Effective Compressive Strengths of Corner and Edge Concrete Columns Based on an Adaptive Neuro-Fuzzy Inference System

Abstract

In the current design codes, the effective compressive strength can be used to reflect decrease in load-transfer performance when upper/lower columns and slabs have different concrete compressive strengths. In this regard, this study proposed a method that can accurately estimate the effective compressive strengths by using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS is an algorithm that introduces a learning system that corrects errors into a fuzzy theory and has widely been used to solve problems with complex mechanisms. In order to constitute the ANFIS algorithm, 50 data randomly extracted from 75 existing test datasets were used in training, and 25 were used for verification. It was found that analysis using the ANFIS model provides a more accurate evaluation of the effective compressive strengths of corner and edge columns than do the equations specified in the current design codes. In addition, parametric studies were performed using the ANFIS model, and a simplified equation for calculating the effective compressive strength was proposed, so that it can be easily used in practice.

Keywords

• ANFIS
• fuzzy
• neuro-fuzzy
• effective compressive strength
• high strength concrete
• slab