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Deflection data provides important information about the mechanical characteristics and structural health condition of bridges. The study presented here pertains to development of a deep learning based approach for structural health monitoring by employing the bridge deflections. The method presented herein uses the long short-term memory (LSTM) framework in detecting the state of damage by tracking the feature changes of time-series deflection and temperature data. Deflection and temperature data of Chongqing Egongyan Rail Transit Suspension Bridge was employed over a period of 15 months to develop the proposed method. The concept of square error index (SE) is introduced as an assessment tool for estimation of the bridge damage level. Results from the present study indicated that the statistical characteristics of SE index are proportional to the level of damage, and are only sensitive to abnormal changes in deflection. Structural health monitoring data over the period of 15 months indicated that the proposed approach has the capability to detect cable damages as low as 0.5%.

Internal cavities in structural elements, such as in concrete-filled steel tubes (CFSTs) of arch ribs reduce confinement, bearing capacity, and the durability of the arch bridges. Formation of internal cavities may be either materials related, which affects proper consolidation, or construction related, especially in terms of proper timing and delivery of concrete slurry to horizontal and inclined structural members. Nondestructive test methods such as ultrasonics have been employed for detection of internal cavities. Despite their success, point-by-point inspection of structural members becomes time-consuming and inefficient, especially when entire structures need to be inspected. Infrared thermography (IR) provides a more reasonable global approach for detection of anomalies. The accuracy and resolution of IR depend on the local ambient conditions affecting convection and external thermal flux prior to detection by IR. The research described herein pertains to the development of a hybrid thermographic approach by using Brillouin fiber optic sensors (BFOSs) for direct detection of thermal convection at the surfaces of steel tubes. Accurate quantitative detection of internal cavity locations and their dimensions required development of a specific machine learning-based approach through which the distributed thermographic data was converted to a series of grayscale images. A Faster Region-based Convolutional Neural Network (Faster R-CNN) based on the improved VGG-16 (IVGG-16) network architecture was utilized for this purpose. The experimental work involved design and fabrication of a distributed temperature sensing sheet (DTSS) for simultaneous transmission of thermal energy into CFST specimens and acquisition of distributed thermographic data by the BFOS. By using the proposed approach, it was possible to detect the embedded internal cavities during the experiments.

An analytical crack-strain transfer model considering interfacial bond-slip between optical fiber and fiber coating is proposed and experimentally validated for crack monitoring of structures. Interfacial shear stress-slip relationship between the optical fiber and fiber coating was determined by using pull-out tests, and a simplified trilinear three-stage interfacial shear stress-slip model was proposed. The model is incorporated into the development of a crack-strain transfer model between the structural substrate and the optical fiber, and the fiber strain distribution is analytically obtained and compared with the strain distribution as perfect bond is assumed between the fiber and fiber coating. Experiments were also conducted to validate the crack-strain transfer model by continuously monitoring corrosion-induced concrete cracking with OFDR distributed optical fiber. Compared with strain transfer models proposed by other researchers in the literature and perfect bond model, the crack-strain transfer model considering interfacial shear stress-slip mechanism between fiber and fiber coating agrees well with experimental results, especially for large crack monitoring.

Accurate micro-crack detections on the whole surface of civil structures have great significance. Distributed optical fiber sensor based on Brillouin optical time-domain analysis technology exhibits great facility to measure strain distributions along the whole surface of structures with a high spatial resolution, thus providing a potential and competitive solution to the detection problem. However, mainly due to low signal-to-noise ratio in measurements, such sensor system is still limited in crack detection–based structural health monitoring applications. How to extract high-quality micro-crack feature representations from the low signal-to-noise ratio–distributed strain measurements is crucial to solve the problem. It has been demonstrated in field of pattern recognition that deep learning can automatically extract high-quality noise-robust feature representations from mass chaos data. Therefore, a micro-crack detection method is proposed herein based on deep learning to analyze the full-scale strain measurements. Each measurement is normalized and segmented into a set of equal-length subsequences. Autoencoders, a typical kind of building block of deep neural network, are stacked layer-wise into a deep network and then exploited to automatically extract feature representations from the subsequences. Each extracted feature representation is labeled as one of the two categories by a Softmax regression. One category originates in the subsequences acquired from structure sections with crack defects and another from sections without any cracks. The micro-crack detections are achieved by solving such a crack/non-crack binary classification problem. A 15-m-long steel I-beam with artifact crack defects is built up in laboratory to verify the proposed method. Experimental results demonstrate that the minimum size of detectable crack opening width reaches to 23 μm, and besides, the proposed method is significantly better than traditional Fisher linear discriminant analysis method and classical support vector machine on the detection accuracy.

