Traffic load model based on weigh in motion measurements
| Autor: | Steenbergen, R. D. J. M., Morales Napoles, O. |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Axles
Safety engineering Bridge design Dynamic amplification factors Buildings and Infrastructure Distributed loads Traffic load Traffic loads Weigh-in-motion systems Traffic intensity SR - Structural Reliability Return periods Traffic load model Univariate Weigh in motion Bridge spans Vehicle weights Vehicle speed Measured parameters Vehicle characteristics Weigh-in-motion datum Built Environment Building Engineering & Civil Engineering Architecture Traffic Future trends Netherlands TS - Technical Sciences Existing bridge Vehicle load Structural safety Vehicles Design load Non-parametric Bridges Weigh-in-motion (WIM) Ultimate limit state Bayesian belief net Bridge structures Safety level Traffic flow models Congested traffic Measurement programs Motion measurements |
| Zdroj: | 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012, 25 June 2012 through 29 June 2012, Helsinki, 933-945 Scopus-Elsevier |
| Popis: | The assessment of the structural safety of existing bridges and viaducts becomes increasingly important in many countries. Within the actions applied to the bridges, the traffic load is, in general, the most significant variable action to be considered when the ultimate limit states are under investigation. Over the last years a considerable increase in traffic loads and intensities has been observed. In this paper design traffic loads for bridges are derived based on an extensive measurement program of vehicle characteristics. Traffic load measurements were carried out in several highways using the Weigh in Motion (WIM) system; for every vehicle, variables recorded by the system include vehicle speed, number of axles, inter axle separation, and axle and vehicle weight. Part of the study is the composition of a Non Parametric Continuous Bayesian Belief Net in order to be able to obtain insight in the several measured parameters. This model has been quantified with data from eight WIM locations in the Netherlands. It consists of 705 nodes representing univariate margins and more than 2,300 arcs. Design loads should be derived such that they provide a sufficient safety level of the bridge; this corresponds to a bridge design using traffic loads with a return period in the order of magnitude of tens of thousands of years. Extrapolation of the Weigh in Motion data is therefore carried out through several statistical methods. For the lane loads a probabilistic traffic flow model was constructed including axle and vehicle loads, traffic intensities, lorry distances and speeds for free and congested traffic. Results are distributed loads on single and multiple lanes for different bridge spans. The value can be used in bridge design in combination with dynamic amplification factors and factors taking into account the uncertainties in the model and the future trends. |
| Databáze: | OpenAIRE |
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