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The present work aims to evaluate expansive soil stabilization using different additives. Twenty soil mixtures consisting of 10%, 20%, 25%, and 30% zeolitic tuff (ZT) with 2%, 4%, and 6% lime in various combinations were used to stabilize the soil for pavement subbase application. A comprehensive test program, including Atterberg's limits, compaction, unconfined compression strength (UCS), California Bearing Ratio (CBR), resilient modulus, and permanent deformation, was performed on natural and stabilized soil specimens. Scanning electron microscopy (SEM) supplied with energy-dispersive X-ray spectroscopy (SEM/EDX) was used to confirm the study findings. Adding ZT increases the availability of the silica and alumina needed for the pozzolanic reaction; test results revealed that adding ZT increases the maximum dry unit weight, CBR, UCS, resilient modulus, decreases plasticity, and permanent deformation. As such, ZT can improve the physical and mechanical properties of lime-stabilized soil as a pavement's subgrade and subbase layers. [ABSTRACT FROM AUTHOR]

Due to a lack of geotechnical and geothermal studies on Jordanian limestone, this paper aims to provide the thermal properties, including thermal conductivity, thermal diffusivity, and specific heat, using the Hot Disk Transient Plane Source (TPS) 2200 method. It also aims to provide a set of mathematical models through which the thermal properties can be indirectly predicted from the rocks' physical and engineering properties. One hundred cylindrical rock specimens with a height of 20 cm and a diameter of 10 cm were extracted and prepared. The results showed that the thermal conductivity values ranged between (1.931–3.468) (W/(m × k)), thermal diffusivity (1.032–1.81) (mm2/s), and specific heat (1.57–2.563) ((MJ)/(m3 × K)). The results also suggest a direct relationship between conductivity and diffusivity and an inverse relationship between conductivity and specific heat. On the other hand, the results indicate the direct relationship between the conductivity and diffusivity, and the inverse relationship between the specific heat and density, hardness, sound velocity, and rock strength; the opposite happens when the rock's porosity is considered. Simple regression, multivariate regression, and the backpropagation–artificial neural network (BP–ANN) approach were utilized to predict the thermal properties of limestone. Results indicated that the ANN model provided superior prediction performance compared to other models. [ABSTRACT FROM AUTHOR]

This study aims to investigate the variation of P-wave velocity as a function of water saturation. In addition, by using a regression analysis, a predictability of saturated P-wave velocity from dry P-wave velocity and rock's hardness has been examined. In order to perform this study, one hundred cylindrical rock core samples, fifty samples each obtained from Ruweished in northeastern Jordan and from Ajloun in northwestern Jordan, have been extracted and prepared with a height of 20 cm and a diameter of 10 cm. P-wave velocity has been measured five times in each sample in dry and saturated states and the average value has been taken. The results indicate that the water saturation leads to an increase of the P-wave velocity, where the increase in more porous samples is less than what has been found in slightly porous samples. Moreover, the saturated P-wave velocity can be predicted through strong statistical models, which link the saturated P-wave velocity with dry P-wave velocity and hardness. [ABSTRACT FROM AUTHOR]