Traffic monitoring, including the estimation of axle and gross vehicle weights of passing trucks over bridges plays an important role in the determination of actual service loads. Knowledge of thes...

A method for distributed detection of damage along the lengths of multi-span continuous Bridges is introduced. It is based on monitoring the distributed strains along the length of the bridge by using Brillouin scattering based optical fiber sensors. Identification of damage beyond the signal to noise limits of the instrument is achieved by normalization of the measured distributed strains during multiple positions of a truck with respect to the theoretical influence line of the bridge. Formulation of the method leads to the introduction of a damage index for identification of microcrack locations along the spans of the Bridge. Effectiveness of the proposed method was evaluated by load testing of a five span continuous precast post-tensioned concrete box girder bridge. Locations of detected microcracks by the distributed sensor system were further verified by visual inspections.

First, the temperature effect on the output polarization degree of the fiber Lyot depolarizer was analyzed in this paper theoretically, which shows that when the environment temperature changes from −40℃ to 80℃, the degree of the output light polarization (DOP) of the fiber Lyot depolarizer will increase until about 70℃, then DOP begin to decrease. The further numerical simulations indicate that this result was caused together by thermally induced group birefringence and thermal coefficient of expansion of the polarization fiber. Using our made fiber Lyot depolarizer (DOP≤0.3% when the environment temperature is 20℃), DOP of the fiber Lyot depolarizer was studied at the condition of a variable temperature experimentally, the results are in agreement with the related theoretically results basically, at last, the difference between theoretical and experimental results is discussed, the possible methods to reduce the influence of the temperature on the output DOP of fiber Lyot depolarizer is presented in this paper. It is a good guiding significance to improve the depolarization performance of the fiber Lyot depolarizer in the fields of fiber sensor, fiber gyroscope, fiber Raman amplifier and so on as we believe.

Pipelines provide an economical mode of transportation for hauling gas and liquids such as oil over long distances. Pipeline explosions cause massive loss of lives, and adversely impact both the environment and the economy. Accurate and automated detection of the arrival times of negative pressure waves (NPW) because of leakages is the key parameter in many pipeline leakage detection approaches. The method introduced here uses the absolute maximum difference in the slopes of NPW time-domain signals for accurate determination of the time of signal arrivals at the sensors. The proposed method involves Fiber Bragg Grating (FBG) sensor-based detection of the leakages, and determination of the arrival of NPW signals for accurate detection of the knee-points in the signals. The main advantage in using the proposed approach is determination of exact arrival time of NPW for accurate detection of leakage point locations along the lengths of pipelines. The experimental program includes construction of two separate gas and liquid pipelines for evaluation of the absolute maximum slope difference (AMSD) method. The study includes evaluation of the differences between the proposed method and conventional visual determination of the NPW arrival times, and the actual locations of the leakage sources in the experiments. The numerical approach introduced herein enables direct integration of the proposed method, for automated real-time monitoring of pipeline leakage locations.

Due to the factors such as environment, material aging, and fatigue loads, structural members are prone to crack damage during the service, which could lead to the risk of collapse as the crack-induced strain accumulates. This paper proposes a method for structural crack identification and location based on a distributed optical fiber dynamic strain monitoring method. The Savitzky-Golay smooth filtering method was used to extract the crack information from the obtained dynamic strain signal. Based on the local strain anomaly of the structure and the nonlinear vibration characteristics of the "breathing" crack model, the cracks distributed along the structure can be located. According to the change of harmonic component, the crack development process can be identified, and early identification and localization of structural cracks during operation can be realized, which provides a practical approach of the damage monitoring for the cracked structures.

A distributed fiber optic sensor is developed for condition monitoring of civil infrastructure systems. The fiber optic sensor is especially useful in applications involving underground structures and elements, i.e. concrete pipes, since they can be embedded within the structural elements and operated remotely. The sensor principles are simple and therefore, practical for crack detection and deformation measurement in civil structural applications. Structural monitoring capability of the sensor was evaluated through experiments with reinforced concrete beams, which were repaired by fiber reinforced polymer (FRP) composite materials. The objective was to test the strain reduction capability of the system in applications involving composite structures. The sensor was adhered to the surface of FRP composite, and in the tension zone of the beams. Experimental results are presented and discussed.

