A novel direct SPT method to accurately estimate ultimate axial bearing capacity of bored PHC nodular piles with 81 case studies in Vietnam
Bored PHC nodular piles (BPNP) are an eco-friendly and advantageous option for pile foundations of medium-rise to high-rise buildings. As none of the current methods to estimate the ultimate axial load-bearing capacity is accurate enough for BPNP in engineering practice, this study aims to achieve t...
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Published in: | Soils and foundations Vol. 62; no. 4; p. 101163 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier B.V
01-08-2022
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Subjects: | |
Online Access: | Get full text |
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Summary: | Bored PHC nodular piles (BPNP) are an eco-friendly and advantageous option for pile foundations of medium-rise to high-rise buildings. As none of the current methods to estimate the ultimate axial load-bearing capacity is accurate enough for BPNP in engineering practice, this study aims to achieve that objective by developing a new direct SPT method. To that end, we use static pile load test and SPT data of 81 PHC nodular piles collected in Vietnam. The ultimate bearing capacity is interpreted from the load–displacement curve in pile static load tests by various methods to determine the most suitable method for the nodular piles. Furthermore, 8 methods to determine axial load pile capacity directly from the standard penetration test are examined. Each method’s effectiveness is evaluated by comparing its predicted values with the measured values. Finally, the genetic algorithm for function optimization is employed to develop a new direct SPT method that can accurately predict the ultimate axial load-bearing capacity of nodular piles. The reliability of the proposed formula is justified by comparing the proportion of end bearing capacity with other published works. It is verified that the developed directed SPT method outperforms all current methods and could be implemented directly in engineering practice. |
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ISSN: | 0038-0806 |
DOI: | 10.1016/j.sandf.2022.101163 |