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EN
Lightweight aggregates, used to produce cavity blocks in the construction sector, vary according to their technical properties and thus, technical analyses should be performed on lightweight aggregate specimens. Lightweight aggregates, like pumice, are widely employed for the production of construction elements, used as light masonry units. In literature there are studies related to applications of various lightweight aggregates, such as volcanic slag, ignimbrite and expanded clay, in addition to pumice, to produce porous cavity blocks. This study investigates the usability of perlitic pumice formations, present around Menderes, İzmir (Turkey), as lightweight aggregate. Many experiments were conducted to investigate this possibility and to determine the optimum mixing ratios of aggregate. Based on the results, for 10% of cement by volume, the optimum aggregate mixing ratio was 40% 0-4 mm and 60% 4-8 mm.
EN
Artificial neural network is generally information processing system and a computer program that imitates human brain neural network system. By entering the information from outside, artificial neural network can be trained on examples related to a problem, so that modeling of the problem is provided. In this study, compressive strength, Poisson ratio of the lightweight concrete specimens, which have different natural lightweight aggregates, were modeled with artificial neural network. The data which were provided by artificial neural network model were compared with the data obtained from experimental study and a good agreement was determined between the results.
EN
In this study, some physical and mechanical performances of artificial aggregated lightweight concretes were compared. Special empirical models were developed to estimate the elasticity modulus of lightweight aggregate concrete (LWAC). Five different natural aggregates and one artificial lightweight aggregate material were used throughout the research. Mixture proportions were kept as constant values in all concrete mixtures. All mixtures were cast into cubic, prismatic and cylindrical concrete standard moulds and they were cured at the same curing conditions. A series of physical and mechanical properties, such as density, compressive strength and elasticity modulus for LWAC were experimentally determined. According to the research findings a few empirical models were statistically developed for estimating the elasticity modulus and Poisson's ratio of LWAC and a new diagram practically to be used for estimating the Poisson's ratio of LWAC was also proposed.
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