Machine learning base models to predict the punching shear capacity of posttensioned UHPC flat slabs.

ABSTRACT: The aim of this research is to present correction factors for the punching shear formulas of ACI-318 and EC2 design codes to adopt the punching capacity of post tensioned ultra-high-performance concrete (PT-UHPC) flat slabs. To achieve that goal, the results of previously tested PT-UHPC flat slabs were used to validate the developed finite element method (FEM) model in terms of punching shear capacity. Then, a parametric study was conducted using the validated FEM to generate two databases, each database included concrete compressive strength, strands layout, shear reinforcement capacity and the aspect ratio of the column besides the correction factor (the ratio between the FEM punching capacity and the design code punching capacity). The first considered design code in the first database

SUBMITTER: Ors DM 

PROVIDER: S-EPMC10874378 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature