Abstract
To assess the safety of an existing bridge, the loads to which it may be subject in its lifetime are required. Statistical analysis is used to extrapolate a sample of load effect values from the simulation period to the required design period. Complex statistical methods are often used and the end result is usually a single value of characteristic load effect. Such a deterministic result is at odds with the underlying stochastic nature of the problem. In this paper, predictive likelihood is shown to be a method by which the distribution of the lifetime extreme load effect may be determined. A basic application to the prediction of lifetime Gross vehicle Weight (GVW) is given. Results are also presented for some cases of bridge loading, compared to a return period approach and important differences are identified. The implications for the assessment of existing bridges are discussed.
| Original language | English |
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| DOIs | |
| Publication status | Published - 2006 |
| Event | 3rd. International ASRANet colloquium - Glasgow, United Kingdom Duration: 10 Jul 2006 → 12 Jul 2006 |
Conference
| Conference | 3rd. International ASRANet colloquium |
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| Country/Territory | United Kingdom |
| City | Glasgow |
| Period | 10/07/06 → 12/07/06 |
Keywords
- bridge
- safety
- loads
- statistical analysis
- simulation
- design period
- characteristic load effect
- stochastic nature
- predictive likelihood
- distribution
- lifetime extreme load effect
- Gross Vehicle Weight (GVW)
- bridge loading
- return period approach
- assessment