期刊
ENGINEERING STRUCTURES
卷 26, 期 7, 页码 917-926出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2004.02.010
关键词
reinforced concrete; shear strength; high-strength concrete; structural design; size effect; artificial neural networks
Over the last decades, a great number of experimental campaigns on the behavior of high- and normal-strength reinforced concrete beams without shear reinforcement failing in shear have been published, and some excellent rational models to explain the physical phenomena have been developed. However, their implementation into design codes still requires considerable simplification. With the aim of taking into account this large amount of information available and to re-evaluate the current codes of practice extensive research was performed. An artificial neural network was developed to predict the shear strength of reinforced beams and, based on its results, a parametric study was carried out to determine the influence of each parameter affecting the failure shear strength of beams without web reinforcement. Finally, new simple expressions are proposed for the design of high-strength and normal-strength reinforced concrete beams without shear reinforcement. The new expressions correlate with the empirical tests better than any current code of practice does. (C) 2004 Elsevier Ltd. All rights reserved.
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