Papers by Author: Dariusz Alterman

Abstract: The relationship between various steel strip geometries and the bonding energy through pull-out tests of aerated concrete specimens is investigated. Prismatic concrete samples containing embedded steel strips with and without holes of differing sizes and quantities were analysed. Improvements of the bonding energy through pull-out tests by 70% are possible by increasing the number of holes on a steel strip from one to four while maintaining a constant surface area. The energy increased even up to 130% for strips containing holes compared to strips without. In addition, the tests have been carried out with a novel easy to assemble set-up containing a freely adjustable ball-joint and a plate with embedded bolts to avoid eccentricity during pull-out tests.

Abstract: This paper is dedicated to an impregnation technique for crack identification of uniaxial tensile behaviour of concrete samples. A method for crack identification in concrete after uniaxial tension tests was adopted for the observation of differences between various experiments which were conducted with and without the elimination of secondary flexure. During the procedure an epoxy resin containing fluorescent dye was infused into concrete samples by vacuum to expose cracks and defects. After impregnation the samples were sawed from the prism and pictures taken under ultraviolet light.

Abstract: Knowledge of the tension softening process of concrete is essential to understand fracture mechanism, further to analyze fracture behaviour, and further to evaluate properties of concrete. For the last eight years, many different tests on uniaxial tension with elimination of secondary flexure were performed in Tohoku Institute of Technology. The paper is dedicated to predict tension softening curve of concrete by using artificial neural networks (ANNs) based on experimental data of five different mixtures of concrete (including High Performance Concrete). It is an advantage to predict a proper tension softening curve without performing uniaxial tension tests. Several artificial neural networks with different architectures (with various hidden neurons and layers) were studied using software - Statistica Neural Network. In order to evaluate the prediction accuracy, tension softening curve and other fracture parameters were predicted for each mix from the other four mixes and compared with the omitted data of the relevant mix. High accuracy was obtained in the all predicted tension softening curves and the fracture parameters were also well predicted.

Abstract: In order to investigate the size effect of concrete, four sizes of rectangular prisms were tested in uniaxial tension. The cross sections of the prisms were 50x100mm, 100x100mm, 200x100mm and 400x100mm. The concrete was an ordinary one with the compressive strength of 34 MPa and the maximum aggregate size of 20mm. Notches were applied on four side faces and secondary flexure was completely eliminated during the test in order to obtain the exact nominal tensile strength. The size effect was analyzed by four factors, namely tensile strength, fracture energy, critical crack opening displacement and tension softening curves. Clear size dependence was observed in critical crack opening displacement and initial convexity of tension softening curves, and a slight size dependence was observed in tensile strength. On the other hand, size effect was unclear in fracture energy and other part of tension softening curves because of their scatters.