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research-article

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

Published: 01 November 2022 Publication History

Abstract

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.

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Cited By

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  • (2024)Failure modes determination and load-bearing capacity evaluation of concrete columns under seismic loads by ANNsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-024-09741-928:13-14(8361-8377)Online publication date: 1-Jul-2024
  • (2024)Peak stress and peak strain evaluation of concrete columns confined with lateral ties under axial compression by artificial neural networksSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09357-528:6(5591-5608)Online publication date: 1-Mar-2024
  • (2024)Multi-objective optimization of MQL system parameters for the roller burnishing operation for energy saving, product quality and air pollutionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09165-x28:2(1229-1254)Online publication date: 1-Jan-2024

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            Published In

            cover image Soft Computing - A Fusion of Foundations, Methodologies and Applications
            Soft Computing - A Fusion of Foundations, Methodologies and Applications  Volume 26, Issue 21
            Nov 2022
            806 pages
            ISSN:1432-7643
            EISSN:1433-7479
            Issue’s Table of Contents

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            Springer-Verlag

            Berlin, Heidelberg

            Publication History

            Published: 01 November 2022
            Accepted: 20 February 2022

            Author Tags

            1. Adaptive neural-fuzzy inference system (ANFIS)
            2. Compressive strength
            3. Confined concrete
            4. Spiral stirrups
            5. Prediction model

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            View all
            • (2024)Failure modes determination and load-bearing capacity evaluation of concrete columns under seismic loads by ANNsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-024-09741-928:13-14(8361-8377)Online publication date: 1-Jul-2024
            • (2024)Peak stress and peak strain evaluation of concrete columns confined with lateral ties under axial compression by artificial neural networksSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09357-528:6(5591-5608)Online publication date: 1-Mar-2024
            • (2024)Multi-objective optimization of MQL system parameters for the roller burnishing operation for energy saving, product quality and air pollutionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09165-x28:2(1229-1254)Online publication date: 1-Jan-2024
            • (2024)Estimation of compressive strength of concrete cement using random vector functional link networks: a case studySoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08885-428:15-16(8641-8656)Online publication date: 1-Aug-2024

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