Helical Pile Capacity-to-Torque Correlation: A More Reliable Capacity-to-Torque Factor Based on Full Scale Load Tests-Article

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The study develops a revised relationship for estimating helical pile capacity from installation torque. Traditional capacity-to-torque factors (Kt), including those in ICC-ES AC358, generally depend on shaft size alone. The authors argue that capacity also varies with shaft shape and diameter, helix configuration, loading direction, and installation torque.<br /><br />The analysis used 799 full-scale static load tests—440 in compression and 359 in tension—on piles with round or square shafts and single or multiple helices. Tests were conducted in sand, clay, and weathered bedrock. Ultimate capacity was defined at 10% net deflection of the average helix diameter.<br /><br />Rather than relating capacity-to-torque ratio directly to shaft diameter, the researchers found a stronger correlation by fitting capacity to the ratio of effective shaft diameter to final installation torque. They developed a power-law baseline and adjustment factors (λ) for eight combinations of shaft shape, helix configuration, and loading direction, yielding a modified factor, Km.<br /><br />The proposed method accounts for these variables and allows the capacity-to-torque factor to change with installation torque. The study reports that AC358 values tend to underestimate capacity at low torque and overestimate it at high torque. Probability analysis generally showed better accuracy and reliability for the modified method, particularly for square shafts and tension loading, although results varied by configuration.<br /><br />The authors caution that the findings apply to the tested products and soil conditions. Most tests covered only 30%–70% of shaft torque ratings; further testing across a wider torque range and in additional soils is recommended.

Keywords

helical pile capacity

installation torque

capacity-to-torque factor

AC358

shaft shape

helix configuration

static load tests

compression and tension

power-law model