Linear genetic programming for shear strength prediction of reinforced concrete beams without stirrups

被引:58
|
作者
Gandomi, Amir H. [1 ]
Mohammadzadeh, Danial S. [2 ]
Luis Perez-Ordonez, Juan [3 ]
Alavi, Amir H. [4 ]
机构
[1] Univ Akron, Dept Civil Engn, Akron, OH 44325 USA
[2] Ferdowsi Univ Mashhad, Dept Civil Engn, Mashhad, Iran
[3] Univ A Coruna, Sch Bldg Engn & Tech Architecture, La Coruna, Spain
[4] Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
关键词
Shear strength; Reinforced concrete beam; Linear genetic programming; Design equation; RC DEEP BEAMS; WEB REINFORCEMENT; NEURAL-NETWORKS; FLOW DISCHARGE; CAPACITY; FORMULATION; EQUATIONS; MODEL; SIZE;
D O I
10.1016/j.asoc.2014.02.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new design equation is proposed for the prediction of shear strength of reinforced concrete (RC) beams without stirrups using an innovative linear genetic programming methodology. The shear strength was formulated in terms of several effective parameters such as shear span to depth ratio, concrete cylinder strength at date of testing, amount of longitudinal reinforcement, lever arm, and maximum specified size of coarse aggregate. A comprehensive database containing 1938 experimental test results for the RC beams was gathered from the literature to develop the model. The performance and validity of the model were further tested using several criteria. An efficient strategy was considered to guarantee the generalization of the proposed design equation. For more verification, sensitivity and parametric analysis were conducted. The results indicate that the derived model is an effective tool for the estimation of the shear capacity of members without stirrups (R = 0.921). The prediction performance of the proposed model was found to be better than that of several existing buildings codes. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:112 / 120
页数:9
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