CAPACITY-TO-TORQUE CORRELATIONS FOR LARGE DIAMETER HELICAL PILES-PPT Presentation

PPT Presentation

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The presentation examines how installation torque can be used to estimate the load capacity of large-diameter helical piles. The established relationship is \(P = K_t T\), where \(P\) is ultimate capacity, \(T\) is final installation torque, and \(K_t\) is the capacity-to-torque factor. Earlier research found shaft diameter to be a major influence and informed industry guidance for smaller piles.<br /><br />As designers increasingly use shafts larger than 4.5 inches—and sometimes up to 18.625 inches—the existing ICC-ES AC358 correlation has limited supporting data. A compiled database of 416 full-scale tension and compression tests, including 86 tests on shafts 5.5 inches or larger, indicates that large piles often achieve greater capacities than AC358 predicts.<br /><br />The authors argue that the existing equation becomes unsuitable at large effective shaft diameters: it drives \(K_t\) toward zero, implying implausibly low capacity. They propose a revised regression with a non-zero horizontal asymptote. It aligns with existing factors for smaller shafts while increasing predicted \(K_t\) values for larger shafts by roughly 5–20%.<br /><br />However, the test database may understate capacity-to-torque factors. Many tests stopped at 200% of design load or did not reach recognized failure criteria, and test loads were not adjusted for piles that experienced installation torque higher than the value used in capacity predictions. The authors recommend improving the database and conducting “excess” tests: after the standard test, reload piles until failure criteria are observed to establish maximum capacity.<br /><br />Overall, the proposed correlation better reflects available large-pile test results, but further testing is needed to confirm true capacities and refine the relationship.

Keywords

helical piles

installation torque

load capacity

capacity-to-torque factor

large-diameter shafts

ICC-ES AC358

full-scale tests

regression model

ultimate capacity

structural engineering