Test results of six half-scale reinforced concrete flat plates connections with an opening in the vicinity of the column are reported. The test specimens represent a portion of a slab bounded by the lines of contraflexure around the column. The tests were designed to study the effect of openings on the punching shear behavior of the slab-column connections. The test parameters were the location and the size of the openings. One specimen had no opening and the remaining five had various arrangements of openings around the column. All specimens were cast with normal density concrete of approximately 30 MPa compressive strength. The openings in the specimens were square, with the sides parallel to the sides of the column. Three sizes of ope

An experimental investigation based on thirty three simple pullout cylinder specimens was conducted to study the bond-slip trend between concrete and steel reinforcement. Plain and deformed steel reinforcement bars were used in this investigation. The effect of bar diameter, concrete compressive strength and development length on bond-slip relation was detected. The results showed that the bond strength increases with increasing of compressive strength and with decreasing of bar diameter and development length. A nonlinear regression analysis for the experimental results yields in a mathematical correlation to predict the bond strength as a function of concrete compressive strength, reinforcing bar diameter and its yield stress. The minimum

The massive growth of the automotive industry and the development of vehicles use lead to produce a huge amount of waste tire rubber. Rubber tires are non-biodegradable, resulting in environmental problems such as fire risks. In this search, the flexural behavior of steel fiber reinforced self-compacting concrete (SFRSCC) beams containing different percentages and sizes of waste tire rubbers were studied and compared them with the flexural behavior of SCC and SFRSCC. Micro steel fiber (straight type) with aspect ratio 65 was used in mixes. The replacement of coarse and fine aggregate was 20% and 10% with chip and crumb rubber. Also, the replacement of limestone dust and silica fume was 50%, 25%, and 12% with ground rubbe

The integration of nanomaterials in asphalt modification has emerged as a promising approach to enhance the performance of asphalt pavements, particularly under high-temperature conditions. Nanomaterials, due to their unique properties such as high surface area, exceptional mechanical strength, and thermal stability, offer significant improvements in the rheological properties, durability, and resistance to deformation of asphalt binders. This research reviewed the application of various nanomaterials, including nano silica, nano alumina, nano titanium, nano zinc, and carbon nanotubes in asphalt modification. The incorporation of these nanomaterials into asphalt mixtures has shown potential to increase the stiffness and high-tempera

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo