Evaluation of reliability index and probability of failure for the improvement of the Nigerian empirical mechanistic flexible pavement analysis and design system (Nempads)

Abstract

The aim of this work was to evaluate reliability index (RI) with respect to fatigue and rutting within the different seasons peculiar to Nigeria, in order to improve Empirical-Mechanistic flexible pavement design approach, using First Order Reliability Method (FORM). Flexible pavement design involves many uncertainties, variabilities, and approximations regarding the input parameters like material properties, traffic loads. Others include subgrade strength, drainage conditions, construction, compaction procedures and climatic factors such as temperature, rainfall, and snowfall, etc. The combination of the variances associated with input parameters contributes to components and system uncertainty, and this combination of variances can have a significant effect on the predicted performance of the pavement. Reliability in pavement design is introduced to consider these uncertainties. Layers thicknesses, material properties, and Equivalent Standard Axle Load (ESAL) were entered into a multi-layer elastic theory software, ELSYM-5, which in turn were used to calculate strains and stresses for different seasons. The results obtained were entered into Nigerian fitted transfer function distress models to compute allowable ESALS. Miner’s hypothesis theory equation was used to calculate the cumulative damage due to stress and strains generated. A Framework was generated for finding individual reliability index (RI), systemic reliability index (SRI), and probability of failure. The findings showed that Season I (Winter) recorded the highest component reliability index for fatigue (5.63 for Normal Distribution). Season II (Summer) recorded the lowest component reliability index (β) for rutting (5.4 for Normal Distribution). Season III (Spring) recorded the lowest component reliability index for fatigue (1.85 for Normal Distribution)