Now showing 1 - 10 of 27
- PublicationModeling same-direction two-lane traffic for bridge loadingMany highway bridges carry traffic in two same-direction lanes, and modeling the traffic loading on such bridges has been the subject of numerous studies. Different assumptions have been used to model multiple-presence loading events, particularly those featuring one truck in each lane. Using a database of weigh-in-motion measurements collected at two European sites for over 1 million trucks, this paper examines the relationships between adjacent vehicles in both lanes in terms of vehicle weights, speeds and inter-vehicle gaps. It is shown that there are various patterns of correlation, some of which are significant for bridge loading. A novel approach to the Monte Carlo simulation of such traffic is presented which is relatively simple to apply. This is a form of smoothed bootstrap in which kernel functions are used to add randomness to measured traffic scenarios. It is shown that it gives a better fit to the measured data than models which assume no correlation. Results are presented from long-run simulations of traffic using the different models and these show that correlation may account for an increase of up to 8% in lifetime maximum loading.
1401Scopus© Citations 83
- PublicationIdentifying and Modelling Permit Trucks for Bridge LoadingAccurate estimates of characteristic traffic load effects are essential in order to optimize bridge safety assessment. Permit trucks dominate the extreme upper tail of the truck loading distribution and as a result need careful examination. This paper proposes rules for filtering these trucks from Weigh-In-Motion data for both the US and Europe. The importance of these trucks in critical bridge loading events is then examined for both regions. A Monte Carlo traffic simulation model is developed which focuses on the accurate simulation of permit trucks.
Scopus© Citations 6 497
- PublicationPortable Bridge WIM Data Collection Strategy for Secondary RoadsA 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.
- PublicationCharacteristic Dynamic Increment for Extreme Traffic Loading Events on Short and Medium Span Highway BridgesMore accurate assessment of safety can prevent unnecessary repair or replacement of existing bridges which in turn can result in great cost savings at network level. The allowance for dynamics is a significant component of traffic loading in many bridges and is often unnecessarily conservative. Critical traffic loading scenarios are considered in this paper with a model that allows for vehicle–bridge interaction and takes into account the road surface condition. Characteristic dynamic allowance values are presented for the assessment of mid-span bending moment in a wide range of short to medium span bridges for bidirectional traffic.
873Scopus© Citations 85
- PublicationSpatial time-dependent reliability analysis of reinforced concrete slab bridges subject to realistic trafficResistance and loads are often correlated in time and space. The paper assesses the influence of these correlations on structural reliability/probability of failure for a typical two-lane RC slab bridge under realistic traffic loading. Spatial variables for structural resistance are cover and concrete compressive strength, which in turn affect the strength and chloride-induced corrosion of RC elements. Random variables include pit depth and model error. Correlation of weights between trucks in adjacent lanes and inter-vehicle gaps are also included and are calibrated against Weigh-In-Motion (WIM) data. Reliability analysis of deteriorating bridges needs to incorporate uncertainties associated with parameters governing the deterioration process and loading. One of the major unanswered questions in the work carried out to date is the influence of spatial variability of load and resistance on failure probability. Spatial variability research carried out to date has been mainly focused on predicting the remaining lifetime of a corroding structure and spatial variability of material, dimensional and environmental properties. A major shortcoming in the work carried out to date is the lack of an allowance for the spatial variability of applied traffic loads. In this paper, a 2-dimensional (2D) random field is developed where load effects and time-dependent structural resistance are calculated for each segment in the field. The 2D spatial time-dependent reliability analysis of an RC slab bridge found that a spatially correlated resistance results in only a small increase in probability of failure. Despite the fact that load effect at points along the length of a bridge are strongly correlated, the combined influence of correlation in load and resistance on probability of failure is small.
Scopus© Citations 20 310
- PublicationUsing Weigh-in-Motion Data to Determine Aggressiveness of Traffic for Bridge LoadingThis paper presents results based on the analysis of an extensive database of weigh-in-motion (WIM) data collected at five European highway sites in recent years. The data are used as the basis for a Monte Carlo simulation of bridge loading by two-lane traffic, both bidirectional and in the same direction. Long runs of the simulation model are used to calculate characteristic bridge load effects (bending moments and shear forces), and these characteristic values are compared with design values for bridges of different lengths as specified by the Eurocode for bridge traffic loading. Various indicators are tested as possible bases for a bridge aggressiveness index to characterize the traffic measured by the WIM data in terms of its influence on characteristic bridge load effects. WIM measurements can thus be used to determine the aggressiveness of traffic for bridges. The mean maximum weekly gross vehicle weight is proposed as the most effective of the indicators considered and is shown to be well correlated with a wide range of calculated characteristic load effects at each site.
