Knowledge-based prediction of shear strength of concrete beams without shear reinforcement

被引:39
作者
Jung, Sungmoon [2 ]
Kim, Kang Su [1 ]
机构
[1] Univ Seoul, Sch Architecture & Architectural Engn, Seoul 130743, South Korea
[2] Belcan Engn Grp Inc, Caterpillar Champaign Simulat Ctr, Champaign, IL 61820 USA
关键词
reinforced concrete beam; shear strength; artificial neural networks; shear database; shear mechanism; shear behavior;
D O I
10.1016/j.engstruct.2007.10.008
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Structural engineers heavily rely on computer software to perform structural analysis, and they increasingly computerize design procedures to avoid manual repetitions. To benefit fully from the computerization, it is necessary to utilize the domain knowledge contained in a database such as a concrete shear database used in this paper. A knowledge-based system uses a database of knowledge in combination with its retrieval mechanism such as artificial neural networks (ANN) to imitate problem-solving strategy of human. This paper presents an application of the knowledge-based approach, utilizing the shear database and retrieval of information using ANN. The database can be used more extensively than regression of shear strength that had been reported in other literature. As a demonstration, two models are developed and compared with design equations. The first model estimates shear strength, and the second model systematically provides conservative estimation. Although both models already outperform all existing design equations, they can be easily revised for further improvement whenever additional experimental data sets become available. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1515 / 1525
页数:11
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