| dc.description.abstract | Accurate modelling of pavement response plays a critical role in the effective design,
analysis, and maintenance of road infrastructure. However, the presence of uncertainty
in material parameters can significantly compromise the reliability and accuracy of such
models. This study focuses on investigating the impact of uncertain material parameters
on pavement response by employing an inverse modelling technique. The objective of this
research is to utilize an inverse modelling approach to assess the influence of uncertain
material parameters on Uzan’s model, a commonly used model for pavement response.
The study considers measured stress and strain values obtained from tyre and Falling
Weight Deflectometer load conditions applied to granular materials. The inverse model
is formulated as a nonlinear least squares minimization problem, in conjunction with
a finite element model that analyses the deformation of flexible pavements. Through
the application of the inverse modelling technique, this study aims to determine the
extent to which uncertain material parameters affect the accuracy of pavement response
predictions. By comparing the predicted pavement behaviour derived from the inverse
model with actual measured data, the influence of uncertain parameters can be quantified.
The outcomes of this research contribute to advancing the understanding of the complex
interplay between material parameter uncertainties and pavement response. | en_US |