Early detection of defects and anomalies is important for safety and efficient management of structural elements. Brillouin scattering–based optical fiber sensors provide distributed sensing capabilities by monitoring the strain and temperature over large distances in structural elements. Their use has been limited to oil and gas explorations, mainly due to the inherent low signal-to-noise ratio in such systems, preventing detection of microcracks in structural monitoring applications. This study introduces a method based on the visual saliency approach through which the digital images acquired by the distributed strain data are employed for the detection of surface microcracks. When using this method, strain data sequences along the entire length of a structural element are sampled with a Brillouin scattering–based optical fiber sensor and then divided into a set of equal-length subsequences. A similarity measure matrix is composed based on the distributed strain data and then converted into a grayscale image. The saliency maps of the acquired grayscale images are calculated and a center-hollowed square template is defined and exploited for convolution with the binarized saliency map as a filter operator. The pixels retained after the filtering correspond to the locations of microcracks. Verification of the method was accomplished by experiments on a 15-m-long steel beam with fabricated defects.

Brillouin scattering based optical fiber sensors provide the opportunity for distributed detection of multiple cracks in structures. Because of capability for making high spatial resolution measurements, pre-pump-pulse Brillouin optical time domain analysis (PPP-BOTDA) systems have been successful in detecting microcracks. Recent studies have shown that when the space between two neighboring microcracks is smaller than the full width at half maximum (FWHM) of the peaks in Brillouin frequency shift (BFS), the strain peaks in BFS interfere, and inhibit detection of multiple microcracks. The focus of the present study is to narrow the size of FWHM by computing the difference in BFS of the strain peaks at two slightly different spatial resolutions. The differential FWHM obtained in this manner is narrower than the original FWHM for single microcrack, as well as two neighboring microcracks. The efficiency of the proposed approach was tested through experiments. The results indicated that it was possible to reduce the FWHM for single cracks, and also to detect the presence of dual microcracks with crack spacing distances smaller than the FWHM. However, the effectiveness of the proposed approach is also dependent on the spatial resolution of measurements, and the signal to noise ratio of the measurement system. While higher spatial resolutions are required for effective narrowing of FWHM in differential approach, the measurement noise at higher spatial resolutions limited the applicability of the method for very small crack opening displacements.

Cable-stayed bridges are structurally efficient and offer cost effective solutions in medium to large-span crossings. The study reported in this article aimed at determining the behavior of a typical cable-stayed bridge when subjected to lateral earthquake excitations. A hybrid analytical–experimental technique is introduced to experimentally simulate the earthquake excitations on the bridge. In this technique, displacement time history of the bridge mid-span was first obtained analytically by exciting the bridge using the earthquake acceleration records. To experimentally simulate the earthquake excitations, these displacements were applied on a $$ \frac{1}{60} $$ scale model of a single plane cable-stayed bridge using a displacement controlled shaker. The efficiency of this technique was evaluated by comparing the experimental versus analytical response in terms of dynamic characteristics and displacement responses of the bridge. The analytical response of the bridge served as a verification tool for validation of key response parameters of the full-scale bridge. These parameters included forces in cables, strains and stresses in the deck, and moments and shear forces acting on pylons in the transverse direction.

The work presented in this article describes development of a machine learning (ML)-based platform for condition assessment of building structures in the aftermath of extreme events. The methods employed in the study include support vector machines, neural networks, and Gaussian Naive Bayes techniques for training of the structural health monitoring model. The ML platform relates the change in stiffness, and strains in various structural components of the system to the intensity and location of damage. Evaluation of the proposed method was accomplished by using it for the characterization of damage in a turn-of-the-century, six-story building with timber frames and masonry walls. The building was damaged due to differential settlement of its foundation. Application of the proposed method in the building required load testing of selected structural elements, and use of the strains acquired from the field tests as input to the ML model.

In this paper, a modified construction for the traditional ϕ -OTDR fiber sensor sensitive for all of distance is presented, the related numerical simulation and experiment analysis results show that this construction can reduce the gain imbalance for all of the distance along the fiber caused by the Rayleigh scattering loss of the fiber and the gain imbalance of Raman fiber amplifier in this fiber sensor system. In order to improve further the vibration sensitivity of this system, the possible methods to restrain the influences of modulation instability effect, Stimulated Brillouin effect, reduce the amplified spontaneous emission (ASE) noises of Raman laser (RL) and Erbium3+-doped fiber amplifiers (EDFA), double Rayleigh backscattering noise in this system are discussed, which will offer a great reference value for the science research and engineering application in the field of fiber sensor as we believe.

