Stefan Hurlebaus

Seismic Response Control Using Shape Memory Alloys : A Review

Shape memory alloys (SMAs) are a class of alloys that possess numerous unique characteristics. They offer complete shape recovery after experiencing large strains, energy dissipation through hysteresis of response, excellent resistance to corrosion, high fatigue resistance, and high strength. These features of SMAs, which can be exploited for the use in control of civil structures subjected to seismic events, have attracted the interest of many researchers in structural engineering over the past decades. This article presents an extensive review of seismic applications of SMAs. First, a basic description of two unique effects of SMAs, namely shape memory and superelastic effect, is provided. Then, the mechanical characteristics of the most commonly used SMAs are discussed. Next, the material models proposed to capture the response of SMAs in seismic applications are briefly introduced. Finally, applications of SMAs to buildings and bridges to improve seismic response are thoroughly reviewed.

Model-Based Multi-input, Multi-output Supervisory Semi-active Nonlinear Fuzzy Controller

: The authors recently proposed a new multi-input, single-output (MISO) semi-active fuzzy controller for vibration control of seismically excited small-scale buildings. In this article, the previously proposed MISO control system is advanced to a multi-input, multi-output (MIMO) control system through integration of a set of model-based fuzzy controllers that are formulated in terms of linear matrix inequalities (LMIs) such that the global asymptotical stability is guaranteed and the performance on transient responses is also satisfied. The set of model-based fuzzy controllers is divided into two groups: lower level controllers and a higher level coordinator. The lower level fuzzy controllers are designed using acceleration and drift responses; while velocity information is used for the higher level controller. To demonstrate the effectiveness of the proposed approach, an eight-story building structure employing magnetorheological (MR) dampers is studied. It is demonstrated from comparison of the uncontrolled and semi-active controlled responses that the proposed design framework is effective in vibration reduction of a building structure equipped with MR dampers.

Active and Semi‐active Adaptive Control for Undamaged and Damaged Building Structures Under Seismic Load

: During the lifetime of a structural system, many severe events such as earthquakes and strong winds may impact the system and result in potential damage. To mitigate the structural vibration and damage during these extreme events, control devices such as active and semi-active devices have received considerable attention because of their attractive characteristics. Active control devices are adaptable to any change and semi-active devices have the capability of offering the reliability of passive devices and the versatility and adaptability of active devices. In this research, a direct-adaptive-control method is used to control the behavior of an undamaged and a damaged structure using semi-active and active devices. In the adaptive control method, the controlled system is forced to behave like the model system which exhibits the desired behavior. The model of the adaptive control method is defined in a way to optimize the response of the controlled structure. The controller developed using this method can deal with changes that occur in the characteristics of the structure because it can modify its parameters during the control process. A magnetorheological (MR) damper is used as the semi-active device in this study, whereas a hydraulic actuator is utilized as the active device to control the behavior of the structure. The performance of a three-story building from the SAC project for the third generation of the control benchmark problem is studied by performing time–history analyses. The structure is subjected to different earthquakes and controlled by the direct adaptive control method. In the analysis of the structure, some stiffness reduction is assumed as a result of potential damage in the first story of the building. Also, the direct adaptive control strategy is used to optimize the response of the undamaged structure and to mitigate the damage impact on the performance of the controlled structure in the presence of noise for output measurements. The results of adaptive control method are compared with those of other control strategies. It is shown that the performance of the three-story building is improved using the adaptive control method. By assessing the results of different control approaches, it is found that the adaptive control method works more effectively than other methods and semi-active devices can provide reliable results.

