Okan Önal

Artificial neural network application on microstructure-compressive strength relationship of cement mortar

Artificial neural network analysis was performed to establish a relationship between microstructural characteristics and compressive strength values of cement mortar in this study. Pore properties such as pore area ratio, total pore length, total dendrite length and average roundness, and paste properties such as hydrated part area and unhydrated part area ratios were approached as microstructural characteristics obtained by digital image analysis. These microstructural quantities were correlated with compressive strength values of cement mortar incorporating with the chemical admixtures by different dosages, which resulted as several microstructural characteristics. Artificial neural network (ANN) analysis indicated that by using ANN as non-linear statistical data modeling tool, a strong correlation between the microstructural properties of cement mortar and compressive strengths can be established.

Short note: A Visual Basic program for analyzing oedometer test results and evaluating intergranular void ratio

A visual basic program (POCI) is proposed and explained in order to analyze oedometer test results. Oedometer test results have vital importance from geotechnical point of view, since settlement requirements usually control the design of foundations. The software POCI is developed in order perform the necessary calculations for convential oedometer test. The change of global void ratio and stress-strain characteristics can be observed both numerically and graphically. It enables the users to calculate some parameters such as coefficient of consolidation, compression index, recompression index, and preconsolidation pressure depending on the type and stress history of the soil. Moreover, it adopts the concept of intergranular void ratio which may be important especially in the compression behavior of sandy soils. POCI shows the variation of intergranular void ratio and also enables the users to calculate granular compression index.

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.

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.