Assessment of flexural and splitting strength of steel fiber reinforced concrete using automated neural network search

被引：6

作者：

Zhang, Zhenhao ^{[1
]}

Paul, Suvash C. ^{[2
]}

Panda, Biranchi ^{[3
]}

Huang, Yuhao ^{[4
]}

Garg, Ankit ^{[5
]}

Zhang, Yi ^{[6
]}

Garg, Akhil ^{[4
]}

Zhang, Wengang ^{[7
]}

机构：

[1] Changsha Univ Sci & Technol, Sch Civil Engn, 960 2nd Sect Wanjiali South Rd, Changsha, Hunan, Peoples R China

[2] Monash Univ Malaysia, Sch Engn, Civil Engn, Jalan Lagoon Selatan, Bandar Sunway 47500, Selangor Darul, Malaysia

[3] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore Ctr 3D Printing, 50 Nanyang Ave, Singapore, Singapore

[4] Shantou Univ, Minist Educ, Intelligent Mfg Key Lab, 243 Daxue Rd, Shantou City, Guangdong, Peoples R China

[5] Shantou Univ, Dept Civil & Environm Engn, 243 Daxue Rd, Shantou City, Guangdong, Peoples R China

[6] Leibniz Univ Hannover, 1 Welfengarten, Hannover, Germany

[7] Shandong Univ Technol, Sch Civil & Architectural Engn, 266 Xincun West Rd, Zibo, Shandong, Peoples R China

来源：

ADVANCES IN CONCRETE CONSTRUCTION | 2020年 / 10卷 / 01期

关键词：

fiber aspect ratio; fiber content; compressive strength; flexural strength; splitting strength; FRC; ANS; COMPRESSIVE STRENGTH; SHEAR BEHAVIOR; ASPECT RATIO; PREDICTION; PERFORMANCE; DURABILITY;

D O I：

10.12989/acc.2020.10.1.081

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Flexural and splitting strength behavior of conventional concrete can significantly be improved by incorporating the fibers in it. A significant number of research studies have been conducted on various types of fibers and their influence on the tensile capacity of concrete. However, as an important property, tensile capacity of fiber reinforced concrete (FRC) is not modelled properly. Therefore, this paper intends to formulate a model based on experiments that show the relationship between the fiber properties such as the aspect ratio (length/diameter), fiber content, compressive strength, flexural strength and splitting strength of FRC. For the purpose of modeling, various FRC mixes only with steel fiber are adopted from the existing research papers. Automated neural network search (ANS) is then developed and used to investigate the effect of input parameters such as fiber content, aspect ratio and compressive strength to the output parameters of flexural and splitting strength of FRC. It is found that the ANS model can be used to predict the flexural and splitting strength of FRC in a sensible precision.

引用

页码：81 / 92

页数：12

共 47 条

[1]

Adeli H., 1989, Microcomputers in Civil Engineering, V4, P247

[2] Neural networks in civil engineering: 1989-2000 [J].