Identification of damping in a bridge using a moving instrumented vehicle

In recent years, there has been a significant increase in the number of bridges which are being instrumented and monitored on an ongoing basis. This is in part due to the introduction of bridge management systems designed to provide a high level of protection to the public and early warning if the bridge becomes unsafe. This paper investigates a novel alternative; a low-cost method consisting of the use of a vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the damping ratio of the bridge. The method is tested for a range of bridge spans and vehicle velocities using theoretical simulations and the influences of road roughness, initial vibratory condition of the vehicle, signal noise, modelling errors and frequency matching on the accuracy of the results are investigated

Virtual structural health monitoring and remaining life prediction of steel bridges

In this study a Structural Health Monitoring (SHM) system is combined with Bridge Weigh-in-Motion (B-WIM) measurements of the actual traffic loading on a bridge to carry out a fatigue damage calculation. The SHM system uses the 'Virtual Monitoring' concept, where all parts of the bridge that are not monitored directly using sensors, are 'virtually' monitored using the load information and a calibrated Finite Element (FE) model of the bridge. Besides providing the actual traffic loading on the bridge, the measurements are used to calibrate the SHM system and to update the FE model of the bridge. The newly developed Virtual Monitoring concept then uses the calibrated FE model of the bridge to calculate stress ranges and hence to monitor fatigue at locations on the bridge not directly monitored. The combination of a validated numerical model of the bridge with the actual site-specific traffic loading allows a more accurate prediction of the cumulative fatigue damage at the time of measurement and facilitates studies on the implications of traffic growth. In order to test the accuracy of the Virtual Monitoring system, a steel bridge with a cable-stayed span in the Netherlands was used for testing

A drive-by inspection system via vehicle moving force identification

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.European Commission - Seventh Framework Programme (FP7

The influence of pre-existing vibrations on the dynamic response of medium span bridges

Critical static bridge loading scenarios are often expressed in terms of the number of vehicles that are present on the bridge at the time of occurrence of maximum lifetime load effect. For example, 1-truck, 2-truck, 3-truck or 4-truck events usually govern the critical static loading cases in short and medium span bridges. However, the dynamic increment of load effect associated with these maximum static events may be assessed inaccurately if it is calculated in isolation of the rest of the traffic flow. In other words, a heavy vehicle preceding a critical loading case causes the bridge initial conditions of displacement and acceleration to be non zero when the critical combination of traffic arrives on the bridge. Failure to consider these pre-existing vibrations will result in inaccurate estimation of dynamic amplification. This paper explores these dynamic effects and, using statistical analyses outlines the relative importance of pre-existing vibrations in the assessment of total traffic load effects.Irish Research Council for Science, Engineering and TechnologyOther funderIRCSETThe European 6th Framework Project ARCHES (Assessment and Rehabilitation of Central European Highway Structures)ti, ke - AS 04/11/201

The sensitivity of bridge safety to spatial correlation of load and resistance

Random Field theory has emerged in recent years to model the statistical correlation of resistance in concrete structures and to determine its influence on the probability of structural failure. A major shortcoming in the work carried out to date is the spatial variability and corresponding correlation associated with applied traffic loads. In this paper the influence of spatial correlation of both traffic load and resistance is considered in the context of bridge safety assessment. The current study, explores, the nature of the problem by three theoretical examples. As a general trend, examples show that while traffic loads are weakly correlated, load effects are strongly correlated as the same heavy vehicle often causes extremes of load effect in different parts of the bridge which is due to the transverse sharing of load (measured here using a load sharing factor). It is found that the strength of correlation of load effect depends greatly on the load sharing factor which is treated in a simple way in many studies. In a more sophisticated beam-and-slab bridge example, load sharing factors are derived from a finite element analysis to assess transverse load sharing, and are shown to vary by girder number, girder segment and by load location. Despite the fact that load effect at points along the length of a bridge is strongly correlated, the combined influence of correlation in load and resistance on probability of failure is small. © 2015 Elsevier B.V

Numerical integration approach to the problem of simulating damage in an asphalt pavement

A road develops permanent deformation or fatigue damage because of the stress and strain induced in its structure by surface loading and environmental change. Dynamic tyre forces generated by the vibration of moving heavy vehicles excited by the road surface profile are strongly influenced by vehicle speed and dynamic properties. A mechanistic-empirical approach is implemented here to simulate the deterioration of a pavement, taking account of dynamic excitation of the axles. This paper highlights the importance of statistical spatial repeatability in damage evolution during the pavement life. Numerical integration of the distribution of forces at each point is shown to be sufficient to predict the changing road surface and elastic modulus. This results in an approximate 100-fold increase in computational efficiency. Finally, the pattern of the forces generated by the axles of a half car is found to be a little less damaging than that of independent quarter cars. In the examples considered, the quarter car reduces calculated pavement life by an average of 6%.Deposited by bulk impor

Estimation of lifetime maximum distributions of bridge traffic load effects

This paper considers the problem of assessing traffic loading on road bridges. A database of European WIM data is used to determine accurate annual maximum distributions of load effect. These in turn are used to find the probability of failure for a number of load effects. Using the probability of failure as the benchmark, traditional measures of safety - factor of safety and reliability index - are reviewed. Both are found to give inconsistent results, i.e., a given factor of safety or reliability index actually corresponds to a range of different probabilities of failure. © 2012 Taylor & Francis Group

STRATEGIES FOR AXLE DETECTION IN BRIDGE WEIGH-IN-MOTION SYSTEMS

To perform effectively, a Bridge Weigh-in-Motion (B-WIM) system requires accurate information on the location and speed of all axles on the bridge. In recent years, axle detection is by sensors under the bridge – so called Free-of-Axle-Detector or Nothing-On-Road (NOR) B-WIM. As axles pass over an axle detecting strain sensor, there is a peak in strain which can be detected by the data acquisition system. This approach works well for some bridges but there are challenges for beam-and-slab bridges where the beams are deep, a common form of construction in Alabama. The slabs in such bridges are therefore generally used for axle detection but the peaks in the slab strains are quite sensitive to the transverse position of the wheels over the beam. This paper describes a study into axle detection which tests alternative strategies for a range of bridge types and spans