Now showing 1 - 10 of 218
  • Publication
    Estimating Characteristic Bridge Loads On A Non-Primary Road Network
    When collecting truck loading data on a primary road network a common, approach is to install a large network of permanent pavement based Weigh-In-Motion systems. An alternative to this approach would be to use one or more portable Bridge Weigh-In-Motion systems which could be moved between bridges at regular intervals to determine the traffic loading throughout the network. A data collection strategy is needed to put such a system to best use. This paper details the data collection strategies which were examined for the National Roads Authority in Ireland. The use of urban economic concepts including Central Place Theory are discussed as methods for analysing which roads are expected to experience the greatest truck loading.
  • Publication
    A filtered measured influence line approach to bridge weigh-in-motion
    (Taylor & Francis (Routledge), 2010-07-11) ; ;
    In Bridge Weigh-in-Motion (B-WIM), an instrumented bridge is used as a scales to weigh passing trucks and their axles. The most common algorithm upon which modern B-WIM systems are based remains that developed by Moses (1979). The performance of this method is well documented; it is very good at estimating Gross Vehicle Weight, but less accurate for individual axles, particularly closely spaced axles on longer bridges. Many alternatives to Moses's original algorithm have been tested and some show the potential to improve accuracy but commercially available B-WIM systems are still based substantially on the original approach. This paper proposes a method of altering the B-WIM algorithm to improve the accuracy of the predictions. The measured dynamic signal, to which the algorithm is applied, is first filtered to remove high frequency components of the dynamic increment of load. The influence line used by the algorithm is also calculated differently. As previously described by OBrien et al. (2006) it is determined using a pre-weighed calibration truck and an algorithm to automatically convert the corresponding measured signal into a 'measured' influence line. However, for this work, the measured signal is first filtered to remove much of the high frequency dynamic components which results in a significant improvement in the overall accuracy of the system. Moses's equations are applied as in most other B-WIM systems but, in this case, using a filtered measured influence line and a filtered signal for the unknown truck. In this way, Moses's least squares fitting method is now comparing only the low frequency components of the measured and theoretical responses and produces a much more accurate fit. The new approach is tested in numerical models and it is shown to result in a substantial improvement in accuracy.
  • Publication
    Portable Bridge WIM Data Collection Strategy for Secondary Roads
    A common method of collecting traffic loading data across a large road network is to use a network of permanent pavement-based WIM systems. An alternative is to use one or more portable Bridge Weigh-In-Motion systems which are moved periodically between bridges on the network. To make optimum use of such a system, a suitable data collection strategy is needed to choose locations for the system. This paper describes a number of possible strategies which the authors have investigated for the National Roads Authority in Ireland. The different strategies are examined and their advantages and disadvantages compared. Their effectiveness at detecting a heavy loading event is also investigated and the preferred approach is identified.
  • Publication
    Damping Detection for Periodic Bridge Health Monitoring Using a Moving Vehicle
    In the past decade there has been a considerable increase in the number of bridges being instrumented for the purposes of vibration based monitoring, typically to monitor dynamic parameters such as frequencies and mode shapes. This type of approach using direct measurements can be very accurate and provide valuable information about a bridge structure. However, drawbacks of this approach include the time and expense associated with the installation of sensors and data acquisition equipment on the bridge. Also, although short to medium span bridges form the greatest proportion of transport networks worldwide, a large percentage of these are not instrumented. Therefore, more recently, a number of researchers have investigated the use of an alternative low-cost approach to monitor bridge dynamic parameters which involves the use of a moving vehicle fitted with accelerometers on its axles. By taking measurements on the vehicle only, this type of indirect method reduces the need for direct installations on the bridge. It is therefore aimed at providing an efficient alternative for the preliminary screening of the condition of short to medium span bridges in a transport network. In this paper, the feasibility of use of the instrumented moving vehicle to detect changes in bridge damping is investigated in a laboratory experiment. The damping of the bridge is used as a damage indicator in this paper as it has been shown to be damage sensitive. Furthermore, it has been found in numerical investigations that it is possible to detect changes in bridge damping from the acceleration response of an instrumented vehicle.
  • Publication
    Probabilistic analysis of potential impact of extreme weather events on infrastructures
    In recent years, a variety of extreme weather events, including droughts, rain induced landslides, river floods, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions across Europe and worldwide. These events can have devastating impact on critical infrastructure systems. The 7th Framework RAIN project will address these issues, involving partners from Ireland, Belgium, Germany, Finland, Italy, Netherlands, Slovenia and Spain. In this project, the impact of critical infrastructure failure on society, on security issues and on the economy will be examined. Based on the impacts of the failures, quantifiable benefits (from a societal, security and economic standpoint) of providing resilient infrastructure will be identified. In this project, a means of quantifying the level of risk will be established, first due to single land transport mode failures, and second due to selected multi-mode-interdependent failure scenarios (e.g. failure of power stations result in failure of electrical train lines). This paper introduces the RAIN project and its goal of developing a methodology to create an advanced risk assessment procedure, including a probabilistic based approach, to derive a measurable indicator of risk.
