Consideration of the permanent deformation of soils that occurred in the northeast region in the mechanistic-empirical analysis of pavements

Materia

article

Wendel Silva Cabral¹  Suelly Helena de Araújo Barroso²  Samuel de Almeida Torquato e Silva³ 

[1] Universidade Federal Rural do Semi-Árido;Universidade Federal do Ceará;Universidade de Brasília

关键词: Permanent deformation;    pavement;    dimensioning;    triaxial test;    artificial neural network;   

DOI  :  10.1590/S1517-707620210004.1396

学科分类：工程和技术（综合）

来源: Universidade Federal do Rio de Janeiro * Coordenacao dos Programas de Pos-Graduacao de Engenharia

【 摘 要 】

In order to establish more efficient designs and adequate construction criteria in the paving area, it is essential to understand the performance of the materials in relation to the mechanistic-empirical dimensioning methods. This work analyzes the properties of Permanent Deformation (DP) and Resilience Module (MR) of soils used in pavement layers to evaluate different types of dimensioning, mechanistic-empirical and empirical of Brazilian highways. The test method for obtaining PD was the multi-stage repeated load triaxial (RLT), with the application of 10,000 cycles per stage, and the mechanistic-empirical dimensioning was performed using the MeDiNa method, recently disclosed in Brazil, and the CAP program 3D-D, which performs numerical analyzes of stresses and displacements of the proposed pavements. The technique used for the development of PD prediction models was Artificial Neural Networks (ANN). The results showed that both the test method and the prediction equations performed satisfactorily in obtaining the behavior of PD. The sizing performed using the methods used resulted in different structures. It is concluded that the model and the technique of obtaining used, as well as the test methodology have great potential to characterize and model the PD of granular materials and that Brazil should invest more and more in the use of mechanistic-empirical methods for analysis of pavements.

【 授权许可】

CC BY