Dynamic properties of structures, in terms of frequencies and mode shapes, represent inherent characteristics and health states of structural systems. A method for extraction of modal parameters of structures based on distributed measurements of dynamic strains is described in this article. AT-BOTDA (Amplitude Transfer-Brillouin Optical Time Domain Analysis) optical fiber sensor based on Brillouin scattering is employed for distributed measurements of dynamic strains in a laboratory beam. SSI-DATA (Data-driven Stochastic Subspace Identification) is selected in the formulation of the method, based on its capability for efficient analysis of large amounts of data. The analysis approach involves pre-processing of the distributed data based on basic principles of dynamics, determination of the sensing range, building the strain state space model, extracting modes and improving the results with selection of the sensing points. Laboratory experiments on a beam indicate that distributed vibration strains collected by AT-BOTDA are sufficient for convergence, resulting in an accurate determination of the first two mode shapes.

Morandi’s Polcevera viaduct was an important transportation link that connected port of Genoa to other major cities in Europe. The bridge was in service for over 50 years and carried the traffic over one of the busiest highways in Europe. Real-time structural health monitoring would have provided data for maintenance and warned of impending failure. The objective of the study reported herein was to estimate the remaining service life and predicting the end of life for the bridge in the absence of available sensor data. The analysis involved time-domain estimation of bridge capacity loss over the period of bridge service and increase in demand over the same period. In addition to the existing information about the bridge, combined effects of corrosion and fatigue were considered in estimating the decrease in the capacity of the bridge from the time it was placed in service. Classical influence line analysis of the individual sections of the pylon–deck system of the bridge, together with the finite element model of the bridge, provided the numerical tool for analysis of the bridge. A number of different approaches were compared in estimating the remaining life of the bridge, including the cumulative damage law of Palmgren and Miner, as well as the Goodman, Gerber and Soderberg mean fatigue stress diagrams. The predicted timing of collapse by these models ranged from the year 2014 based on the cumulative damage law, and 2016 by the Gerber and Goodman diagrams. The estimates from this study predict the collapse of the bridge 2–4 years prior to the actual collapse date in 2018. The results of this study indicated that even without an active instrumented structural health monitoring system, basic engineering principles may provide the backing for estimation of remaining life of the infrastructure. In the case of the Morandi bridge, such an analysis at some point during its service life would have possibly predicted imminence of collapse prior to the actual collapse.

Reinforced concrete structural components such as beams are subject during their service life to different loading conditions that may affect their durability and efficiency. This can reduce the safety level of the structure over time until it degrades completely and reaches its ultimate limit state. In particular, cracking conditions due to tensile conditions can be developed leading to the exposure of the steel reinforcements to the aggression of external agents, such as chlorides. Being able to monitor the development and the evolution of cracking is crucial and this research is aimed at this purpose. In particular, laboratory tests have been performed on reinforced concrete beams equipped with distributed fiber optics sensors to monitor the state of cracking. This technology has been selected because its inherent accuracy and low noise. Furthermore, since technology relies of optical signals, the sensors are not affected by electrical and magnetic noise. They are also resistant to high temperatures and chemically reactive environments. The main objectives of the presented first part of this research are focused on the deformation and temperature assessment after concrete pouring, crack detection, localization and opening quantification.

The accuracy of structural models significantly depends on the availability of input design parameters such as the dimensions of resisting elements, material properties, joint connection details, loading conditions, etc. When dealing with old structures, a lot of this information is not accessible, which leads to the introduction of many uncertainties into the model. In the last few decades, several structural health monitoring (SHM) techniques have been used to compensate such lack of data and perform more reliable structural analyses. However, SHM might result in costly and time-consuming surveys that can be as well affected by uncertainties due to environmental effects, measurement noise, and signal processing errors. This paper discusses and introduces a straightforward SHM procedure to collect the fundamental information to achieve a better accuracy and reliability of the finite element model of the considered building. The methodology starts with the acquisition of structural data from available construction drawings and Building Information Modeling (BIM) to create a preliminary finite element model. Then a series of non-destructive tests are performed using thermal camera, sclerometer, pachometer to identify the fundamental structural parameters. In addition, environmental noise measured through accelerometers is used to determine the principal frequencies of the structure. Harmonic excitations are then horizontally applied to resisting elements using a vibrodyne. The proposed methodology was tested on an RC school building located in Melzo (Milan, Italy). Statistical and signal processing techniques are then utilized to interpret the acquired signals and consequently update and calibrate the structural model for the vulnerability assessment. The processed signals revealed substantial differences with the original FE model. Thus, rigidity, mass and damping were modified accordingly.

