Measured Bridge Response Research Articles

Vehicle-Bridge Interaction Modelling Using Precise 3D Road Surface Analysis.

Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM.

Genuine Influence Line and Influence Surface Identification from Measured Bridge Response Considering Vehicular Wheel Loads

A bridge influence line (BIL) and a bridge influence surface (BIS) reflect the relationship between the bridge responses and the loads on the bridge and have been commonly used in techniques such as bridge damage detection, bridge safety evaluation, bridge model correction, bridge weigh-in-motion, and so on. Conventionally, a BIL can be extracted from the bridge response under a moving vehicle with known axle loads, while a BIS can then be obtained by lateral interpolation from BILs obtained for key transverse positions. However, in the traditional BIL-extracting methods, the transverse distance between the coaxial wheels was not considered; that is, the coaxial left and right wheel loads are simply treated as one concentrated load (usually referred to as the axle load). Therefore, the obtained BIL is the bridge response under two loads rather than one. Hence, errors may be introduced to the obtained BILs and propagated to the interpolated BIS. Moreover, the potentially significant effect of the unbalance of coaxial wheel loads on BIL identification is ignored. In this research, a new method for determining a genuine BIL and BIS is proposed. The wheel load rather than the axle load was taken into calculation in this method, where the effect of the transverse distance between the coaxial wheels and the unbalance of the coaxial wheel loads was naturally taken into consideration. Laboratory experiments and numerical simulations were performed to verify the effectiveness of the proposed method. Furthermore, a comprehensive parametric analysis was conducted to investigate the effects of some important parameters such as vehicle velocity, lateral deviation of the center of gravity of vehicles, axle count, and road surface condition on the identification performance. The results show that the BIL and BIS can be identified with satisfactory accuracy.

Data-driven analytical load rating method of bridges using integrated bridge structural response and weigh-in-motion truck data

Load rating is a widely used approach for evaluating the load-carrying capacity of bridges in an effort to ensure safe bridge operation under expected traffic loads. Load rating often relies on simplified analytical models including empirically derived model parameters that do not reflect bridge-specific information resulting in conservative ratings. To reduce this conservatism, this study proposes a novel data-driven framework that utilizes long-term bridge response data to extract bridge-specific model parameters that can be used within in the Load and Resistance Factor Rating (LRFR) process. The data-driven LRFR (DD-LRFR) framework is empowered by a cyber-physical system (CPS) architecture that uses Internet connectivity to integrate measured bridge responses with truck weights measured by a weigh-in-motion (WIM) station. The CPS architecture uses computer vision of camera images to confirm trucks observed at a WIM station are identical to those observed at a bridge. Bridge response and axle weight data are then used to extract probabilistic models of dynamic load allowances and unit influence lines. The DD-LRFR method is validated using a 20-mile (32.2-km) segment of the I-275 northbound highway in Michigan that is monitored continuously by the CPS architecture. Six girders associated with two bridges along I-275 are rated using the proposed DD-LRFR methodology with rating factors compared to those obtained using conventional and refined load rating methods. The DD-LRFR method yields inventory- and operational-level rating factors that are less conservative than those from the approximate LRFR method and comparable to those using finite element modeling of the bridge.

Evaluation of bridge support condition using bridge responses

This article presents a method for evaluating the support condition of bridges. This is done by representing the aging and deteriorated supports as rotation springs with equivalent spring constants. Sensitivity analysis was performed to obtain a relationship between the spring constant and the bridge responses (deflections/slopes). From this relationship, measured bridge responses can be used to estimate the equivalent spring constants through interpolation. Numerical analysis was performed to check whether the method can be used to calculate equivalent spring constants. Then, the method was verified by performing laboratory tests on a scale model bridge and field test on an actual bridge. In both tests, spring constants were estimated using the proposed method and then verified by calculating the displacements and frequencies and comparing them to the measured values.

Nonlinear FE model updating and reconstruction of the response of an instrumented seismic isolated bridge to the 2010 Maule Chile earthquake

SummaryNonlinear finite element (FE) modeling has been widely used to investigate the effects of seismic isolation on the response of bridges to earthquakes. However, most FE models of seismic isolated bridges (SIB) have used seismic isolator models calibrated from component test data, while the prediction accuracy of nonlinear FE models of SIB is rarely addressed by using data recorded from instrumented bridges. In this paper, the accuracy of a state‐of‐the‐art FE model is studied through nonlinear FE model updating (FEMU) of an existing instrumented SIB, the Marga‐Marga Bridge located in Viña del Mar, Chile. The seismic isolator models are updated in 2 phases: component‐wise and system‐wise FEMU. The isolator model parameters obtained from 23 isolator component tests show large scatter, and poor goodness of fit of the FE‐predicted bridge response to the 2010 Mw 8.8 Maule, Chile Earthquake is obtained when most of those parameter sets are used for the isolator elements of the bridge model. In contrast, good agreement is obtained between the FE‐predicted and measured bridge response when the isolator model parameters are calibrated using the bridge response data recorded during the mega‐earthquake. Nonlinear FEMU is conducted by solving single‐ and multiobjective optimization problems using high‐throughput cloud computing. The updated FE model is then used to reconstruct response quantities not recorded during the earthquake, gaining more insight into the effects of seismic isolation on the response of the bridge during the strong earthquake.

