Resilient modulus for unbound granular materials and subgrade soils in Egypt

Abstract

Abstract. Mechanistic Empirical (ME) pavement design methods started to gain attention especially the last couple of years in Egypt and the Middle East. One of the challenges facing the spread of these methods in Egypt is lack of advanced properties of local soil and asphalt, which are needed as input data in ME design. Resilient modulus (Mr) for example is an important engineering property that expresses the elastic behavior of soil/unbound granular materials (UGMs) under cyclic traffic loading for ME design. In order to overcome the scarcity of the resilient modulus data for soil/UGMs in Egypt, a comprehensive laboratory testing program was conducted to measure resilient modulus of typical UGMs and subgrade soils typically used in pavement construction in Egypt. The factors that affect the resilient modulus of soil/UGMs were reviewed, studied and discussed. Finally, the prediction accuracy of the most well-known Mr Prediction models for the locally investigated materials was investigated.

Particle Swarm Optimization Algorithm-Extreme Learning Machine (PSO-ELM) Model for Predicting Resilient Modulus of Stabilized Aggregate Bases

“…According to the Mechanistic-Empirical Pavement Design Guide, among other factors, W-D and freeze-thaw cycles are important parameters that degrade the base/subbase materials and may contribute to premature failure of pavements [4]. There is a significant correlation between the W-D and freeze-thaw conditions in terms of durability and the resilient modulus (M r ) or equivalent elastic modulus, which measures the performance of base materials in a pavement structure [4][5][6][7]. M r values can be measured in the laboratory in accordance with the AASHTO T307 [8] or predicted by soft computing models [3,9].…”

Predicting Resilient Modulus of Unbound Granular Base/Subbase Material. (Dept. C)

“…UGMs are typically characterized using various geotechnical parameters such as gradation, fines content, particle shape, maximum/nominal maximum aggregate size, LL, PI, uniformity coefficient (Cu), and coefficient of curvature (Cc). Many researchers showed that the modulus of these materials depends, to some extent, on some or all of these parameters [22].…”

“…From literature, various models were developed to predict the MR of UGMs based on index characteristics, stress state and moisture content [22]. The following subsections present the well-known established models for predicting the MR of coarse materials that have been published in the literature.…”

Construction and demolition waste as raw material in pavements layers

“…The results showed that the material tested can only be used in a pavement subbase, since its CBR was 29.8% and the swelling of 0.1% is made within the limit established by the standard. Finally, it is possible to find in literature several resilient modulus models to predicted (Mr) values depending on material properties, such as CBR (Mousa et al, 2017b). For materials with CBR > 10%, the following equation is suggested, 𝑀 𝑟 = 2555 × 𝐶𝐵𝑅 0.65 (2)…”