Accurate critical stress prediction is a key element for a mechanistic–empirical design of pavement structures. For unbonded concrete overlays (UBOL), the critical stress prediction procedure used by the current Mechanistic–Empirical Pavement Design Guide (MEPDG) has several shortcomings. The current MEPDG UBOL model only predicts top or bottom-critical longitudinal stresses, so transverse fatigue cracking is considered whereas longitudinal cracking, which has been observed in several in-service overlays, is ignored. The MEPDG critical stress prediction models assume that the UBOL and the existing pavement have the same deflection profiles, ignoring the separation between the overlay and the existing pavement. Various interlayer properties influencing critical overlay stress are also overlooked. In addition, the model only considers conventional lane width UBOLs and is unable to analyze short slab overlays. The latter has been gaining popularity as an attractive geometry for UBOLs. This paper documents the development of an improved procedure for computing UBOL critical stresses for conventional and short width slabs geometry. The procedure is able to predict critical transverse and longitudinal stresses at various locations taking into account interlayer stiffness and the presence of voids in the interlayer. Rapid solutions using neural networks were developed to enable computationally efficient UBOL critical stress prediction.
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