867Scopus© Citations 79
- PublicationA Review of the HL-93 Bridge Traffic Load Model Using an Extensive WIM DatabaseHL-93, the current bridge traffic load model used in the United States is examined here. Weigh-in-motion (WIM) data from 17 sites in 16 states containing 74 million truck records are used to assess the level of consistency in the characteristic load effects (LEs) implied by the HL-93 model. The LEs of positive and negative bending moments and shear force are considered on single- and two-lane same-direction slab and girder bridges with a range of spans. It is found that the ratio of WIM-implied LE to HL-93 LE varies considerably from one LE to another. An alternative model is proposed that achieves improvements in consistency in this ratio for the LEs examined, especially for the single-lane case. The proposed model consists of a uniformly distributed load whose intensity varies with bridge length.
514Scopus© Citations 18
- PublicationLifetime maximum load effects on short-span bridges subject to growing traffic volumesThis paper investigates the phenomenon of growth in truck volumes during the lifetime of a bridge and the influence of that growth on characteristic maximum load effects. The study uses Weigh-in-Motion (WIM) data from the Netherlands to calibrate Monte Carlo simulation of load effects on a range of bridge spans. For short spans, the distribution of 25-day maximum data is Weibull. As span increases, a better fit is obtained with a mixture that separates low loader vehicles from all others. Growth is addressed by assuming constant, linear or quadratic variations in the properties of the best-fit Generalized Extreme Value distributions. The principle of parsimony is used to select the most appropriate fit. Growth is shown to change the nature of the trend on probability paper, shifting the curves to the right. While the influence of growth is relatively modest, fitting non-stationary data to a stationary curve gives erroneous results.
445Scopus© Citations 45
- PublicationA Bayesian approach for estimating characteristic bridge traffic load effectsThis paper investigates the use of Bayesian updating to improve estimates of characteristic bridge traffic loading. Over recent years the use Weigh-In-Motion technologies has increased hugely. Large Weigh-In-Motion databases are now available for multiple sites on many road networks. The objective of this work is to use data gathered throughout a road network to improve site-specific estimates of bridge loading at a specific Weigh-In-Motion site on the network. Bayesian updating is a mathematical framework for combining prior knowledge with new sample data. The approach is applied here to bridge loading using a database of 81.6 million truck records, gathered at 19 sites in the US. The database represents the prior knowledge of loading throughout the road network and a new site on the network is simulated. The Bayesian approach is compared with a non-Bayesian approach, which uses only the site-specific data, and the results compared. It is found that the Bayesian approach significantly improves the accuracy of estimates of 75-year loading and, in particular, considerably reduces the standard deviation of the error. With the proposed approach less site-specific WIM data is required to obtain an accurate estimate of loading. This is particularly useful where there is concern over an existing bridge and accurate estimates of loading are required as a matter of urgency.
- PublicationEstimating characteristic bridge traffic load effects using Bayesian statisticsThis paper investigates the use of Bayesian updating to improve estimates of characteristic bridge traffic loading. Over recent years the use Weigh-In-Motion technologies has increased hugely. Large Weigh-In-Motion databases are now available for multiple sites on many road networks. The objective of this work is to use data gathered throughout a road network to improve site-specific estimates of bridge loading at a specific Weigh-In-Motion site on the network. Bayesian updating is a mathematical framework for combining prior knowledge with new sample data. The approach is applied here to bridge loading using a database of 81.6 million truck records, gathered at 19 sites in the US. The database represents the prior knowledge of loading throughout the road network and a new site on the network is simulated. The Bayesian approach is compared with a non-Bayesian approach, which uses only the site-specific data, and the results compared. It is found that the Bayesian approach significantly improves the accuracy of estimates of 75-year loading and, in particular, considerably reduces the standard deviation of the error. With the proposed approach less site-specific WIM data is required to obtain an accurate estimate of loading. This is particularly useful where there is concern over an existing bridge and accurate estimates of loading are required as a matter of urgency.