Estimation of gross weight, suspension stiffness and damping of a loaded truck from bridge measurements

Particle filter method (PFM) based on Bayesian inference gives a reliable estimate of hidden parameters from the noisy measured signal. A new method of vehicle parameter identification based on measured bridge response has been proposed using PFM. An uncoupled iterative technique is utilised for solving bridge vehicle interaction problem which has been used as a forward solution of the PFM. A field test under moving truck has been conducted on an existing pre-stressed concrete bridge to collect response data at different locations. Based on the extracted bridge natural frequencies and measured peak acceleration responses at five sensor locations, finite element model of the tested bridge has been updated using response surface-based model updating technique. In addition to estimation of test truck parameters using measured bridge response, dynamic wheel load induced in the bridge has been determined. Excellent agreement has been found between the measured and reconstructed bridge response using estimated parameters.

Nonsmooth dynamics prediction of measured bridge response involving deck‐abutment pounding

SummaryEarthquake‐induced deck‐abutment contact alters the boundary conditions at the deck level and might activate a different mechanical system than the one assumed during the design of the bridge. Occasionally this discrepancy between the assumed and the actual seismic behavior has detrimental consequences, for example, pier damage, deck unseating, or even collapse. Recently, an insightful shake‐table testing of a scaled deck‐abutment bridge model , showed unexpected in‐plane rotations even though the deck was straight. These contact‐induced rotations produced significant residual displacements and damage to the piers and the bents. The present paper utilizes that experimental data to examine the validity and the limitations of a proposed nonsmooth dynamic analysis framework. The results show that the proposed approach satisfactorily captures the planar rigid‐body dynamics of the deck which is characterized by deck‐abutment contact. The analysis brings forward the role of friction on the physical mechanism behind the rotation of the deck, and underlines the importance of considering the frictional contact forces during deck‐abutment interaction even for straight bridges, which typically are neglected. Finally, the paper investigates the sensitivity of the rotation with respect to macroscopic contact parameters (i.e., the coefficient of friction and the coefficient of restitution). Copyright © 2017 John Wiley & Sons, Ltd.

Nonlinear FE model updating of seismic isolated bridge instrumented during the 2010 Mw 8.8 Maule-Chile Earthquake

In this paper, nonlinear finite element model updating (FEMU) is performed to study the prediction accuracy of a state-of-the-art finite element (FE) model of a seismic isolated bridge (SIB). The seismic isolator model parameters are updated in two phases: using component-wise and system-wise FEMU. The isolator model parameter values estimated from 23 isolator component tests show a large scatter, and a poor goodness-of-fit (GOF) of the bridge response to the 2010 Maule Earthquake is obtained when most of those parameter sets are used for the isolator elements of the bridge FE model. In contrast, good agreement between the FE predicted and measured bridge response is obtained when the isolator model parameters are calibrated using the bridge response data recorded during the 2010 Mw 8.8 Maule, Chile Earthquake. The updated FE model is then used to reconstruct response quantities not recorded to gain more insight into the effects of seismic isolation during a strong earthquake.

Multiple support seismic excitation of the Evripos bridge based on free-field and on-structure recordings

The 395 m long Evripos bridge in central Greece connects the island of Evia to the mainland. An accelerometer array of 43 triaxial sensors has been monitoring both the free-field excitation and the response of the superstructure in a series of seismic events since 1994. This paper focuses on the characteristics of the spatially variable earthquake ground motions (SVEGMs) recorded during two seismic events (1999 and 2013) and the corresponding bridge response. A model updating is performed to match the numerically predicted with the measured bridge response. Then, the nature of the recorded ground motions is studied and the incoherency patterns of the seismic waves are compared with empirical or semi-empirical models. It is observed that the loss of coherency at the site is isotropic. It is also documented, for the first time based on actual free-field and on-structure recordings, that the asynchronous excitation of a bridge excited higher modes of vibration while suppressing the oscillation on its fundamental frequency. The latter is in line with analytical predictions and is believed to be a key finding in understanding the nature of SVEGM and predicting its potential impact on the seismic response of bridges.

