Search

The new Broadway Bridge over the Arkansas River is located in downtown Little Rock, AR, USA. The Arkansas Department of Transportation replaced the existing historical structure, which was costly to maintain and considered structurally deficient. The new iconic structure consists of two basket-handled 134 m tied-arch bridges, which are designed to accommodate 24 000 vehicles daily, and includes a shared-used path. The US$98 million bridge was completed in 2017. Located along the existing alignment in a downtown metropolitan area, impacts to traffic were a prime concern. The bridge was closed to traffic for 6 months to allow for construction and to float the new arches into place. Throughout design, fracture-critical members were given careful consideration. The tie girder was designed with a bolted connection to prevent a fracture in one plate from propagating throughout the cross-section. It was then analysed as a three-sided section at the extreme event limit state. This internal redundancy minimised the potential risk of a catastrophic structural failure. This paper discusses the design considerations for the fracture-critical members, the construction technique and the expected movement of the main-span tied-arch superstructures. [ABSTRACT FROM AUTHOR]

Featured Application: Acceleration based moving force identification is applied for weigh in motion and bridge damage detection purposes. This paper presents a new moving force identification (MFI) algorithm that uses measured accelerations to infer applied vehicle forces on bridges. Previous MFI algorithms use strain or deflection measurements. Statistics of the inferred forces are used in turn as indicators of global bridge damage. The new acceleration-based MFI algorithm (A-MFI) is validated through numerical simulations with a coupled vehicle-bridge dynamic interaction model programmed in MATLAB. A focussed sensitivity study suggests that results are sensitive to the accuracy of the vehicle velocity data. The inferred Gross Vehicle Weight (GVW), calculated by A-MFI, is proposed as the bridge damage indicator. A real weigh-in-motion database is used with a simulation of vehicle/bridge interaction, to validate the concept. Results show that the standard deviation of inferred GVWs has a good correlation with the global bridge damage level. [ABSTRACT FROM AUTHOR]

This paper describes a novel method for detecting bridge damage that uses a partially instrumented vehicle fleet, each vehicle being instrumented with just one accelerometer. Importantly, no prior knowledge of the bridge or individual vehicle properties is required. Firstly, a model simplification concept is proposed to calculate the displacement under the vehicle wheel from single acceleration measurements on a half-car model. Then, optimisation is used to find individual vehicle properties using simulated noisy measurements from a fleet of vehicles. Finally, accelerations from the fleet are used to find the 'apparent profile difference', which contains bridge deflection data. The difference is found to be independent of surface profile but dependent on vehicle axle weight differences and a moving reference influence function (MRIF). When the axle spacings and the relative axle weights are reasonably consistent in a subset of the fleet, the MRIF can be simplified into a compound MRIF. Even when the MRIF and individual axle weights are not available on-site, the shape of the compound MRIF can be determined through an iterative process and used to monitor bridge health condition. Bearing damage is represented in this paper as an increase of rotational resistance of the bearings. The numerical results show that the damage severity and location can be identified. • A new drive-by fleet monitoring concept is introduced using a partially instrumented vehicle fleet without knowing individual vehicle properties. • A new concept, vehicle model simplification, is introduced to enable monitoring bridges using partially instrumented vehicles. • Vehicle wheel displacement is successfully obtained from vehicle accelerations and used in structural health monitoring. • The relation between bridge deflection under the wheel and vehicle load is modelled as a moving reference influence function. This influence function is simplified to monitor bridges. [ABSTRACT FROM AUTHOR]

As road and bridge construction industry becomes more prosperous, the vehicle’s speed and load capacity increase significantly. This paper aims at the problem of vehicle-bridge coupling vibration of highway bridges. In this paper, based on the basic theory of vehicle-bridge coupled vibration, the differential equation of vehicle-bridge coupled system is obtained. The mode decomposition method is adopted to transform the system differential equation into a matrix form. The second-order development function based on the built-in function was written by the principle of Runge-Kutta method, and the second-order time-varying differential equation group was solved. Taking the simply supported beam as an example, this paper studies the dynamic characteristics of bridge and vehicle under different speed and mass. [ABSTRACT FROM AUTHOR]

Summary: Sliding bearings of a bridge are important sliding elements that accommodate the bridge movement caused by temperature action and vehicle/wind load. The sliding life of sliding bearings is determined by the wear of the sliding materials in the bearing. However, the wear of sliding bearings primarily results from a large amount of cumulative sliding displacement experienced by the sliding bearing, even if the movement of the bridge under the vehicle/wind load is far less than the allowable design displacement of the sliding bearing. In general, bearing displacement is monitored using displacement gauges with a low sampling frequency, which cannot accurately capture the relatively high‐frequency displacement component caused by vehicle/wind loads. For predicting the sliding life of sliding bearings, this paper provides a mode rotation angle superposition approach to estimate cumulative sliding displacement. The estimation approach incorporates the combination of the rotation angles of bridge ends and the modal parameters of bridges. The feasibility and advantage of the estimation approach are illustrated by a numerical example; then, the influence factors of the error are analysed. Finally, sliding life prediction of sliding bearings is applied to an actual bridge using the estimation approach of cumulative sliding displacement. [ABSTRACT FROM AUTHOR]

In this paper, a new inequality-based criterion is proposed and investigated for obstacle avoidance of redundant robot manipulators at the joint-acceleration level. By incorporating such a dynamically updated inequality criterion and the joint physical constraints (i.e., joint-angle limits, joint-velocity limits, and joint-acceleration limits), a novel minimum-acceleration-norm (MAN) scheme is presented and investigated for robots' redundancy resolution. In addition, the resultant obstacle-avoidance MAN scheme resolved at the joint-acceleration level is reformulated as a general quadratic program (QP). Moreover, two important “Bridge” theorems are established, which show that such a QP problem can be equivalent to linear variational inequality (LVI) and then to piecewise-linear projection equation (PLPE). An LVI-based numerical method is thus developed and applied for online solution of the QP problem and the inequality-based obstacle-avoidance MAN scheme. Simulative results based on the PA10 robot manipulator in the presence of window-shaped and point obstacles further demonstrate the efficacy and superiority of the proposed acceleration-level inequality-based MAN scheme for obstacle avoidance of redundant robot manipulators. In addition, experimental verification conducted on a practical six-link planar robot manipulator substantiates the effectiveness and physical realizability of the proposed obstacle-avoidance scheme. [ABSTRACT FROM PUBLISHER]

This paper describes Twim, a toolbox written in the MATLAB computer language. Twim is designed for monitoring bridge behaviour during train passages as well as for performing Bridge Weigh-In-Motion of railway traffic, both in real-time and offline. The algorithms calculate the static bogie loads and bogie distances, as well as the speed and acceleration of the train. Twim also includes visualization functions, automatic identification of known locomotives and an auto-calibration that uses locomotives with known bogie loads. The algorithms used place specific requirements on both the bridge type and the instrumentation of the bridge. These requirements are explained in the paper. The instrumentation of several bridges is described, and some of the interesting results gained through this instrumentation are presented. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bridge displacement, particularly due to specific loading events, is increasingly seen as a data signal that potentially contains information useful for bridge management. The lack of a convenient fixed reference location historically made displacement measurement challenging in field conditions, but recent developments in image processing have enabled low-cost, camera-based displacement measurements. Even so, logistical challenges remain. These include organising access to locate the camera, stabilising the camera in windy conditions and managing the large data files that result. Consequently, since accelerometers are widely used, research has continued to investigate recovery of displacement through double integration of acceleration signals. The main challenge with this approach is the errors in the calculated displacement signal due to the low frequency noise. Much of the research to overcome this challenge has involved the use of filters, but results can be highly sensitive to parameter selection and it can be difficult to define the confidence level for the calculated displacement. In this paper, an approach is proposed that does not require the use of filters. The approach, instead, focuses on the quality of hardware used to minimise low frequency noise in acceleration signals, and then implements various quality checks for different bridge and loading scenarios. Sensitivity of the proposed procedure to the choice of start and end points in the acceleration time series data is demonstrated and an approach to overcome this sensitivity has been developed. The robustness of the approach was trialled on three different bridges, subject to three different loading scenarios, that is, a moving truck, a moving train, and pseudo static loading with a truck stopping on a bridge. Where the calculated displacements passed quality checks, they were found to be in good agreement with the directly measured displacements (recorded with Imetrum displacement measurement system). Unsurprisingly, long duration, pseudo-static loading is the most challenging case due to cumulation of low frequency noise effects, where the quality checks correctly identified that the calculated signal would be unreliable. [ABSTRACT FROM AUTHOR]

