A relatively large number of drying and wetting tests have been performed on clayey soils compacted at the standard or modified Proctor optimum water content and maximum density and compared with tests on normally consolidated or overconsolidated soils. The results show that drying and wetting paths on compacted soils are fairly linear and reversible in the void ratio or water content versus negative pore-water pressure planes. On the wet side of the optimum, the wetting paths are independent of the compaction water content and can be approached by compaction tests with measurement of the negative pore-water pressure. Correlations have been established between the liquid limit of the soils and such properties as the optimum water content and negative pore-water pressure, the maximum dry density, and the swelling or drying index. Although based on a limited number of tests, these correlations provide a fairly good basis to model the drying–wetting paths when all the necessary data are not available.Key words: compaction, unsaturated soils, clays, drying, wetting, Proctor conditions.

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This paper reports a study undertaken to achieve a compatible and affordable technique for the high-quality dispersion of carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) in an aqueous suspension to be used in multifunctional cementitious composites. In this research work, two noncovalent surfactants with different dispersion mechanisms (Pluronic F-127 (nonionic) and sodium dodecylbenzene sulfonate (SDBS) (ionic)) were used. We evaluated the influences of various factors on the dispersion quality, such as the surfactant concentration, sonication time, and temperature using UV-visible spectroscopy, optical microscopic image analysis, zeta potentials, and particle size measurement. The effect of tributyl phosphate (TBP) used as an antifoam agent was also evaluated. The optimum suspensions of each surfactant were used to produce cementitious composites, and their mechanical, microstructural, electrical, and thermal behaviors were assessed and analyzed. The best dispersed CNT+GNP aqueous suspensions using Pluronic and SDBS were obtained for concentrations of 10% and 5%, respectively, with 3 hours of sonication, at 40°C, with TBP used for both surfactants. The results also demonstrate that cementitious composites reinforced with CNT+GNP/Pluronic showed better mechanical performance and microstructural characteristics due to the higher quality of the dispersion and the increasing hydration rate. Composites prepared with an SDBS suspension demonstrated lower electrical and thermal conductivities compared to those of the Pluronic suspension due to changes in the intrinsic properties of CNTs and GNPs by the SDBS dispersion mechanism.

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In this paper a hybrid combination of carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) was used for developing cementitious self-sensing composite with high mechanical, microstructural and durability performances. The mixture of these two nanoparticles with different 1D and 2D geometrical shapes can reduce the percolation threshold to a certain amount which can avoid agglomeration formation and also reinforce the microstructure due to percolation and electron quantum tunneling amplification. In this route, different concentrations of CNT + GNP were dispersed by Pluronic F-127 and tributyl phosphate (TBP) with 3 h sonication at 40 °C and incorporated into the cementitious mortar. Mechanical, microstructural, and durability of the reinforced mortar were investigated by various tests in different hydration periods (7, 28, and 90 days). Additionally, the piezoresistivity behavior of specimens was also evaluated by the four-probe method under flexural and compression cyclic loading. Results demonstrated that hybrid CNT + GNP can significantly improve mechanical and microstructural properties of cementitious composite by filler function, bridging cracks, and increasing hydration rate mechanisms. CNT + GNP intruded specimens also showed higher resistance against climatic cycle tests. Generally, the trend of all results demonstrates an optimal concentration of CNT (0.25%) + GNP (0.25%). Furthermore, increasing CNT + GNP concentration leads to sharp changes in electrical resistivity of reinforced specimens under small variation of strain achieving high gauge factor in both flexural and compression loading modes.

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Jet grouting (JG) is a soil treatment technique which is the best solution for several soil improvement problems. However, JG lacks design rules and quality controls. As a result, the main JG works are planned from empirical rules that are too conservative. The development of rational models to simulate the effects of the different parameters involved in the JG process is of primary importance in order to satisfy the binomial safety-economy that is required in any engineering project. In this paper, we present a new approach to predict the uniaxial compressive strength (UCS) of JG materials based on data mining techniques. This model was developed and verified using data from a JG laboratory formulation that involves the measurement of UCS. The results of the proposed approach are compared with the EC2 analytical model adapted to the JG material, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the UCS of JG material and its contributing factors.

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