Feasibility of an evolutionary artificial intelligence (AI) scheme for modelling of load settlement response of concrete piles embedded in cohesionless soil

ABSTRACT

This investigation aimed to examine the load carrying capacity of piles embedded in sandy soil of various densities, and to develop a predictive model to determine pile settlement using a novel artificial intelligence (AI) method. Experimental pile load tests were conducted using three concrete piles, with aspect ratios of 12, 17 and 25. Evolutionary Levenberg–Marquardt MATLAB algorithms, enhanced by T-tests and F-tests, were used in this process. According to the statistical analysis and the relative importance study, pile length, applied load, pile flexural rigidity, pile aspect ratio and sand–pile friction angle were found to play a key role in pile settlement. Results revealed that the proposed optimum model algorithm precisely characterized pile settlement. There was close agreement between the experimental and predicted data (Pearson's R = 0.988, P = 6.28 × 10^-31) with a relatively insignificant root mean square error of 0.002.

KEYWORDS:

• Levenberg–Marquardt MATLAB algorithm
• pile load-settlement
• sandy soil
• pile slenderness’ ratio
• sand relative density

Acknowledgments

The authors would like to thank the reviewers for their constructive feedback, which help to improve the quality of the paper. The authors are extremely grateful to all organisations that funded the study described in this paper, which was supported by the Iraqi Ministry of Higher Education and Scientific Research and University of Wasit.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Iraqi Cultural Attache in London; University of Wasit [grant number 1178].