Type

Journal Article

Authors

Eugene J. O'Brien
Colin C. Caprani

Subjects

Mathematics

Topics
monte carlo extreme value statistics traffic bridge structural dynamics statistical methods extreme value theory bridges live loads probabilistic load predictive likelihood

The use of predictive likelihood to estimate the distribution of extreme bridge traffic load effect (2010)

Abstract To assess the safety of an existing bridge, the loads to which it may be subject in itslifetime 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. An estimate of the distributions of lifetime maximum load effect facilitates the reliability approach to bridge assessment. Results are presented for some cases of bridge loading, compared to a return period approach and significant differences identified. The implications for the assessment of existing bridges are discussed.
Collections Ireland -> University College Dublin -> Critical Infrastructure Group Research Collection
Ireland -> University College Dublin -> Interdisciplinary Centres & Research Groups
Ireland -> University College Dublin -> Civil Engineering Research Collection
Ireland -> University College Dublin -> College of Engineering & Architecture
Ireland -> University College Dublin -> Critical Infrastructure Group
Ireland -> University College Dublin -> School of Civil Engineering

Full list of authors on original publication

Eugene J. O'Brien, Colin C. Caprani

Experts in our system

1
Eugene J. O'Brien
University College Dublin
Total Publications: 192
 
2
Colin C. Caprani
University College Dublin
Total Publications: 42