Field-calibrated influence lines for improved axle weight identification with a bridge weigh-in-motion system

Bridge weigh-in-motion (BWIM) systems take influence line (IL) as a reference to calculate axle weights. The calibrated ILs based on field measurements can acquire better conformity with the actual situation and more actually represent the characteristic of existing bridges. Following the methodology proposed by O'Brien et al. (2006), this paper presents back-calculating of the ILs from direct measurements taken on field tests for identification of axle weights of heavy vehicles. The algorithm for calibrating ILs is based on continuously measured bridge responses (strains) produced by two calibration vehicles passing across the instrumented bridge. In terms of the calibrated ILs, Moses' algorithm was applied to identify axle weights of moving vehicles by the least-square method. Field tests on highway US-78 in Alabama were conducted as a case study to evaluate the accuracy of the presented algorithms in calibrating ILs and to identify the axle weights by comparing with the static measurements, and with the measurements by the bending-plate weigh-in-motion (WIM) system on a one-to-one basis to demonstrate the accuracy of BWIM system relative to conventional pavement WIM systems. Finally, factors influencing axle weight identification, including the selection of ILs, the shapes of ILs and the scan numbers for collecting strain signals, were discussed.

Adaptive adhesion by a beetle: Manipulation of liquid bridges and their breaking limits

A drop brought into contact with a nearby substrate can wet and spread against the substrate, forming a liquid bridge that exerts a capillary force. This force due to surface tension can be used to "grab" the substrate, pulling it toward the drop. "Wet" adhesion results from the parallel action of an array of small liquid bridges. The Florida palm beetle, Hemisphaerota cyanea, uses wet adhesion to defend itself against attacking predators by adhering to the palm leaf using an array of about 120,000 μm-sized liquid bridges. The beetle's survival depends on the strength of adhesion which, in turn, depends on how liquid bridges break. Individual bridges break when they go unstable, according to their response curves. However, the ultimate strength of an individual bridge depends on the class of disturbances to which it is subjected, and it has been speculated that the beetle may have some control over this class. The authors experimentally study families of liquid bridge equilibria for their breaking limits when subjected to constant-length (L) and constant-force (F) disturbances. While to control constant-L disturbances is straightforward, to apply and control constant-F disturbances on a liquid bridge requires more ingenuity. The authors introduce an apparatus with a lever-arm and a ball-bearing slide. The authors then compare our experimentally measured bridge response curves to the force trace from experiments on the beetle (prior literature) to infer the mode of beetle detachment. Under normal loads, the beetle detaches as a constant-L instability for smaller loads and as a constant-F instability for larger loads. The beetle's ability to adjust the type and magnitude of loading in real time is not only crucial to its survival but has implications for the design of various engineering devices.

Strain-Based Evaluation of a Steel Through-Girder Railroad Bridge

In the state of New Mexico (USA), passenger rail began in 2008 between Belen and Santa Fe on the Rail Runner, following the acquisition of about 100 miles of existing rail and related infrastructure. Many of the bridges on this route are over 100 years old and contain fatigue prone details. This study focuses on a steel through-girder bridge along this corridor. To accurately evaluate these structures for load carrying capacity and fatigue, an accurate analytical model is required. Accordingly, four models were developed to study the sensitivity of a bridge in New Mexico to floor-system connection fixity and the ballast. A diagnostic load test was also performed to evaluate the accuracy of the finite-element models at locations of maximum moments. Comparisons between the simulated and measured bridge response were made based on strain profiles, peak strains, and Palmgren-Miner’s sums. It was found that the models including the ballast were most accurate. In most cases, the pinned ended models were closer to the measured strains. The floor beams and girders were relatively insensitive to the ballast and end conditions of the floor-system members, whereas the stringers were sensitive to the modeling of the ballast.

Effect of Computational Patterns of PCA on Moving Force Identification

Effect of computational patterns of principle component analysis (PCA) on moving force identification (MFI) is studied in this paper. The motion equation of bridge due to moving vehicles are formed, the relationship between moving axle loads and caused bridge responses are established for the PCA-based MFI method in time domain. The measured bridge responses are rearranged in a matrix form for easily performing PCA and are adopted for obtaining an acceptable solution to the MFI problem. A laboratory experimental study was conducted to assess effectiveness and robustness of the PCA-based MFI method. The illustrated results show that the PCA-based method is an easy executive and more effective method for the MFI problem. The PCA computational patterns should be appropriately considered due to its higher sensitivity on response catalogues.

