An experimental design-based evaluation of sensitivities of MEPDG prediction: investigating main and interaction effects

Abstract

The mechanistic–empirical pavement design guide (MEPDG) uses mechanistic–empirical models by analysing the impacts of traffic, climate, materials and pavement structure to predict performances of pavement. The MEPDG software uses a three-level hierarchical input to predict performance in terms of terminal International Roughness Index, permanent deformation, total cracking (reflective and alligator), asphalt concrete (AC) thermal fracture, AC bottom-up fatigue cracking and AC top-down fatigue cracking. However, these inputs with different levels of accuracy may have significant impact on performance prediction. This study focuses on the sensitivity of the inputs of MEPDG distresses to identify the effect of the accuracy level of inputs based on experimental design. A local sensitivity analysis is carried out to identify the main effect of inputs considering them as independent variables. Interaction effects are also analysed based on random combination of the inputs. Sensitive input variables and their combinations are evaluated through a multiple regression analysis for respective distresses.