structural damage, finite- element model updating techniques are often applied to locate and quantify structural damage. However, the dynamic behavior of a structure can only be observed in a narrow knowledge space, which usually causes nonuniqueness and ill-posedness in the damage detection problem formulation. Thus, advanced optimization techniques are a necessary tool for solving such a complex inverse problem. Furthermore, a preselection process of the most significant damage parameters is helpful to improve the efficiency of the damage detection procedure. A new approach, which combines a parameter subset selection process with the application of damage functions is proposed herein to accomplish this task. Starting with a simple 1D beam, this paper first demonstrates several essential concepts related to the proposed model updating approach. A more advanced example considering a 2D model is then considered. T...

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

The application of control technologies to structures is expected to enhance a structure's performance in response to natural hazards. This study focuses on the development of control design strategies suitable for smart base isolation systems. The phase I benchmark problem for 3D base-isolated buildings is used as a case study to facilitate a direct comparison with the results of other designs. The smart base isolation system consisting of passive isolators and controllable semiactive devices at the base is employed for the demonstration and validation of these strategies. Magnetorheological (MR) dampers are used as the control devices and are placed in parallel with the isolation system. An H2/LQG control algorithm is used to determine the nominal control action and is used in conjunction with a clipped optimal decision block. Effective design for this complex system requires the use of control device and sensor placement techniques achieved with the consideration of the structure's physical properties. The use of correlation is also proposed to minimize redundancies in the placement of the sensors and devices. Simulation results demonstrate that the control technique is effective in improving the structural performance for a variety of earthquakes. Copyright © 2007 John Wiley & Sons, Ltd.

In this paper, a total strain-based hysteretic material model based on MCFT is proposed for non-linear finite element analysis of reinforced concrete structures. Although many concrete models have been proposed for simulating behavior of structures under cyclic loading conditions, accurate simulations remain challenging due to uncertainties in materials, pitfalls of crude assumptions of existing models, and limited understanding of failure mechanisms. The proposed model is equipped with a fully generalized hysteresis rule and is formulated for 2D plane stress non-linear finite element analysis. The proposed model has been formulated in a tangent stiffness-based finite element scheme so that it can be used for most general finite element analysis packages. Moreover, it eliminates the need to check that tensile stresses can be transmitted across a crack. The tension stiffening model is a function of the bar orientation and any orientation can be accommodated. The proposed model has been verified with a series of experimental results of 2D RC planar panels. This study also demonstrates how parameters of the proposed model associated with cyclic damage modeling influences the pinched cyclic shear behavior.

Results from real time hybrid simulations are compared to full numerical simulations for a hybrid viscous damper, composed of a viscous dashpot in series with an active actuator and a load cell. By controlling the actuator displacement via filtered integral force feedback the damping performance of the hybrid viscous damper is improved, while for pure integral force feedback the damper stroke is instead increased. In the real time hybrid simulations viscous damping is emulated by a bang-bang controlled Magneto-Rheological (MR) damper. The controller activates high-frequency modes and generates drift in the actuator displacement, and only a fraction of the measured damper force can therefore be used as input to the investigated integral force feedback in the real time hybrid simulations.

Hybrid Simulation (HS) and Real Time Hybrid Simulation (RTHS) are recognized as powerful techniques for civil infrastructure assessment. Typically in HS/RTHS, a critical component is isolated as the physical component in the simulation, while the remainder of the structure is modeled numerically. This approach enables response evaluation on both local and global level. Broadening the applications that would like to use HS and RTHS requires that we examine more complex structural systems. When multiple components in the structural system have the same design and contribute roughly equally to the response, it may be difficult to select the most appropriate physical component. However, modeling errors in those structural components that reside in the numerical component can influence the accuracy of the global responses. Model updating based on the responses of the physical component for determining the model parameters will reduce the influence of the modeling errors. Advances in online system identification techniques and their application to more complex structural models, enables the option of incorporating online model updating into HS/RTHS. Through a simplified case study, we explore the feasibility of HS/RTHS with model updating (HSMU/RTHSMU). A two story steel frame equipped with two identical magnetic-rheological (MR) dampers. In RTHS, the first story MR damper is loaded as the physical component and the remainder of the structure, including the frame and the second MR damper, is numerically modeled. Simulation and conventional RTHS response are considered. In each case the second story MR damper model uses one initial parameter set, which is then updated online using identified parameters based on the physical component (RTHSMU). Online model updating is then investigated using a validation signal, and the fidelity and advantages of RTHSMU are discussed.

