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Improving The Prediction For The Ultimate Axial Capacity Of Driven Piles In Ontario Soils With A Genetic Algorithm

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posted on 08.06.2021, 07:57 by Markus Jesswein
A genetic algorithm (GA) was developed to improve predictions for the ultimate axial capacity of driven piles in Ontario soils. Challenges arise to accurately predict the ultimate capacity due to many influential factors, such as the ground conditions, installation method, and pile geometry. A total of 43 piles (H or pipe piles) were collected from the Ministry of Transportation of Ontario. Side and tip resistances were extracted from piles subjected to extension and compression load tests. The soil measurements and pile resistances were regressed with a statistical analysis and GA, and the developed relationships were compared to existing design methods. On average, existing design methods overestimated the capacity by a factor of 1.16 to 3.00. The proposed correlations were slightly conservative with the capacity but provided errors within ± 30 % of the measured side resistance. The new design methods from the GA offer substantial improvements for pile design

History

Language

eng

Degree

Master of Applied Science

Program

Civil Engineering

LAC Thesis Type

Thesis