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Soft Computing-Based Models for Estimating the Ultimate Bearing Capacity of an Annular Footing on Hoek–Brown Material

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Abstract

The finite element limit analysis solution presented in this paper offers novel approaches for estimating the ultimate bearing capacity of annular foundations on Hoek–Brown criterion. The study examines the effects of five of dimensionless parameters, including the ratio of internal to external radii, the depth ratio, the adhesive factor, the yield parameter, and the geological strength index, on the findings of bearing capacity as well as the processes of collapse. Furthermore, one of the soft-computing regression methodologies, the multi-objective evolutionary polynomial regression analysis (MOGA-EPR) method, is utilized along with the requirement of the FELA outcomes as input data. This paper provides accurate limit-state predictions for annular footings on diverse rock masses using the MOGA-EPR model. By using the MOGA-EPR approach, the findings are highly precise and trustworthy, empowering designers to choose the best annular foundation design for various Hoek–Brown material varieties. Moreover, this study extends its scope by encompassing the application of multiple linear regression, multiple nonlinear regression, and artificial neural network models for an extensive comparative analysis. The amalgamation of these models widens the evaluative framework, fostering a more comprehensive exploration of predictive capabilities and insights into the stability assessment of annular footings across rock mass conditions. Through this multifaceted approach, a holistic comprehension emerges, thereby enhancing the decision-making process pertaining to the design of annular foundations within diverse Hoek–Brown material contexts.

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Data Availability

All data, models, and code that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This study was financially supported by Office of the Permanent Secretary, Ministry of Higher Education, Science, Research and Innovation under Research Grant for New Scholar (RGNS 65-112).

Funding

This research was funded by National Science, Research and Innovation Fund (NSRF), and King Mongkut’s University of Technology North Bangkok with Contract no. KMUTNB-FF-66-27.

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Authors and Affiliations

  1. Research Unit in Sciences and Innovative Technologies for Civil Engineering Infrastructures, Department of Civil Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12120, Thailand

    Suraparb Keawsawasvong, Kongtawan Sangjinda & Wittaya Jitchaijaroen

  2. Department of Roads and Transport Engineering, University of Al-Qadisiyah, Al-Diwaniyah, Al-Qadisiyah, Iraq

    Saif Alzabeebee

  3. Department of Civil Engineering, Faculty of Engineering and Technology, Rajamangala University of Technology Isan, Nakhon Ratchasima, 30000, Thailand

    Cherdsak Suksiripattanapong

  4. Department of Teacher Training in Civil Engineering, Faculty of Technical Education, King Mongkut’s University of Technology North Bangkok, Bangkok, 10800, Thailand

    Raksiri Sukkarak

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  1. Suraparb Keawsawasvong
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  2. Kongtawan Sangjinda
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Correspondence to Raksiri Sukkarak.

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Keawsawasvong, S., Sangjinda, K., Jitchaijaroen, W. et al. Soft Computing-Based Models for Estimating the Ultimate Bearing Capacity of an Annular Footing on Hoek–Brown Material. Arab J Sci Eng 49, 5989–6006 (2024). https://doi.org/10.1007/s13369-023-08588-w

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