Multi-fractal scaling law for split strength of concrete cubes

Abstract

Experiments on concrete members indicate that the nominal strength of a specimen decreases with increasing specimen size for the same specimen geometry. This phenomenon is known as the size effect in the fracture mechanics of plain and reinforced concrete. Although nominal strength is also highly affected by the width of the distributed load in split-tension cylinder and cube specimens, this effect can be negligible within the practical range of the load-distributed width in diagonal cubes. However, the number of reported theoretical and experimental studies on cube and especially diagonal cube split-tension specimens is much more limited than those on cylindrical specimens. Therefore, in this study, six series of cube and diagonal cube specimens, with three different sizes and with two different maximum aggregate sizes (4 mm and 16 mm) but similar geometries, were tested under different load-distributed widths. The peak loads obtained from the test results were analysed using the multi-fractal scaling law. Subsequently, two prediction formulae are proposed for the design of torsional concrete/reinforced concrete members.

Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques

“…For realizing the best artificial intelligence (AI) model to meet this goal, this study provides and compares five well-known models that are widely used by researchers [4][5][6][7][8]. Similar to other research in the fields of science and technology, AI techniques have widespread application in order to put forward reasonable evaluation in many engineering problems [9][10][11][12][13][14][15][16][17] of the energy consumption in buildings. In numerous types of artificial intelligence-based solutions, artificial neural network (ANN) is known as a recognized method that is largely employed for many prediction-based examples [18][19][20][21][22].…”