Bridge live load models from WIM data
Miao, T.J. & Chan, Tommy H.T. (2002) Bridge live load models from WIM data. Engineering Structures, 24(8), pp. 1071-1084.
This paper describes the development of a new methodology for deriving highway bridge live load models for short span bridges. The development is based on a 'repeatable' methodology to obtain extreme daily moments and shears using 10 years Hong Kong weigh-in-motion (WIM) data as compared to the traditional normal probability paper approach. The methodology can also be applied to the development of bridge live loading models in other parts of the world. Two types of loading are proposed. A methodology based on the equivalent base length concept is used to derive the lane loading model and the standard truck loading model is developed based on a statistical approach. The developed lane and truck loadings are compared with other loading models adopted locally and overseas. It is the first time in Hong Kong the bridge design loading is developed based on actual acquired load data using statistical and probabilistic approach.
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|Item Type:||Journal Article|
|Additional Information:||For more information, please refer to the journal's website (see hypertext link) or contact the author.|
|Keywords:||average daily truck traffic, equivalent base length, extreme daily events, Kolmogorov, Sminorv method, Monte Carlo simulation, loading models, maximum observed load, probability level, statistical analysis, weigh, in, motion|
|Subjects:||Australian and New Zealand Standard Research Classification > TECHNOLOGY (100000)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Structural Engineering (090506)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||Copyright 2002 Elsevier|
|Deposited On:||03 Mar 2008 00:00|
|Last Modified:||10 Aug 2011 16:08|
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