Manhattan Bridge is a suspension structure that connects Manhattan to Downtown Brooklyn. This bridge is over 110 years old and subjected to daily repeated axles of transit trains and other vehicular traffic. Visual inspections of the bridge revealed manifestation of many cracks in the welded details due to the out-of-plane forces at the connections between transit and floor beams. The research reported herein, pertains to the fatigue life evaluation and reliability assessment of typical cracked welded details. The bridge was instrumented with a real-time structural health monitoring system based on FBG sensors for remote monitoring of the cracked connections. Both deterministic and probabilistic approaches were employed for prediction of the remaining fatigue life of typical cracked details. For the same fatigue reliability index of 2.3, the deterministic and probability based methods yielded remaining fatigue life of 369 and 120 years, respectively, for the typical welded connections details of the bridge.

A method for monitoring the upheaval buckling of subsea buried pipelines by distributed optical fiber sensors is introduced. The proposed method originates from the fact that the bucked pipe has the deterministic patterns of the bending-induced and axial force–induced strains, which can be used to identify the pre- and post-buckling states of the pipe. The challenge for utilizing these features is that the distributed fiber optic sensor can only measure the compound strain created by both bending and axial compression. A monitoring scheme by placing three sensors with [Formula: see text] space around the circumference of the pipeline was proposed in this article. An approach was presented to extract the bending-induced and axial force–induced strains from the longitudinal strains measured by the distributed fiber optic sensors. The experimental programs were then designed to investigate the feasibility of the proposed method. It is demonstrated that the proposed method is possible to detect the occurrence of buckling in the pipe. However, further research is necessary in order to examine the efficiency of the proposed approach under the complex loading patterns at subsea levels.

Rainfall infiltration can be a major cause of slope failure. In the present paper, an indoor soil slope model was built; a distributed sensing fiber was designed based on Brillouin optical time-domain analysis (BOTDA). Two soil moisture probes were planted and a rainfall infiltration test was simulated to acquire the data of slope infiltration and deformation progress under rainfall infiltration. Time domain volumetric moisture content of the slope as well as the vertical and horizontal strain changes were monitored. The moisture content results showed the infiltration path and had obvious ascent at the sliding surface of the slope. The fiber results showed that there existed an apparent strain concentration near the shear section of the slope and strain conversion zone; the soil deformation law had a close spatial relationship with the infiltration path in the soil. In addition to the accurate determination of the sliding surface, a secondary shear surface was also detected by the BOTDA system. These results provide valuable information pertaining to the sliding mechanism and prediction of slope failure.

Development of a method for distributed detection of microcracks on structural elements with very small crack opening displacements is described in this study. Robust principal component analysis (RPCA) and support vector machine (SVM) techniques were employed for denoising and classification of the signals. The objective was to detect microcracks in structural elements less than 30 µm in size. The viability of the method was accomplished by experiments involving a 15-meter steel beam with known microcracks. A distributed optical fiber sensor system based on the Brillouin scattering technology was employed for distributed measurement of strains along the length of the 15-m long beam. Distributed strain signals based on Brillouin based sensors possess inherent system noise and ambient perturbations which in turn reduce the signal-to-noise ratio of the measurements. Therefore, it is not possible to detect the smaller microcracks with small crack opening displacements. Smaller CODs are lost within the noisy distributed strain signal acquired by the Brillouin system. Undetected microcracks result in larger cracks, corrosion, and other anomalies with severe economical and safety ramifications. The method introduced for denoising and enhancement of the signal in the present study enables manifestation of the singularities on the distributed strain data and detection of microcracks. The significant component containing those singularities is effectively separated from the noise component by RPCA-based matrix decomposition. An SVM classifier with Gaussian kernel function was designed, through which the crack detections are realized by singular and nonsingular binary classification. The experimental results demonstrated that it was possible to detect microcracks with CODs as low as 23 µm without errors.

On August fourteen of 2018, a portion of the highway connection viaduct over the Polcevera Valley in Genoa, Italy collapsed, and resulted in forty-three deaths, and many injuries. In the aftermath of the tragic event, in search of answers, a number of studies focused on various scenarios pertaining to the causes of the collapse, i.e. sustained effects of fatigue and corrosion, lack of redundancy, construction abnormalities, and others. In the study reported herein, post collapse analysis of the Morandi’s Polcevera viaduct was conducted by the applied element method (AEM). AEM made it possible for step-by-step evaluation of the structural response of the bridge model to progressive reduction of the strength capacity of single macro-components. In using the proposed approach, it was not necessary to consider the factors that may have resulted in the capacity degradation of the structural elements, such as fatigue and corrosion. Instead, structural degradations were introduced in the model as an incremental area reduction factor until complete section loss was reached. The results of the analyses revealed that the stay cable was the most critical element whose failure would have triggered the collapse. The simulation model further indicated that if sections other than the stay cable had triggered the collapse, such as the main girder, the large visible displacements involved in their collapse, would have warned the authorities of the impending failure. The reproduced mechanism of collapse was further validated with references to the real debris distribution observed from images and a comparison with the available video footage of the bridge collapse, released by the Italian Authorities.

