Compressive strength evaluation of concrete confined with spiral stirrups by using adaptive neuro-fuzzy inference system (ANFIS)

被引:9
|
作者
Chang, Wei [3 ]
Zheng, Wenzhong [1 ,2 ,3 ]
机构
[1] Harbin Inst Technol, Key Lab Struct Dynam Behav & Control, Minist Educ, Harbin 150090, Peoples R China
[2] Harbin Inst Technol, Key Lab Smart Prevent & Mitigat Civil Engn Disast, Minist Ind & Informat Technol, Harbin 150090, Peoples R China
[3] Harbin Inst Technol, Sch Civil Engn, 202 Haihe Rd, Harbin 150090, Peoples R China
基金
美国国家科学基金会;
关键词
Adaptive neural-fuzzy inference system (ANFIS); Compressive strength; Confined concrete; Spiral stirrups; Prediction model; STRESS-STRAIN BEHAVIOR; COLUMNS; REINFORCEMENT; NETWORK; MODEL;
D O I
10.1007/s00500-022-07001-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The compressive strength of concrete confined with spiral stirrups was an important parameter to evaluate the load-bearing capacity of concrete columns. The confinement provided by spiral stirrups let concrete under the triaxial compression state and improved the compressive strength of concrete. However, the relationships between concrete and stirrups were complex and the existing prediction models for evaluating the compressive strength of confined concrete were various. In this paper, an adaptive neural-fuzzy inference system (ANFIS) model was developed to evaluate the compressive strength of concrete confined with stirrups. A set of 231 experimental results of concrete confined with spiral stirrups were collected from the previous studies to establish a reliable database. The investigated parameters included the aspect ratio of specimens, the diameter, spacing, yield strength, and volumetric ratio of stirrups, the ratio of longitudinal reinforcement, and the compressive strength of concrete. The results showed that the ANFIS model predicted the compressive strength of confined concrete accurately. By comparing with existing models, the proposed ANFIS model had high applicable and reliability. The effects of the investigated parameters on the compressive strength of concrete were analyzed based on the proposed ANFIS model.
引用
收藏
页码:11873 / 11889
页数:17
相关论文
共 50 条
  • [1] Compressive strength evaluation of concrete confined with spiral stirrups by using adaptive neuro-fuzzy inference system (ANFIS)
    Wei Chang
    Wenzhong Zheng
    [J]. Soft Computing, 2022, 26 : 11873 - 11889
  • [2] Application of Adaptive Neuro-Fuzzy Inference System for Evaluating Compressive Strength of Concrete
    Sinha, Deepak Kumar
    Satavalekar, Rupali
    Kasilingam, Senthil
    [J]. INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, 2021, 21 (02) : 176 - 188
  • [3] LANDSLIDE SUSCEPTIBILITY MAPPING BY USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)
    Choi, J.
    Lee, Y. K.
    Lee, M. J.
    Kim, K.
    Park, Y.
    Kim, S.
    Goo, S.
    Cho, M.
    Sim, J.
    Won, J. S.
    [J]. 2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1989 - 1992
  • [4] Sensitivity and robustness analysis of adaptive neuro-fuzzy inference system (ANFIS) for shear strength prediction of stud connectors in concrete
    Yosri, Ahmed M.
    Farouk, A. I. B.
    Haruna, S. I.
    Deifalla, Ahmed Farouk
    Shaaban, Walaa Mahmoud
    [J]. CASE STUDIES IN CONSTRUCTION MATERIALS, 2023, 18
  • [5] Application of the adaptive neuro-fuzzy inference system model in predicting the concrete compressive strength from the silverschmidt hammer
    [J]. Kuo, W.-T. (wtkuo@kuas.edu.tw), 1600, National Taiwan University of Science and Technology (28):
  • [6] Prediction of Compressive Strength of Self compacting Concrete with Flyash and Rice Husk Ash using Adaptive Neuro-fuzzy Inference System
    Pathak, S. S.
    Sharma, Sanjay
    Sood, Hemant
    Khitoliya, R. K.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2012, 3 (10) : 119 - 122
  • [7] Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study
    Palanivelu, Sangeetha
    Marayanagaraj, Shanmugapriya
    [J]. REVISTA ITECKNE, 2023, 19 (02):
  • [8] Yarn Strength Modelling Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP)
    Fallahpour, A. R.
    Moghassem, A. R.
    [J]. JOURNAL OF ENGINEERED FIBERS AND FABRICS, 2013, 8 (04): : 6 - 18
  • [9] Estimation of subsurface strata of earth using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Y. Srinivas
    A. Stanley Raj
    D. Hudson Oliver
    D. Muthuraj
    N. Chandrasekar
    [J]. Acta Geodaetica et Geophysica Hungarica, 2012, 47 : 78 - 89
  • [10] Optimization of Photosynthetic Rate Parameters using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Valenzuela, Ira C.
    Baldovino, Renann G.
    Bandala, Argel A.
    Dadios, Elmer P.
    [J]. 2017 INTERNATIONAL CONFERENCE ON COMPUTER AND APPLICATIONS (ICCA), 2017, : 129 - 134