• The feasibility assessment of drive-by bridge inspection is investigated. • A novel index to quantify the transmissibility performance is proposed. • An induced change is identified through drive-by bridge inspection. • Successful identification of the first three modes of the bridge is verified. This paper presents results of numerical and experimental investigations for the feasibility assessment of drive-by bridge inspection, where the health status of a bridge is solely identified from the dynamic response of an inspection vehicle, passing over a target bridge. To this aim, a novel metric based on the transmission performance between the vehicle and the bridge is proposed, and it is demonstrated that the vehicle having a higher sensitivity index has superior performance, in moving state, to identify bridge frequencies, and consequently separate different states of a bridge from one another. In addition to numerical validation, experimental validation from a laboratory-based experiment is presented, where a two-axle vehicle model is adopted as an inspection vehicle and a single-span steel beam is employed as a target bridge. Vibration data are collected using three highly sensitive accelerometer sensors installed on the vehicle, one at the middle of each axle, i.e., the front axle, and the rear axle, and the third one at the center of gravity of the vehicle, to measure the pitching and bouncing modes of the vehicle. The contributions and the key findings of the work are as follows: First, this paper presents one of the early attempts of experimentally validating the feasibility of drive-by bridge inspection to identify an induced change in the structure of a bridge which has caused less than 2% variation in the fundamental frequency. Second, a novel index for quantifying the performance of transmission between the bridge and the vehicle is proposed. It is verified that a vehicle with a higher sensitivity index captures more bridge-related information, hence making the bridge modal frequencies more identifiable. Third, through experiments, successful identification of the first three vibration modes of the bridge, obtained from the moving vehicle tests, is verified under the condition of constant and slow speed, when there is ongoing excitation on the bridge. Fourth, the indices and criteria presented herein would be helpful in designing a real drive-by inspection system which can be potentially used for drive-by bridge inspection of a network of bridges with similar structural design in practice. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated. [ABSTRACT FROM AUTHOR]

Bridge displacement measurements are important data for assessing the condition of a bridge. Measuring bridge displacement under moving vehicle loads is helpful for rating the load-carrying capacity and evaluating the structural health of a bridge. Displacements are conventionally measured using a linear variable differential transformer (LVDT), which needs stable reference points and thus prohibits the use of this method for measuring displacements for bridges crossing sea channels, large rivers, and highways. This paper proposes a reference-free indirect bridge displacement sensing system using a multichannel sensor board strain and accelerometer with a commercial wireless sensor platform (Xnode). The indirect displacement estimation method is then optimized for measuring the structural displacement. The performance of the developed system was experimentally evaluated on concrete- and steelbox girder bridges. In comparison with the reference LVDT data, the maximum displacement error for the proposed method was 2.17%. The proposed method was successfully applied to the displacement monitoring of a tall bridge (height = 20 m), which was very difficult to monitor using existing systems. [ABSTRACT FROM AUTHOR]

