Please use this identifier to cite or link to this item:
Title: Statistical models from weigh-in-motion data
Authors: Chan, THT
Miao, TJ
Ashebo, DB
Keywords: Axle weight
Dense traffic status
Gross vehicle weight
Inattentive traffic status
Monte Carlo method
Stochastic process
Weigh in motion
Issue Date: 2005
Publisher: Techno Press
Source: Structural engineering and mechanics, 2005, v. 20, no. 1, p. 85-110 How to cite?
Journal: Structural engineering and mechanics 
Abstract: This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.
ISSN: 1225-4568
EISSN: 1598-6217
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 14, 2018


Last Week
Last month
Citations as of Aug 17, 2018

Page view(s)

Last Week
Last month
Citations as of Aug 12, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.