Computer simulation and field measurement of dynamic pavement loading

Mathematics and Computers in Simulation (Impact Factor: 0.95). 06/2001; 56(3):297-313. DOI: 10.1016/S0378-4754(01)00297-X


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.

Download full-text


Available from: L. Sun, Dec 10, 2014
  • Source
    • "The results showed that the dynamic loads were significantly higher than the static loads under rough pavement conditions. Sun (2001) compared the predicted and measured Dynamic Pavement Load (DPL) generated by vehicle pavement interaction. Based on measured profiles of pavement surface, the dynamic load was simulated based on a quarter car model. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this study is to investigate the effects of vehicle operation properties on vehicle dynamic loads. A continuous or distributed model is formulated using a two-dimensional (2D) half-truck finite element model and analysed. Using the 2D half-truck finite element model, numerical simulations were performed to obtain the dynamic loads using various parameters such as the road roughness, vehicle speed, suspension stiffness and damping in order to evaluate their individual effects on the dynamic axle load response. The Impact Factor (IF) and Dynamic Load Coefficient (DLC) based on dynamic loads were calculated. The results show that the IF and DLC are increased as road roughness and vehicle speed increase. In addition, decreasing the suspension stiffness and increasing the damping reduces the IF. For a particular suspension type, the suspension stiffness and damping coefficient have no significant impact on the DLC.
    Full-text · Article · Nov 2014 · KSCE Journal of Civil Engineering
  • Source
    • "Commonly, stochastic models are used to describe the variability of measured road profiles and, in particular, Gaussian processes are often employed. Hence, responses, assuming stationary conditions, constant velocity and linear relation between the road surface and vehicle responses, are also stationary and Gaussian, see, for example, [1] [2] [3] [4] for some recent studies. However, measured profiles are not accurately represented by a stationary Gaussian model as pointed out in the literature, see for example, in [2]. "
    [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.
    Full-text · Article · May 2012 · Vehicle System Dynamics
  • Source
    • "For example, Schmeitz et al.(2004) presented both tyre and vehicle models over arbitrary road profiles, and investigated how the vehicle system behaved and how the enveloping model that generated an effective road surface contributed to this behavior . Sun (2001) adopted computer simulation and field measurement to investigate dynamic pavement loading generated by vehicle-pavement interaction and established an approximate relationship between road surface roughness and the measurement instrument coefficient of variation and vehicle speed. Some metrics have been put forward and used for measuring handling and ride comfort considering terrain conditions and tyre types (Uys et al., 2006). "
    [Show abstract] [Hide abstract]
    ABSTRACT: In order to reconstruct typical off-road terrain surface for vehicle performance virtual test, a terrain generation method with controllable roughness was proposed based on fractal dimension. Transverse profile sampling and unevenness characteristics of typical off-road terrain were discussed according to the choices of appropriate wavelength and sampling interval. Since the off-road terrain in virtual environment is self-similar, the method of calculating the discrete fractal Gauss noise and its auto-correlation function were analyzed. The terrain surface fractal dimension was estimated by determining the Hurst coefficient. As typical off-road terrain is rugged terrain, the method of reconstructing it using fractal modelling is presented. The steps include calculating statistical variations in the absolute value of the difference in elevation between two points, plotting the points in log-log space, identifying linear segments and estimating fractal dimension from the linear segments slope. The constructed surface includes information on potholes, bumps, trend and unevenness of terrain, and can be used as the excitation of vehicle performance virtual test.
    Preview · Article · Jul 2006 · Journal of Zhejiang University - Science A: Applied Physics & Engineering
Show more