Abstract:
Road pavement deterioration/failure prediction could be considered as the first step in highway maintenance implementation process. The present study focused on the model analysis of failure susceptibility for some roads in the South-western part of Nigeria using TDRAMS model. . The main purpose of using the TDRAMS model is to map pavement susceptibility to failure at different sections of the road. However, this method has been used for various roads without modification, thereby disregarding the effects of highway traffic modes, pavement features and road subsurface hydrogeologic characteristics. Thus, this technique must be standardized and be validated for applications to various highways with particular types of failure/deterioration inducing factors. In this study, the potential for the more precise evaluation of susceptibility to road failure is achieved by correcting the weights ratings of the TDRAMS parameters. This study assessed TDRAMS as a predictive model for investigating the susceptibility of south-western road to failure through proper analysis and simulation of data on TDRAMS [where T is traffic load, D is Depth to Water Table , California Bearing Ratio R, A is Cross section slope, M is maximum dry density (MDD), and S is asphalt thickness]. The weights and the ratings of the variables were given percentage increment to the optimum level (the value of TDRAMS at which there is no further change in the TDRAMS model).
Several simulation were carried out through the statistical package for social scientists (SPSS) tool, to critically analyse the contribution of each factor of TDRAMS in the overall TDRAMS value by changing the weight and the ratings of this factors.. The weights and ratings of the collected field data were also varied/modified to determine the sensitivity of the model. It was discovered after several simulations that each variable contributed differently to the TDRAMS value. Traffic load T, and The Depth to water table D were the most important factors in the TDRAMS model. Simulations on the varied weight showed that the most significant parameters were {T}Traffic load and{D}depth of water table at an optimum point of 81% increase in the weight of traffic from the original TDRAMS model (weight 32) and 78% increase in the depth of water table from the original TDRAMS model (weight 23). The modified TDRAMS model is efficient in assessing pavement failure susceptibility at any section of the road.
