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RETRACTED ARTICLE: Analysis of influential factors for predicting the shear strength of a V-shaped angle shear connector in composite beams using an adaptive neuro-fuzzy technique

Author

Listed:
  • I. Mansouri

    (Birjand University of Technology)

  • M. Shariati

    (University of Malaya)

  • M. Safa

    (University of Malaya)

  • Z. Ibrahim

    (University of Malaya)

  • M. M. Tahir

    (UTM)

  • D. Petković

    (University of Niš, Pedagogical Faculty in Vranje)

Abstract

The V-shaped angle shear connector is recognized as to expand certain mechanical properties to the shear connectors, contains adequate ductility, elevate resistance, power degradation resistance under cyclic charging, and high shear transmission, more economical than other shear connectors, for instance, the L-shaped and C-shaped shear connectors. The performance of this shear connector had been investigated by previous researchers (Shariati et al. in Mater Struct 49(9):1–18, 2015), but the strength prediction was not clearly explained. In this investigation, the shear strength prediction of this connector was analyzed based on several factors. The ultimate purpose was to investigate the variations of different factors that were affecting the shear strength of this connector. To achieve this aim, the data (concrete compression strength, thickness, length, height, slope of inclination, and shear strength) were collected from the parametric studies using finite element analysis results for this purpose were input using the ANFIS method (neuro-fuzzy inference system). The finite element analysis results were verified by experimental test results. All variables from the predominant factors that were affected the shear strength of the shear connector (V-shaped angle) were also selected by using the ANFIS process. The results exhibited that the proposed shear connector (V-shaped angle) contained the potentiality to be used practically after several improvements. One option might be the improvement of the testing process for different predictive models with more input variables that will improve the predictive power of the created models.

Suggested Citation

  • I. Mansouri & M. Shariati & M. Safa & Z. Ibrahim & M. M. Tahir & D. Petković, 2019. "RETRACTED ARTICLE: Analysis of influential factors for predicting the shear strength of a V-shaped angle shear connector in composite beams using an adaptive neuro-fuzzy technique," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1247-1257, March.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1306-6
    DOI: 10.1007/s10845-017-1306-6
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    Citations

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    Cited by:

    1. Biljana Petković & Yousef Zandi & Alireza Sadighi Agdas & Ivica Nikolić & Nebojša Denić & Nenad Kojić & Abdellatif Selmi & Alibek Issakhov & Slaviša Milošević & Afrasyab Khan, 2022. "Adaptive neuro fuzzy evaluation of energy and non‐energy material productivity impact on sustainable development based on circular economy and gross domestic product," Business Strategy and the Environment, Wiley Blackwell, vol. 31(1), pages 129-144, January.
    2. Safa, Maryam & Sari, Puteri Azura & Shariati, Mahdi & Suhatril, Meldi & Trung, Nguyen Thoi & Wakil, Karzan & Khorami, Majid, 2020. "Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    3. Ali Aldrees, 2022. "Using peak discharge estimation methods in urban flood modeling for WADI AL-AQIQ," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3461-3484, March.
    4. Vujović, Vuk & Denić, Nebojša & Stevanović, Vesna & Stevanović, Mališa & Stojanović, Jelena & Cao, Yan & Alhammadi, Yasir & Jermsittiparsert, Kittisak & Van Le, Hiep & Wakil, Karzan & Radojkovic, Ivan, 2020. "Project planning and risk management as a success factor for IT projects in agricultural schools in Serbia," Technology in Society, Elsevier, vol. 63(C).
    5. Yan Cao & Towhid Pourrostam & Yousef Zandi & Nebojša Denić & Bogdan Ćirković & Alireza Sadighi Agdas & Abdellatif Selmi & Vuk Vujović & Kittisak Jermsittiparsert & Momir Milic, 2021. "RETRACTED ARTICLE: Analyzing the energy performance of buildings by neuro-fuzzy logic based on different factors," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 17349-17373, December.

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