Seismic assessment of bridge structures isolated by a shape memory alloy/rubber-based isolation system

This paper explores the effectiveness of shape memory alloy (SMA)/rubber-based isolation systems for seismic protection of bridges against near-field earthquakes by performing a sensitivity analysis. The isolation system considered in this study consists of a laminated rubber bearing, which provides lateral flexibility while supplying high vertical load-carrying capacity, and an auxiliary device made of multiple loops of SMA wires. The SMA device offers additional energy dissipating and re-centering capability. A three-span continuous bridge is modeled with the SMA/rubber-based (SRB) isolation system. Numerical simulations of the bridge are conducted for various near-field ground motions that are spectrally matched to a target design spectrum. The normalized forward transformation strength, forward transformation displacement and pre-strain level of the SMA device, ambient temperature and the lateral stiffness of the rubber bearings are selected as parameters of the sensitivity study. The variation of the seismic response of the bridge with the considered parameters is assessed. Also, the performance of the SRB isolation system with optimal design parameters is compared with an SMA-based sliding isolation system. The results indicate that the SRB isolation system can successfully reduce the seismic response of highway bridges; however, a smart isolation system that combines sliding bearings together with an SMA device is more efficient than the SRB isolation system.

Robot-Assisted Bridge Inspection

The Center for Robot-Assisted Search and Rescue (CRASAR®) deployed a customized AEOS man-portable unmanned surface vehicle and two commercially available underwater vehicles (the autonomous YSI EcoMapper and the tethered VideoRay) for inspection of the Rollover Pass bridge in the Bolivar peninsula of Texas in the aftermath of Hurricane Ike. A preliminary domain analysis with the vehicles identified key tasks in subsurface bridge inspection (mapping of the debris field and inspecting the bridge footings for scour), control challenges (navigation under loss of GPS, underwater obstacle avoidance, and stable positioning in high currents without GPS), possible improvements to human-robot interaction (having additional display units so that mission specialists can view and operate on imagery independently of the operator control unit, incorporating 2-way audio to allow operator and field personnel to communicate while launching or recovering the vehicle, and increased state sensing for reliability), and discussed the cooperative use of surface, underwater, and aerial vehicles. The article posits seven milestones in the development of a fully functional UMV for bridge inspection: standardize mission payloads, add health monitoring, improve teleoperation through better human-robot interaction, add 3D obstacle avoidance, improve station-keeping, handle large data sets, and support cooperative sensing.

Probabilistic Seismic Demand Models and Fragility Estimates for Reinforced Concrete Highway Bridges with One Single-Column Bent

In performance-based seismic design, general and practical seismic demand models of structures are essential. This paper proposes a general methodology to construct probabilistic demand models for reinforced concrete (RC) highway bridges with one single-column bent. The developed probabilistic models consider the dependence of the seismic demands on the ground motion characteristics and the prevailing uncertainties, including uncertainties in the structural properties, statistical uncertainties, and model errors. Probabilistic models for seismic deformation, shear, and bivariate deformation-shear demands are developed by adding correction terms to deterministic demand models currently used in practice. The correction terms remove the bias and improve the accuracy of the deterministic models, complement the deterministic models with ground motion intensity measures that are critical for determining the seismic demands, and preserve the simplicity of the deterministic models to facilitate the practical application of the proposed probabilistic models. The demand data used for developing the models are obtained from 60 representative configurations of finite-element models of RC bridges with one single-column bent subjected to a large number of representative seismic ground motions. The ground motions include near-field and ordinary records, and the soil amplification due to different soil characteristics is considered. A Bayesian updating approach and an all possible subset model selection are used to assess the unknown model parameters and select the correction terms. Combined with previously developed capacity models, the proposed seismic demand models can be used to estimate the seismic fragility of RC bridges with one single-column bent. Seismic fragility is defined as the conditional probability that the demand quantity of interest attains or exceeds a specified capacity level for given values of the earthquake intensity measures. As an application, the univariate deformation and shear fragilities and the bivariate deformation-shear fragility are assessed for an example bridge.

Localization of notches with Lamb waves.