State-space (SS) model is proposed to identify the time lag between the asynchronous accelerations at different locations of the Jiangyin Bridge measured during a ship-bridge collision. One of the accelerations is chosen as the reference signal, and the time axis of the rest of them are shifted relative to that of the reference signal with a series of shifting times. For each pair of reference and time shifted signals, SS models in correspondence to the shifting time series are formulated. Their system matrices are identified with data-driven stochastic subspace identification algorithm, and their model order is determined by Akaike's information theoretic criterion and final prediction error. If the 2 accelerations for model fitting are asynchronous, errors may be introduced into the SS model and its prediction error is expected to be greater than the counterpart obtained with synchronous accelerations. Therefore, the actual time lag between them is identified from the shifting time that corresponds to the minimum of loss function, which is used to map the prediction error vector sequence to a real number. In addition, asynchronous acceleration data measured 2 hr ahead of the ship-bridge collision and synchronous acceleration data measured long after the ship-bridge collision are also analyzed. The former dataset is exploited to evaluate the reproducibility of the SS model for time synchronization, and the latter dataset is utilized to examine its anti-false-identification capability. The results show that the SS model achieves a satisfactory performance in the identification of time lag for both asynchronous and synchronous measurement data. [ABSTRACT FROM AUTHOR]

To address the Dark Silicon problem, architects have increasingly turned to special-purpose hardware accelerators to improve the performance and energy efficiency of common computational kernels, such as encryption and compression. Unfortunately, the latency and overhead required to off-load a computation to an accelerator sometimes outweighs the potential benefits, resulting in a net decrease in performance or energy efficiency. To help architects and programmers reason about these trade-offs, we have developed the LogCA model, a simple performance model for hardware accelerators. LogCA provides a simplified abstraction of a hardware accelerator characterized by five key parameters. We have validated the model against a variety of accelerators, ranging from on-chip cryptographic accelerators in Sun's UltraSparc T2 and Intel's Sandy Bridge to both discrete and integrated GPUs. [ABSTRACT FROM PUBLISHER]

Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck–trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle–bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated. [ABSTRACT FROM AUTHOR]

Dynamic characteristics of the Confederation Bridge were determined from recorded accelerograms of vibrations due to traffic and wind. Natural frequencies of four vertical and five transverse modes of the bridge were identified from the Fourier amplitude spectra of the accelerograms. By appropriate filtering and processing of the accelerograms, displacement time histories of vibrations associated with each of these modes were computed, which were used to determine the mode shapes of the bridge. These characteristics are essential for investigations of the dynamic performance of the bridge. The computed natural frequencies are significantly larger than those of the finite element model used in the design of the bridge. Since the dynamic effects due to traffic, wind, and seismic loads depend on the natural frequencies of the bridge, an evaluation study of these effects is needed using the natural frequencies and mode shapes obtained from measured vibrations.Key words: bridge, acceleration, displacement, record, vibration, filtering, frequency, mode, Fourier spectrum.Les caractéristiques dynamiques du pont de la Confédération ont été déterminées à partir d'enregistrements d'accélérations causées par les vibrations dues à la circulation et au vent. Les fréquences fondamentales de quatre modes verticaux et de cinq modes latéraux du pont ont été identifiées à partir de l'amplitude des spectres de Fourier des accélérations enregistrées. Avec un filtrage et un traitement appropriés des accélérations enregistrées, les historiques de temps des déplacements des vibrations associés à chaque mode ont été calculés, lesquels ont été utilisés afin de déterminer les modes propres du pont. Ces caractéristiques sont essentielles afin d'investiguer les performances dynamiques du pont. Les fréquences fondamentales calculées sont significativement plus grandes que celles du modèle d'éléments finis utilisé pour la conception du pont. Puisque les effets dynamiques causés par la circulation, le vent et les charges sismiques dépendent des fréquences fondamentales du pont, une évaluation de ces effets, utilisant les fréquences fondamentales et les modes propres obtenus à partir de vibrations mesurées, est requise.Mots clés : pont, accélération, déplacement, enregistrement, vibration, filtrage, fréquence, mode, spectre de Fourier.[Traduit par la Rédaction] [ABSTRACT FROM AUTHOR]