This paper represents a comparative study in which Gene Expression Programming (GEP), Group Method of Data Handling (GMDH), and multiple linear regressions (MLR) were utilized to derive new equations for the prediction of time-dependent bearing capacity of pile foundations driven in cohesive soil, technically called pile set-up. This term means that many piles which are installed in cohesive soil experience a noticeable increase in bearing capacity after a specific time. Results of researches indicate that side resistance encounters more increase than toe resistance. The main reason leading to pile setup in saturated soil has been found to be the dissipation of excess pore water pressure generated in the process of pile installation, while in unsaturated conditions aging is the major justification. In this study, a comprehensive dataset containing information about 169 test piles was obtained from literature reviews used to develop the models. to prepare the data for further developments using intelligent algorithms, Data mining techniques were performed as a fundamental stage of the study. To verify the models, the data were randomly divided into training and testing datasets. The most striking difference between this study and the previous researches is that the dataset used in this study includes different piles driven in soil with varied geotechnical characterization; therefore, the proposed equations are more generalizable. According to the evaluation criteria, GEP was found to be the most effective method to predict set-up among the other approaches developed earlier for the pertinent research.

Turkey is one of the most important earthquake regions in Europe. This region has been exposed to many earthquakes of different magnitudes from past to present. It is of great importance to determine the dynamic properties of the soils for structures to be built in earthquake zones. In order to minimize the damages that may occur, the behavior of the soils under repeated loads should be known and taken into consideration in the design. In this study, 4 different point borings were taken near active fault lines in the North Anatolian fault zone (NAFZ). In order to determine the dynamic parameters of soils, both dynamic triaxial (TRX) and resonant column (RC) tests were carried out on undisturbed samples at every 5 m. As a result of the experiments, V_s and G_max values were obtained from the field and differences were determined. The dynamic behavior of the soil was examined at varying depths with the comparison of reference models in the literature and compatible results were obtained. Finally, the behavior at the transition region is highlighted. As a result, three shear modulus and dumping ratio models have been proposed for clay soils to be used in different soil conditions.

In this study, the compressive strength of cement stabilized soil was predicted using the electrical resistivity measurement. The effects of the water to cement (w/c) ratio and recovered Carbon Black (rCB) contents were examined. A series of electrical resistivity and compressive strength tests were conducted on two types of stabilized soil after 28 days of curing. Multiple nonlinear regression (MNLR) analysis was used to evaluate the relationship between the compressive strength and the electrical resistivity in terms of the rCB, C_u (uniformity coefficient), and w/c ratio. The results showed that the w/c ratio and C_u have a strong influence on the compressive strength and electrical resistivity of the cement stabilized soil compared to the rCB content. The use of a small amount of rCB led to a decrease in the void space in the specimen and was attributed to the increase strength and decrease electrical resistivity. A high w/c ratio also induced a low electrical resistivity and compressive strength, whereas 3% rCB in the cemented soil provided the optimum strength for all w/c ratios. Finally, a prediction equation for the compressive strength using the electrical resistivity measurement was suggested based on its reliability, time effectiveness, non-destructiveness, and cost-effectiveness.

This article investigates the effect of viscoelastic foundations on the waves' dispersion in a beam made of ceramic-metal functionally graded material (FGM) with microstructural defects. The beam is considered to be shear deformable, and a simple three-unknown sinusoidal integral higher-order shear deformation beam theory is applied to represent the beam's displacement field. Novel to this study is the investigation of the impact of viscosity damping on imperfect FG beams, utilizing a few-unknowns theory. The stresses and strains are obtained using the two-dimensional elasticity relations of FGM, neglecting the normal strain in the beam's depth direction. The variational operation is employed to define the dispersion relations of the FGM beam. The influences of the material gradation exponent, the beam's thickness, the porosity, and visco-Pasternak foundation parameters are represented. Results showed that phase velocity was inversely proportional to the damping and porosity of the beams. Additionally, the foundation viscous damping had a stronger influence on wave velocity when porosity volume fractions were low.

Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σ_c) and tensile strength (σ_t) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R²), adjusted R² (Adj R²), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R² and Adj R² values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

Monitoring contaminants in waste landfills on a seabed is important because the leachate affects the marine ecosystem and facility stability. The objective of this study is to optimize a time-domain reflectometry (TDR) probe using different coating materials and several electrodes to estimate contaminants in saline soil. Copper concentrations ranging from 0 mg/L to 10 mg/L were mixed in 3% salinity water to simulate contaminants in the ocean environment. Epoxy, top-coat, and varnish were used as coating materials, and two to seven electrodes were prepared to vary the number and arrangement of the electrodes. Test results showed that the varnish stably captured the increase in copper concentration, while the other coating materials became insensitive or caused leakage current. In addition, a TDR probe with more electrodes exhibited stable and distinct electromagnetic signals. Thus, the TDR probe with seven electrodes coated with varnish was effectively used to estimate contaminants in saline soil.

Adopting cohesive soil as geocell-pocket infill materials is not fully accepted by researchers in the field of road engineering. The cohesion that may inhibit the lateral limitation of geocells is a common vital idea that exists within every researcher. However, the influence of infill materials' cohesion on geocell-reinforced performance is still not thoroughly determined. The mechanism behind this still needs to be studied in depth. This study initially discussed the relationship between subgrade bearing capacity, geocells' contribution to reinforced performance, and infill materials' cohesion (IMC). A law was proposed that adopting the soil with high cohesion as infill materials benefited the subgrade bearing capacity, but this was attributed to the superior mechanical properties of infill materials rather than geocells' contribution. Moreover, the vertical and lateral deformation of subgrade, coupling shear stress and confining stress of geocells, and deformation of geocells were deeply studied to analyze the mechanism that high cohesion can inhibit the geocells' contribution. The results indicate that the infill materials with high cohesion result in the total displacement of the subgrade toward to deeper depth, not the lateral direction. These responses decrease the vertical coupling shear stress, confining stress, and normal displacement of geocell walls, which weaken the lateral limitation of geocells.

Accurately measuring the hydraulic conductivity of dredged slurry (HCODS) is a difficult task and usually requires highly developed experimental techniques. To resolve such problem, this paper presents a novel laboratory method, where a double drainage sedimentation test (DDST) is proposed to generate a downward seepage after the end of primary consolidation (EOP). Based on the established stress equilibrium equations, it is figured out that the determination of local hydraulic gradients requires the effective stress distribution to be measured. Accordingly, an additional single drainage sedimentation test (SDST) with the same initial water content is performed in the novel laboratory method, which can be utilized to establish the relationship between effective stress and water content for investigated slurry. Thus, HCODS can be determined via a pair of SDST and DDST, with the water contents after the EOP measured. The corresponding calculation procedure is given in details. With a simply-designed settling column, the hydraulic conductivity tests were performed on three types of dredged slurry. The results demonstrated the effectiveness of the novel laboratory method in measuring HCODS.