Seismic response of cable-stayed bridges is investigated with the main focus pertaining to the effects of near-field ground motions and soil-structure interaction on the dynamic response of the bridges. A 1/60 scale model of a typical cable-stayed bridge was designed and fabricated for the laboratory investigations. Three different types of ground motion records from the 1999 Chi-Chi earthquake, namely far-field, non-pulse near-field, and pulse-type near-field were employed in the experiments and the numerical analysis of the bridge. Laboratory simulation of the soil-structure interaction was accomplished by a box-spring system with interchangeable springs as foundations for the bridge towers. A three-dimensional numerical model of the bridge was developed, and its response was verified by the experimental results. Results from the numerical and experimental investigations indicated that the effects of foundation soil stiffness on the response of the bridge was influenced by the type of input ground motions. The bridge response was amplified when their foundation was in softer soils.

The out-of-plane seismic behavior of infilled walls has attracted increasing attention in recent years. As a newly-developed infilled wall, the cast-in-situ composite wall with the metal tailing porous concrete (CCWMTPC) possesses better thermal performance than the conventional masonry infilled walls. In this article, the out-of-plane seismic behavior of CCWMTPC is investigated by a series of shaking table tests. The specimen includes a steel frame with two infilled CCWMTPCs. With increase of the peak ground accelerations of four different input excitations, the peak out-of-plane accelerations and peak relative displacements measured at the mid-height and top of the CCWMTPCs exhibited linear response. The CCWMTPCs were not damaged. The experimental results revealed that the CCWMTPCs were still within their elastic state following the input excitations. Subsequently, the specimen was excited harmonically by the sine-waves until some level of damage was observed. A numerical analysis by the finite elements was performed in order to evaluate the experimental results and to compare the behavior of the CCWMTPC with the conventional masonry infilled walls. Results indicated that the out-of-plane performance of CCWMTPC under input excitations is better than their masonry counterparts.

In recent years several studies have been developed on structural collapses of buildings, leaving the bridges’ field partially investigated by few researchers. However, recent events of bridge collapses, namely in Genoa (Italy) on August 14th 2018 and in Kolkata (India) on September 4th 2018, have focused the public interest on the infrastructures’ safety for their consequences in terms of fatalities and injuries, but also of economy and social losses. The present work is focused on the disproportionate collapse of the Morandi’s Bridge in Genoa and consists in an independent study that is based on the available data from literature. The possible triggering events have been deepened starting from the corrosion and the fatigue issue of the steel tendons within the stays. Furthermore, the evolution of the loading conditions in terms of trucks’ number and individual truck weight from the bridge opening (1967) is considered. Therefore, (i) corrosion and fatigue models have been selected from literature and identified through original local weather parameters as temperature, humidity, chlorides, etc. while (ii) statistical historical data of the highway traffic in Italy have been collected. They are useful in the numerical analyses with finite element models of the Morandi’s bridge to identify possible collapse initiations. Some remarks on the role of redundancy in bridges structural scheme as the strategic characteristic to avoid the disproportionate collapse and to improve robustness are provided. Furthermore, the degree of staticindeterminacy of the structure with respect to disproportionate collapse is also discussed.

Monitoring deflections provides a powerful diagnostic tool for structural health monitoring of bridges. Excessive deflections under service loads may be indicative of structural changes, damage and deterioration. For the real time monitoring of deflections under operating traffic loads, it is often difficult to establish a fixed reference point for displacement transducers either because the bridge crosses over a body of water or a roadway. Moreover, vandalism and environmental conditions disrupt and more than likely alter the fixity of the reference points. The work presented in this study pertains to the development of a method for real time remote monitoring of bridge deflections. From the practical point of view, the primary attribute of the proposed method is its capability for making reference free estimates of bridge deflections. The formulations employ the measured rotations and curvatures of the bridge for this purpose. The feasibility of the approach was tested on two different highway bridges. Both bridges were instrumented with a number of different fiber optic sensors that included tiltmeters and strain gauges. Conventional transducers and displacement measurement devices were also used in parallel in order to evaluate the performance of the proposed method. A series of load tests were conducted at both bridge sites that included use of trucks with known weights. In addition, finite element models were developed and employed for further verification of the proposed approach. Field test measurement results and their correlations with the conventional methods as well as comparison with the finite element models are described in this article.

