Reliability Assessment of Road Pavements Subjected to Moving Surface Loads via Shakedown Concept

Fundamental shakedown theory is mostly employed to evaluate the long-term behavior of elastic-plastic bodies subjected to cyclic loadings. Particularly, shakedown analysis provides safe margins against fatigue and rutting in pavement structures subjected to moving surface loads. Pavement shakedown solutions have been traditionally found by adopting analytical/numerical deterministic approaches. In these approaches all input parameters such as geometry, loading conditions and material properties are supposed to be strictly definite and thus a general safety factor is adopted to incorporate inherent uncertainties. However, in the present paper an unpretentious probabilistic solution is presented by providing suitable limit state function for pavement shakedown problem. In this regard, random samples are generated individually by selecting a number of Monte Carlo simulations. Afterward, the failure probabilities and reliability indexes are determined by detection of the limit state function for every sets of generated random input parameters through Monte Carlo iterations. In the proposed solution, cohesion and friction angle of soil mass are pursued as log-normally distributed random variables within two-dimensional pavement shakedown analysis. The simulations indicate the importance of soil inherent variability regarding to the probabilistic analysis outcomes

Keywords:

Pavements , Reliability analysis , Shakedown , Monte Carlo simulations , Limit state function