Article

Computer simulation and field measurement of dynamic pavement loading

Mathematics and Computers in Simulation (Impact Factor: 0.84). 01/2001; 56:297-313. DOI: 10.1016/S0378-4754(01)00297-X

ABSTRACT Two methods, i.e. computer simulation and field measurement, are used in this paper to investigate dynamic pavement loading (DPL) generated by vehicle–pavement interaction. A profilometer is used for measuring road surface roughness. Based on the power spectral density of the measured surface roughness, a computer simulation program is developed using quarter vehicle model. In field measurement methods, an experiment is designed to gain the time history of DPL. An IVECO vehicle is taken as a test vehicle and eight vibration cells were used to pick up vertical accelerations of vehicle body and axle. The test data are collected and recorded while the test vehicle is moving along 11 different pavement sections of highway and bridge at six different speeds. Statistical characteristics of vertical accelerations and DPL of the test vehicle are obtained and analyzed by means of random process theory. The result of computer simulation matches the result of field measurement very well. It is found that DPL is primarily concentrated between 1.8 and 14.8 Hz and coefficient of variation of DPL falls into the range of 5–35% of static vehicle load. An approximate relationship between coefficient of variation of DPL and vehicle speed and road surface roughness is established. © 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.

0 Bookmarks
 · 
87 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This study focuses on the statistical description and analysis of road surface irregularities that are essential for heavy-vehicle fatigue assessment. Three new road profile models are proposed: a homogenous Laplace moving average process, a non-homogenous Laplace process and a hybrid model that combines Gaussian and Laplace modelling. These are compared with the classical homogenous Gaussian process as well as with the non-homogenous Gaussian model that represents the road surface as a homogenous Gaussian process with Motor Industry Research Association spectrum enhanced by randomly placed and shaped irregularities. The five models are fitted to eight measured road surfaces and their accuracy and efficiency are discussed.
    Vehicle System Dynamics 05/2012; 50(5):725-747. · 0.77 Impact Factor
  • Source
    Journal of Multivariate Analysis 01/2013; 113:59-72. · 1.06 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Multivariate Laplace distribution is an important stochastic model that accounts for asymmetry and heavier than Gaussian tails, while still ensuring the existence of the second moments. A Levy process based on this multivariate infinitely divisible distribution is known as Laplace motion, and its marginal distributions are multivariate generalized Laplace laws. We review their basic properties and discuss a construction of a class of moving average vector processes driven by multivariate Laplace motion. These stochastic models extend to vector fields, which are multivariate both in the argument and the value. They provide an attractive alternative to those based on Gaussianity, in presence of asymmetry and heavy tails in empirical data. An example from engineering shows modeling potential of this construction.
    Journal of Multivariate Analysis 01/2013; 113:59-72. · 1.06 Impact Factor

Full-text

View
1 Download
Available from