Change in phase or wavelength for interferometric and fiber Bragg Gratings (FBG) based sensors can be described by strain-optic effects. In Brillouin sensors, strain sensitivity need to be expressed in terms of acousto-opto-mechanical properties of fibers. It is then possible to formulate theoretical relationships that lead to the evaluation of strain sensitivities and establishment of gauge factors for Brillouin based sensors. This article reports on the derivation of generalized relationships describing the strain sensitivity in terms of acousto-optic effects in optical fibers. In particular, the formulations correspond to polarization maintaining fibers at various polarization angles with respect to the slow axis of the fiber. The scope of research encompassed theoretical and experimental studies involving both single mode as well as polarization maintaining optical fibers subjected to strain under isothermal conditions. A high resolution BOTDA was employed in the experiments in order to verify the validity of theoretical relationships between strain and Brillouin frequency shifts for different polarization angles.

Firstly, based on the elasto-optical effect of quartz crystal, the formula of the transmissivity for the quartz birefringent optical filter (QBOF) applied with the mechanical-stress is derived and analyzed by numerical simulation, which shows that when the stress is applied on the surface of the quartz crystal vertically or parallel to its optical axis, the phase retardation of the quartz crystal will change accordingly, then the output optical spectrum of QBOF applied with stress is measured by Ultra-6600 spectrophotometer, the related experimental results are agreed with the simulation results very well, which show that when the stress is applied on the surface of the quartz crystal, the central wavelength will shift the longer or shorter wavelength according to the direction and the value of the applied stress. At last, a new type of the stress compensation QBOF is proposed, it can offset the change of phase retardation of the quartz crystal caused by the variation of temperature, which will has a certain application for the stable output of optical filter when the environment temperature changes as we believe.

Monitoring of distributed strains provides important information about the behavior of structural systems. However, detection and quantification of cracks while still at micro size levels w...

A method for structural health monitoring of cable-stayed bridges based on the dynamic distributed sensing of bridge deck strains is introduced in this article. The objective is to detect the location and the magnitude of the cables that have totally or partially lost their tensile load-carrying capacities. Dynamic sensing provides a realistic approach for condition assessment of the bridge under operational conditions. A Brillouin scattering optical time domain analysis (BOTDA) fiber-optic sensor was used to monitor the distributed strain in the deck of a scaled model cable-stayed bridge in the laboratory. The formulations developed in the present study take advantage of the dynamic distributed sensing capability of the BOTDA in amplitude transfer (AT) mode for the establishment of a relationship between the redistribution of deck strains and the tension loss in the individual cables of cable-stayed bridges. The experimental program involved single cable and multicable damage scenarios. The appli...

A reference-free damage detection method based on distributed monitoring of strains in large structural systems is introduced. The method employs the dynamic distributed strain data to formulate its own virtual reference state for detection of defect locations. It uses a single line of optical fiber by way of a dynamic pulse-prepump (amplitude transfer) Brillouin scattering technique in order to acquire dynamic distributed strain data. An experimental program was designed to evaluate the performance of the proposed methodology. The experiments involved dynamic tests of a long beam with simulated defects with small opening displacements ranging between 50 and 550 μm. The implications of this approach are significant since it enables the structure to be monitored at any stage during its service life without the need for prior reference data.

This study describes development of an indirect method for reference-free monitoring of lateral displacements in concrete columns under dynamic loads. The method is independent of the material and section properties of the structure. Therefore, damage due to the change in material and section properties during seismic events does not affect the estimated displacement results. The approach involves discretization of the column elements and placement of strain sensors on opposing sides of the columns for the computation of curvature during the seismic events. Element equivalent force vectors are obtained from the measured strains and subsequently employed for the computation of lateral displacements. Fiber Bragg grating displacement sensors were employed for monitoring the strains. The experimental portion of the research involved shake table tests of a four-span bridge using the recorded ground motions of the 1994 Northridge earthquake. The objective was to verify the accuracy and efficiency of the proposed method by comparing the results with direct displacement measurements. Comparison of the proposed method with the direct measurement of the lateral displacements during the shake table tests indicated reasonable correlation between the computed and direct measurements.