A time-frequency representation (TFR) is used to analyze the interaction of a multimode and dispersive Lamb wave with a notch, and then serves as the basis for a correlation technique to locate the notch. The experimental procedure uses a laser source and a dual-probe laser interferometer to generate and detect Lamb waves in a notched plate. The high fidelity, broad-bandwidth, point-like and noncontact nature of laser ultrasonics are critical to the success of this study, making it possible to experimentally measure transient Lamb waves without any frequency biases. A specific TFR, the reassigned spectrogram, is used to resolve the dispersion curves of the individual modes of the plate, and then the slowness-frequency representation (SFR) of the plate is calculated from this reassigned spectrogram. By considering the notch to be an additional (second) source, the reflected and transmitted contributions of each Lamb mode are automatically identified using the SFRs. These results are then used to develop a quantitative understanding of the interaction of an incident Lamb wave with a notch, helping to identify mode conversion. Finally, two complementary, automated localization techniques are developed based on this understanding of scattering of Lamb waves.

Summary Review of GPS Technology for Structural Health Monitoring

Over the last two decades, global positioning system (GPS) technology has been developed rapidly and recently applied to civil structures for appropriate monitoring of structural performance. Currently, the GPS technique can only be applied to flexible structures having lower modal frequency ranges, and it still has remaining issues when it comes to obtaining accurate measurements. However, the application of GPS is promising as a monitoring tool because it can measure dynamic characteristics and static displacements in real time, whereas the conventional monitoring system using accelerometers cannot measure static and quasi-static displacements. Furthermore, rapid advancements in GPS devices and algorithms can mitigate erroneous sources of GPS data, and integrated systems using GPS receivers with other supplement sensors are capable of providing accurate measurements. Therefore, GPS technology can provide accurate displacements of structures in real time, and stress and strain conditions of the structures can be computed using finite-element models and numerical analyses. It is also expected that damage localization and severity can be identified using the dynamic characteristics of structures obtained from GPS. This paper summarizes the use of GPS technology for structural health monitoring.

Smart layer for damage diagnostics

In this research damage diagnostics is carried out by a novel design of a smart layer that consists of piezoelectric films. This thin layer is attached to the structure being monitored. First, some fundamental investigations are carried out in order to examine the influence of the thickness of the film, the influence of different adhesives, and the influence of the couplant. The wave field generated by the smart layer propagates into a solid. The directional dependency is investigated. Moreover, an improved type of polyvinylidene fluoride (PVDF) copolymer is presented and investigated for the potential application in the field of structural health monitoring. The use of this PVDF copolymer makes the manufacturing process of a self-sensing actuating layer in ultrasonics much easier than conventional PVDF films since the piezoelectric film is directly sputtered onto the surface of a metallic specimen or onto a metallic layer. This smart layer technique is a valuable tool for identifying the location and size of cracks and delaminations in composites as well as for determining local material thicknesses which might occur due to corrosion. It can be applied in order to monitor the so-called ‘hot spots’ on new structures as well as on already existing structures. The application of the smart layer is demonstrated on a plate-like structure containing a damage. The identified damage corresponds well with the actual damage.

Model-based analysis of dispersion curves using chirplets

Time-frequency representations, like the spectrogram or the scalogram, are widely used to characterize dispersive waves. The resulting energy distributions, however, suffer from the uncertainty principle, which complicates the allocation of energy to individual propagation modes (especially when the dispersion curves of these modes are close to each other in the time-frequency domain). This research applies the chirplet as a tool to analyze dispersive wave signals based on a dispersion model. The chirplet transform, a generalization of both the wavelet and the short-time Fourier transform, enables the extraction of components of a signal with a particular instantaneous frequency and group delay. An adaptive algorithm identifies frequency regions for which quantitative statements can be made about an individual modes energy, and employs chirplets (locally adapted to a dispersion curve model) to extract the (proportional) energy distribution of that single mode from a multimode dispersive wave signal. The effectiveness of this algorithm is demonstrated on a multimode synthetic Lamb wave signal for which the ground-truth energy distribution is known for each mode. Finally, the robustness of this algorithm is demonstrated on real, experimentally measured Lamb wave signals by an adaption of a correlation technique developed in previous research.