Editor's Note : This is the second of a two-part Eduquakes series on educational shake tables. In Seismological Research Letters 78(3), Eduquakes provided a brief survey of low-end shake tables and activities; here Shirley Dyke and co-authors describe an ongoing effort to allow wide access (via the Internet) to more sophisticated shake tables. These bench-top tables are capable of matching realistic earthquake ground motion and would enhance any seismology class. For example, students could first calculate the expected waveforms from an earthquake and then test the effects on a model building, thereby providing a system-level “rupture-to-rafters” understanding of earthquakes and their effects. Although developed primarily for earthquake engineering, these tools are potentially useful to a much wider audience. Bench-scale shake tables are an engaging tool for educating students at all levels about the importance of earthquake engineering. Shake tables allow for classroom demonstrations and hands-on experimentation regarding structural response to earthquake ground motions. Demonstrations for K-12 students allow students to gain an understanding of earthquake motions and how structures can be designed or retrofitted to better withstand seismic motions. At more advanced levels, undergraduate and graduate students can conduct experiments to test their knowledge of fundamental concepts. Students may also build or modify scaled structural models to experiment with their own innovations and may also gain experience with modern sensors. While theoretical and analytical discussions are necessary, hands-on experiments are quite effective for demonstrating basic concepts in structural dynamics and earthquake engineering and nicely supplement more traditional educational methods. The University Consortium on Instructional Shake Tables (UCIST) was developed by Shirley Dyke in 1998 to enhance undergraduate and graduate education in earthquake engineering (see http://ucist.cive.wustl.edu/). This consortium, head-quartered at Washington University in St. Louis, was initially a cooperative educational effort among 23 universities associated with the three U.S. national earthquake …

Magnetotheological (MR) dampers have emerged recently as potential devices for vibration mitigation and semi-active control in smart structures and vehicle applications. These devices are highly nonlinear and thus accurate models of these devices are important for effective simulation and control system design. In the current literature, the Bouc–Wen model is coupled with linear elements to describe these MR devices both in simulation and control. In this paper, we propose the friction Dahl model to characterize the dynamics of a shear mode MR damper. This leads to a reinterpretation of the MR damper behavior as a frictional device whose friction parameters change with the voltage. An identification technique for this new model is proposed and tested numerically using an experimentally obtained model. A good match has been observed between the model obtained from experiments and the Dahl based model of the MR device.

This study investigates the use of correlation-based damage detection methods for long-span, cable-stayed bridges. The proposed approach is based on the multiple damage location assurance criterion (MDLAC), which combines a correlation-based technique with a forward-type estimation of damage-sensitive structural parameters. Observing the level of correlation between the variations in the measured and analytically synthesized natural frequencies enables damage localization. The sensitivity matrix, developed from the finite element model, further accommodates multiple damage detection. The locations of damage are determined by iteratively searching for the combination of structural parameters that maximizes the correlation coefficient through the application of genetic algorithms. It is demonstrated that correlation-based modal analysis is successful for damage detection and localization using a numerical model of a full-scale cable-stayed bridge.

An oscillator traversing an elastic continuum, often referred to as the moving-oscillator problem, is representative of many common engineering systems. Due to the dynamic interaction between the two subsystems, deflections may be significantly larger than those generated when such interaction is neglected. Additionally, undesirable vibrations can result in damage due to fatigue. This study focuses on the development of control techniques designed to reduce the dynamic response of the continuum generated by this interaction. A series expansion is used to model the continuum, which, when combined with a single degree of freedom oscillator, results in a time-varying, linear model describing the dynamics of the coupled system. Three different control techniques are considered: passive, active, and semiactive. These techniques are applied and evaluated in terms of their ability to reduce the dynamic response of the continuum and the oscillator. A tracking algorithm, that uses absolute accelerations of both the continuum and the oscillator for feedback, is also used to calculate the optimal control action. A illustrative numerical example is taken from civil engineering, and considers a vehicle crossing a bridge. The results indicate that the response of the system with semiactive control approaches that of an active control, while using significantly less power. Copyright © 2005 John Wiley & Sons, Ltd.