  • Publication
    Spatially Variable Assessment of Lifetime Maximum Load Effect Distribution in Bridges
    Bridge structures are key components of highway infrastructure and their safety is clearly of great importance. Safety assessment of highway bridges requires accurate prediction of the extreme load effects, taking account of spatial variability through the bridge width and length. This concept of spatial variability i s also known as random field analysis. Reliability - based bridge assessment permits the inclusion of uncertainty in all parameters and models associated with the deterioration process. Random field analysis takes account of the probability that two points n ear each other on a bridge will have correlated properties. This method incorporates spatial variability which results in a more accurate reliability assessm ent. This paper presents an integrated model for spatial reliability analysis of reinforced concre te bridges that considers both the bridge capacity and traffic load. A sophisticated simulation model of two - directional traffic is used to determine accurate annual maximum distributions of load effect. To generate the bridge loading scenarios, an extensi ve Weigh-in-Motion (WIM) database, from five European countries, is used. For this, statistical distributions for vehicle weights, inter - vehicle gaps and other characteristics are derived from the measurements, and are used as the basis for a Monte Carlo simulation of traffic. Results are presented for bidirectional traffic, with one lane in each direction, with a total flow of approximately 2000 trucks per day.
  • Publication
    The analysis of short signal segments and its application to Drive-by bridge inspection
    (Seventh Sense Research Group, 2015-05) ;
    ‘Drive-By’ damage detection is the concept of using sensors on a passing vehicle to detect damage in a bridge. At highway speeds, the vehicle spends a short amount of time on the bridge: it may not even go through a full oscillation, resulting in only a partial signal of the bridge motion being detected. Given that the spectral resolution of standard signal processing techniques depends on the length of data in the signal, they cannot be used to identify the bridge frequency accurately. In addition, the nonlinear and non-stationary nature of the vehicle-bridge interaction system poses challenges. An optimisation approach is proposed here as an alternative to standard signal processing techniques to overcome the challenges of short signals and the nonlinear nature of the drive-by system. Signal pollution due to the road profile is overcome using time-shifted bridge curvatures, a novel damage indicator.
  • Publication
    Experimental determination of dynamic allowance for traffic loading in bridges
    Bridge codes adopt values for dynamic allowance in traffic load models that are necessarily conservative to cover for an entire range of bridges with different mechanical characteristics, boundary conditions, and the large number of uncertainties associated to the vehicle-bridge interaction problem. A further level of conservatism occurs due to the independent manner in which the governing static load and the corresponding allowance for dynamics are specified. In particular, certain bridges are not susceptible to high levels of vehicle-bridge interaction when loaded by a critically heavy vehicle or a critical combination of vehicles. Recent advances in Bridge Weigh-In-Motion technology allow not only to collect information on the weights, spacings and speeds of the traffic loads traversing a bridge, but also to separate the maximum static strain from the total measured strain using a filtering procedure. In this paper, maximum static and total load effects are collected and analysed for three different sites as part of the European project ARCHES (6th RTD framework programme). Bridge measurements are used to discuss the dynamics of the most frequent truck classes and the entire traffic sample. The measurements reveal a decrease in percentage increment in dynamics and a reduction on the variability of the dynamic increment as the static load effect increases. This phenomenon can be of particular relevance in the assessment of the dynamics of extreme loading cases.
  • Publication
    Use of weigh-in-motion (WIM) data for site-specific LRFR bridge rating
    In this paper, truck weigh-in-motion (WIM) data are used to develop live load factors for use on Alabama state-owned bridges. The factors are calibrated using the same statistical methods that were used in the original development of AASHTO’s Load and Resistance Factor Rating (LRFR) Manual. This paper describes the jurisdictional and enforcement characteristics in the state, the WIM data filtering, sorting, and quality control, as well as the calibration process. Large WIM data sets from five sites were used in the calibration and included different truck volumes, seasonal and directional variations, and WIM data collection windows. Certain MATLAB programs were developed in the live load factor calibration process. The resulting state-specific live load factors are smaller than those of LRFR manual and are recommended to the Alabama Department of Transportation (ALDOT) in rating their bridges more efficiently
  • Publication
    The Effect of Lane Changing on Long-Span Highway Bridge Traffic Loading
    Maximum loading on long-span bridges typically occurs in congested traffic conditions. As traffic becomes congested car drivers may change lane, increasing the tendency for trucks to travel in platoons. For long-span bridges this phenomenon may increase the regularity and severity of bridge repair programs, with potential significant associated costs. This research investigates the effect of lane changing by car drivers on bridge loading. A Monte Carlo simulation model in which individual car drivers probabilistically decide, based on a lane-changing bias probability, whether or not to change lane has been developed. The sensitivity of bridge loading to this factor is investigated for different bridge lengths and traffic compositions. This research concludes that the lane-changing behavior of car drivers has an effect on bridge loading for long-span bridges, and the magnitude of this effect is quite sensitive to the percentage of trucks in the traffic.