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Articles

A new modified method of predicting load-settlement behavior for large-diameter helical piles in sand considering nonlinear degradation of soil stiffness

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Pages 83-98 | Received 23 Nov 2020, Accepted 29 Oct 2021, Published online: 27 Jan 2022
 

Abstract

With respect to the design of helical pile foundations, reliable prediction of pile settlement is necessary to ensure appropriate structural and serviceability performance. At present, most research into the load-settlement response is focused on the regular displacement piles (precast/cast-in-place driven displacement piles) while there is little research on the prediction of the load-settlement curve of helical piles in sand. This paper presents a new modified method taking Randolph’s analytical pile solution as the theoretical framework with the consideration of the nonlinear soil stiffness degradation corresponding to different loads and settlements. The proposed method for helical piles is verified by centrifuge tests of 9 helical piles in three types of sand (loose, medium dense and dense sand) and 4 helical piles in two field test cases with better agreement with test results compared with the existing method for driven piles. Also, the influence of different parameters of pile and soil on the load-settlement curve of single-blade piles is analyzed.

    Highlights

  1. A novel empirical formula is proposed to analyze the nonlinear behavior of the load-displacement curve of a single-helix pile based on the back-analysis method.

  2. The load-settlement curves predicted from the new modified method is in reasonably good agreement with measured ones from both centrifuge and field tests.

  3. The calculated load-settlement curves of 4 helical piles in 2 field tests from the new modified method are in significantly better agreement with those from exisiting method for driven piles in sand.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Financial support from the National Natural Science Foundation of China (Grant Nos. 52078427 and 51978588) is greatly acknowledged.

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