부산대학교 도서관

The local bearing capacity is a basic mechanical property, which is crucial in the post-tensioned anchorage zone design. However, it is challenging to accurately predict local bearing capacity due to the disordered and complex stress conditions in anchorage zone. The existing prediction models have limited application scope, which are difficult to meet the application requirements of novel materials. In this study, the objective is to develop the general prediction models for evaluating concrete local bearing capacity. A reliable database was established based on the test result datasets collected from this study and previous studies. Then, the influence of concrete strength, local area aspect ratio and duct was analyzed. The calculation model was obtained based on fitting analysis (FA) and artificial neural network (ANN) technology. Besides, both the FA model and ANN model were proven to accurately predict concrete local bearing capacity, according to the prediction performance comparisons with existing typical prediction models.