Gürkan Özden

Estimating compaction parameters of fine- and coarse-grained soils by means of artificial neural networks

This paper presents artificial neural network (ANN) prediction models for estimating the compaction parameters of both coarse- and fine-grained soils. A total number of 200 soil mixtures were prepared and compacted at standard Proctor energy. The compaction parameters were predicted by means of ANN models using different input data sets. The ANN prediction models were developed to find out which of the index properties correlate well with compaction parameters. In this respect, the transition fine content ratio (TFR) was defined as a new input parameter in addition to traditional soil index parameters (i.e. liquid limit, plastic limit, passing No. 4 sieve and passing No. 200 sieve). Highly nonlinear nature of the compaction data dictated development of two separate ANN models for maximum dry unit weight (γdmax) and optimum water content (ωopt). It was found that generalization capability and prediction accuracy of ANN models could be further enhanced by sub-clustered data division techniques.

Determination of Cylindrical Soil Specimen Dimensions by Imaging with Application to Volume Change of Bentonite-Sand Mixtures

Volumetric shrinkage of compacted bentonite and sand mixtures has been continuously monitored at small strain levels (i.e., <5 %) using a digital image processing technique. A special digital measurement setup and a computer algorithm have been developed in order to identify volume of the drying specimens. Volume change of three compacted bentonite-sand mixtures at different initial moisture contents were recorded during drying by means of vernier caliper and digital measurements. Continuous monitoring of the volumetric shrinkage of specimens using digital images proved that digital measurement and data reduction methodology developed herein is capable of determining the shrinkage amount with desired accuracy. It is shown in the study that consistent volumetric shrinkage strain readings can be taken using this cost effective, nondestructive, and operator independent measurement setup, which may have become the preferred shrinkage measurement methodology in soil mechanics laboratory practice with some added features.

Numerical simulations of landslide-stabilizing piles: a remediation project in Söke, Turkey

A catastrophic landslide following a rainy season occurred in the backyard of a school building in Söke, Turkey. The landslide caused property damage and adversely affected the present forest cover. Immediately after the landslide, double-row stabilizing piles were designed and constructed based on the findings of two-dimensional (2D) finite element (FE) analyses to take an urgent precaution. To remedy the problem, pile displacements were monitored using inclinometers, and it was observed that the measured displacements were greater than the values calculated in the design stage. Accordingly, two different three-dimensional (3D) numerical FE models were used in tandem with the inclinometer data to determine the load transfer mechanism. In the first model, numerical analyses were made to predict the pile displacements, and while the model predicted successfully the displacement of the piles constructed in the middle with reasonable accuracy, it failed for the corner piles. In the second model, the soil load transfer between piles was determined considering the sliding mass geometry, the soil arching mechanism and the group interaction between adjacent piles. The results of the second model revealed that the middle piles with large displacements transferred their loads to the corner piles with smaller displacements. The generated soil loads, perpendicular to the sliding direction, restricted pile deformations and piles with less displacement were subjected to greater loads due to the bowl-shaped landslide. A good agreement between the computed pile displacements and inclinometer data indicates that the existing soil pressure theories should be improved considering the position of the pile in the sliding mass, the depth and deformation modulus of stationary soil, the relative movement between the soil and piles and the relative movement of adjacent piles.

Visual and Quantitative Investigation of the Settlement Behavior of an Embankment Using Aerial Images Under Large-Size Field Loading

In this study, the settlement behavior of the embankment due to the surcharge loading have been visually and quantitatively investigated. The spatial variation of settlements of an oversized embankment have been monitored using aerial images taken at intervals. In order to achieve the deformations due to the surcharge loading in the field, two topographical three-dimensional models (before and after surcharge loading), derived from aerial images and ground control points, have been generated and compared. The aerial images were acquired by an unmanned aerial vehicle with autonomous flight capabilities. The topographies were compared by generating two cloud point models. The deformations, determined from the comparison of two cloud points, were visualized by assigning an intensity value, which was calculated based on the three-dimensional variations of each data point. The surficial settlement profiles nearby the surcharge load have been computed. It has been concluded that centimeter level accuracy on surficial settlement has been achieved by low altitude aerial images, although the illumination condition of the area has an influence on the measurements.