Search Results (2)

Pavement structures cover vast areas of urban cities and non-urban roads and play a key role in daily commuting functionality and economic development; therefore, they must be conserved against any distress. The rutting problem, being a major distress to the pavement structure, must be solved and dealt with in order to preserve its value. One way of solving this dilemma is by using geo-grids within the pavement structure. A geo-grid is a synthetic material usually made from polymers with different thicknesses and stiffnesses. This paper investigates the effects of geo-grids on reducing the rutting occurrence through adding a layer of geo-grid with certain properties at different levels of the pavement structure. We also investigate, the result of the added geo-grid material to the developed vertical stresses within the pavement cross-section. This investigation is conducted by constructing a 3-D finite elements-based (FE) model of a pavement cross-section using ANSYS software; student version R1 2021. The FE-based model is validated by comparing its numerical predictions with the experimental results acquired from an accelerated large-scale paved model. The results show that the deeper the geo-grid is positioned, the more significant the rutting resistance is observed due to the stiffness of the geo-grid bearing the tensile force until a certain depth. Moreover, noticeable stress reduction is seen in the developed vertical compressive stresses below the loading area resisted by the geo-grid. Full article

Compressed sensing is a thriving research field covering a class of problems where a large sparse signal is reconstructed from a few random measurements. In the presence of several sensor nodes measuring correlated sparse signals, improvements in terms of recovery quality or the requirement for a fewer number of local measurements can be expected if the nodes cooperate. In this paper, we provide an overview of the current literature regarding distributed compressed sensing; in particular, we discuss aspects of network topologies, signal models and recovery algorithms. Full article