COMPARISON OF ESTIMATION METHODS FOR ULTIMATE BEARING CAPACITY OF DRIVEN PILES BASED ON NON-FAILED LOAD TESTS
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Abstract
Pile load testing is commonly conducted using test piles to evaluate pile behavior under actual soil conditions. In practice, these tests are often performed only up to a specified proof load level at which the ultimate failure point is not clearly observed, thereby requiring interpretation methods to estimate the ultimate bearing capacity. This study aims to assess and compare methods for estimating the ultimate bearing capacity of driven piles and to propose an approach for joint interpretation of the results. Field data from five test piles in the Highway No. 4–Sadao Border Checkpoint 2 Interchange Project (Section 1), Songkhla Province, were analyzed. The dataset comprised soil investigation results, pile driving records, and field static pile load test results. The evaluation comprised four approaches: (1) static method, (2) interpretation of static load test results using various methods, (3) a proposed combined method based on selected interpretation methods, and (4) dynamic method. The results indicated that the estimated ultimate bearing capacities varied according to the analytical principles and input data of each approach. The static analytical method generally produced relatively low and conservative estimates, ranging from 122.75 to 142.95 tons. The proposed combined method produced intermediate estimates ranging from 132.46 to 177.84 tons serving as a complementary approach when used with other methods. Dynamic methods yielded higher estimates, reflecting the influence of energy assumptions and pile driving conditions. the Hiley formula produced values ranging from 206.54 to 273.67 tons, whereas the Engineering news formula yielded values ranging from 181.82 to 210.53 tons. These findings indicate that the ultimate bearing capacity of driven piles should not be evaluated using a single method alone. Instead, multiple methods should be considered together to support engineering judgment under the limitations of field data.
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