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In the proposed paper two computing models of pavement are described and mutually compared.
One-dimensional and two-dimensional random field models of pavement surface are discussed given three different assumptions.
Although the parametric analysis findings vary depending on the specific pavement response, the study results illustrate the appropriate selection of analysis type, constitutive models of pavement material, and layer boundary conditions on the accuracy of FE modeling results.
This differs from previous models of pavement cell shape change that were based on static images and population-level sampling [ 10, 20, 26].
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Consider a two-dimensional random field model of pavement surface as shown in Fig. 7.
Open image in new window Fig. 6 Two-dimensional random field model of pavement surface.
For more accurate applications, it is no longer necessary to use hypothetical random field model of pavement surface.
In this paper, an image-based technique for the assessment of a 3D model of pavement texture is presented.
The hypothesis of isotropy is applied to the measured one-dimensional road profile so that a two-dimensional random field model of pavement surface roughness can be achieved.
One-dimensional random field model of pavement surface is adequate for two-wheel vehicles, such as bicycles and motor-cycles but inadequate for cars and trucks having two or more wheel per axle.
Their model of a sunflower capitulum is a continuum surface, whereas in our cellular model of pavement cells we encounter discontinuities at the boundaries of the cells.
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