Identification of Dynamic Vehicular Axle Loads: Theory and Simulations

This paper presents a new method of identifying dynamic vehicular axle loads by directly using bridge measurements. To demonstrate how the proposed methodology works out, vehicle-bridge coupling equations are first established for numerical simulations. The developed vehicle-bridge coupled system contains only the modal properties of the bridge and the physical parameters of the vehicle. Using the superposition principle and influence surface concept, the dynamic interaction forces (i.e. the dynamic axle loads) can then be identified from the measured bridge responses. A series of simulations are carried out in which the effects of various factors such as bridge inertia force, measurement station, vehicle speed, traveling route, number of vehicles, road surface condition, and noise level have been investigated. The identified results show that the proposed method is able to identify dynamic axle loads with good accuracy, which can serve as a basis for dynamic bridge-weigh-in-motion. This paper also serves as a theoretical base for the companion paper in which the proposed method is applied to identify the dynamic axle loads of a real truck on an existing bridge.

Multiple vehicle axle load identification from continuous bridge bending moment response

The identification of multiple vehicle dynamic axle loads on multi-span continuous bridge is presented. The objective of the present study was to develop a practical technique to determine dynamic axle loads of multiple vehicles based on the measured bridge response. Based on the inverse problem of turning bridge responses into time-varying point loads, the solution can be determined using least squares regularization optimization. The updated static component (USC) technique is adopted to improve the accuracy and eliminate the difficulty of an optimal regularization selection. The computer simulation and experimental studies were conducted to investigate the effectiveness of the proposed method. A scaled model of a three-span, continuous bridge and two scaled 2-axle vehicles were designed, constructed and fabricated in the laboratory. Various moving schemes of multiple vehicle travel including following, overtaking and side-by-side movements were considered. The actual dynamic axle loads of the model vehicles during the travel were directly monitored and used in accuracy evaluation. From the obtained results, it is observed that the USC technique effectively improved the accuracy and robustness of the problem, particularly in correction of the absence of identified axle loads around the internal bridge supports. The method is robust and accurately identifies every dynamic axle load for all moving schemes of vehicles. No conflict of the identified axle loads during axle overlapping and passing the bridge support is observed because the axle loads are identified independently and controlled by static influence lines from the USC algorithm. The comparison between the measured and reconstructed bending moments indicates that the approach is correct. The accuracy of identified dynamic axle loads for all cases of study is within a relative percentage error of 13%.

Long-term Structural Health Monitoring System for a FRP Composite Highway Bridge Structure

This article discusses the implementation of a long-term structural health monitoring system for a FRP highway bridge using vibration-based monitoring techniques. The design and installation of such a system is prompted by the need to present a quantitative assessment of structural response to owners and operators in order to provide early warnings for major changes in response in the case of impending catastrophic failures. The bridge under discussion is instrumented with accelerometers as well as corresponding data acquisition and transmission equipment for automatic data collection. Ambient vibration based techniques are used to extract modal parameters from measured bridge response. Information regarding the change of internal structural characteristics is then obtained through a mode shape curvature based approach. Structural stiffness change is based on the analysis of collected data. A finite element model updating technique is used to provide an improved baseline model. The updated model is then used for simulation of damage effects.

Reaction Distribution in Highly Skewed Continuous Steel Girder Bridge

A field live load test and a finite element method (FEM) analysis performed on an existing 60° skew, three-span continuous steel girder bridge are presented. The live load testing program with nonstandard truck load was carried out to allow for assessing the adequacy of existing structures and pier support to carry an HS25 standard load. In particular, it was of interest to evaluate the effect of bridge skew on the distribution of reaction forces at interior piers. The measured bridge response under the live load was used to develop and calibrate a FEM model by using the ANSYS computer program. The calibrated FEM model was then used to predict bridge response under an HS25 load. For all load cases investigated, the FEM results showed that distribution of vertical reaction forces on the interior piers was nonuniform. The analysis results indicated that higher reaction forces were experienced by piers on the side of the bridge closer to the obtuse corner than on the side near the acute corner. The importance of using actual field measured test data to develop and calibrate a realistic FEM model is demonstrated.

Moving force identification based on the frequency–time domain method

This paper addresses the problem on the identification of moving vehicle axle loads based on measured bridge responses using a frequency–time domain method. The focus is on the evaluation of two solutions to the overdetermined set of equations established as part of the identification method. The two solutions are (i) direct calculation of the pseudo-inverse and (ii) calculation of the pseudo-inverse via the singular value decomposition (SVD) technique. For this purpose, a bridge–vehicle system model was fabricated in the laboratory and the bending moment responses of bridge model were measured as a two-axle vehicle model moved across the bridge deck. The moving axle loads are then calculated from the measured responses via the two solutions to the over-determined set of equations. The effects of changes in the bridge–vehicle system, measurement and algorithm parameters on the two solutions are evaluated. Case studies show that the moving force identification is more feasible and its accuracy acceptable with the use of the SVD technique. This technique can effectively enhance the identification method and improve the identification accuracy over that of the direct pseudo-inverse solution.