Proposta para seleção de ligantes e misturas asfálticas considerando deformação permanente e fadiga

Abstract

Since the performance of a pavement depends, among other factors, on the performance of the binder and the asphalt mixture, several researches of the Group of Studies and Research in Pavement and Road Safety (GEPPASV) were dedicated to the characterization of these materials. The structured organization of these data is necessary for the understanding of asphalt materials with greater reliability. In this sense, based on the systematic structuring of a group database, this research aimed to classify asphalt materials using permanent deformation and fatigue criteria, to establish correlations between scales, and to perform a general classification of asphalt binders and mixtures considering both defects together. Initial investigation of the data showed that the indicators softening point, Brookfield viscosity at 135°C, |G*|/senɸ, |G*|65°C:1Hz, ɸ65°C:1Hz, continuous PGH and "h" from 2s2p1d modeling, are potential indicators of permanent deformation in binders, but Jnr was found to be the most suitable. For fatigue in binders, the parameters  of the 2s2p1d modeling, cycles to failure and the fatigue factor of the binder (FFL19°C) were highlighted. For both permanent deformation and fatigue, polymer-modified binders appear to outperform the others, although there are exceptions. For permanent deformation in mixtures, the shape index of the aggregate fraction #3/4, |E*|54°C:1Hz, |E*|/senɸ54°C:1Hz, RAP content, parameters "h" and E00 (2s2p1d) and "g" (sigmoidal) seem to be good indicators. In general, stiffer and/or polymermodified mixtures appear to be better for permanent deformation. For fatigue in mixtures, the best indices observed were |E*|21°C:1Hz, "d" from sigmoidal modeling, the mixture fatigue factor (FFM) and the index  from G R vs. Nf curves. Mixtures with modified binder seem to show better behavior. Relationships between scales identified that Jnr3.2, viscosity at 135°C and softening point can make reasonable inferences about Flow Number, and that if the parameters  and "k" of 2s2p1d in binders, and FFL19°C can infer about the FFM of the mixtures. Pavement fatigue was simulated by FlexPAVETM and MeDiNa programs, considering 3 structures, suitable for medium, heavy and extremely heavy traffic. For these simulations, FlexPAVETM better discretized the differences between mixtures with different binders, and MeDiNa predicted, in general, higher cracked area values.The index  was the most suitable to infer about the cracked area calculated by FlexPAVETM damage, and MR*FFM about the cracked area of MeDiNa. The 25 binder classes, identified by Jnr3.2 64°C and FFL19°C maxPSE, the 6 mixture classes for each scenario simulated in FlexPAVETM, and the 4 mixture classes for each scenario simulated in MeDiNa, enable the most assertive and economical selection of asphalt materials based on the two main defects of Brazilian pavements, which occur simultaneously in the field, adapting them to the traffic condition foreseen in the project