A new approach for monitoring the weight of trucks in motion using the bridge response is introduced in this article. The proposed technique is based on the use of strain rosettes for acquisition of shear strains near bridge supports. Bridge weigh-in-motion monitoring using shear force is a new approach that differs from the prevailing techniques based on the measurement of flexural strains. Formulations are introduced using the shear force response of the bridge in the computation of gross vehicle weights. The method requires truck speeds, influence lines, and shear force responses for the computation of gross vehicle weight. All these are acquired by two sets of rosette sensors attached in series on the webs of bridge girders. An experimental program was designed to evaluate the response of the proposed approach in real-time monitoring of moving truck weights. This was accomplished by instrumentation and load testing of a two-span prestressed concrete box girder bridge by a calibrated truck. Field test results are presented and compared with the actual weight of the calibrated truck.

Development of a model for the analysis of strain transfer mechanism in Brillouin-based sensors with strain singularities is provided in this study. The main objective of the research pertained to the development of a method for accurate detection of cracks and their locations in sensing with Brillouin-based fiber optic distributed sensors. The work involved formulation of a shear lag–based model considering the elastic as well as elastoplastic stages of the fiber optic coating strains. Feasibility of the proposed approach is evaluated through an experimental program. The experimental program involved use of a Brillouin optical time domain reflectometer (BOTDR) for distributed measurement of strain and detection of simulated cracks in a 15-m-long beam. The results indicate that the discontinuities in the strain distribution based on the theoretical analysis provide the means to accurately pinpoint the location of simulated cracks. On the other hand, the distortion effect of the BOTDR system due to...

Structural damping is an important parameter in system identification and assessment of structural systems. Due to its variable nature, especially in highway bridges, precise estimation of damping poses challenges both from the computational point of views as well as complexity of operations. Survey of technical literature indicates that several methodologies have been developed over the past few decades for the determination of structural damping parameters. The present study determines damping in an operational highway bridge using two approaches, namely, the decay of motion direct measurement and the natural excitation technique. A two-span concrete box girder bridge was instrumented with various types of fiber optic Bragg grating sensors. Series of live load tests were performed on the bridge using a calibrated truck. Estimated damping was implanted in a detailed finite element model of the bridge. Live load on the actual bridge was replicated on the finite element model and the calculated results correlated with measured data at site.

Development of a simplified approach for monitoring the cables of cable-stayed bridges is described in this article. The method introduced in this paper uses the distributed measurement of strains along the bridge deck to detect the cables that have totally or partially lost their tensile force. The fundamental principle employed in formulating the method is the interrelationship between the individual cable forces and the bending moment along the bridge span. The proposed method was evaluated through an experimental program that involved fabrication and testing of a reduced scale model of a single plane cable-stayed bridge. Distributed strain along the span length was monitored by a Brillouin Optical (Neubrex, Hyogo, Japan) Time Domain Analysis fiber optic sensor system. Strain gauges, Fiber Bragg Grating sensors (Technica Optical Component, LLC, Beijing, China), and a finite element model of the bridge were employed for evaluating the efficiency of the proposed method. Several different damage c...

Distributed sensing offers great promise in structural health monitoring of bridges and other types of critical structures. Over the years, a number of different Brillouin scattering–based systems have been developed for distributed sensing, including sensors based on the Brillouin optical time domain reflectometer. This study pertains to the quantitative characterization of Brillouin optical time domain reflectometer–based sensors for monitoring of distributed strains and detection of defects. This study involved experiments involving a 15-m-long beam and simulated defects. In the experiments, the effect of strain localization at the defect sites was masked by the low spatial resolution of the Brillouin optical time domain reflectometer. The Brillouin optical time domain reflectometer–measured response was evaluated by numerical modeling of the beam. Computation of the flexural strains involved a hybrid approach in which the experimentally determined degraded stiffnesses of the defect zones were employed...

Scour is the major cause for many bridge failures and damage to piers and abutments. Scour is not easily discernible because it is hidden under the channel flow. Over the years, a number of sensors have been developed for detection of scour depth. Development, testing, and field implementation of a new and simple type of scour sensor is described in this paper. The scour depth detection concept is based on measuring the fundamental frequency of vibration of a rod embedded in the riverbed. The sensor uses a single fiber-optic Bragg grating (FBG) sensor for transduction of the vibration frequency. The inverse relationship between the fundamental frequency and the length of the sensor rod is used for detection of the scour depth. A computational approach is developed based on the Winkler spring reaction soil model for automated calibration of the scour sensor during installation in the riverbed. The scope of the research included development of the theoretical basis for the sensor, establishment of the computational methodology for detection of the riverbed foundation properties, proof-of-concept laboratory tests, small-scale field verification tests, and installation and remote monitoring of scour in a multispan scour critical bridge in Illinois. The results include laboratory test data from the measurements in soil, simulated scour tests in a hydraulic flume, and real-time data from remote monitoring of scour at the bridge site.