Empirical Models for Predicting Reinforced Concrete Quantities for Superstructure Columns of Framed Buildings in Nigeria

Abstract

This study developed regression-based models of the relationship between architectural and structural design variables for speedy quantification of reinforcement concrete in columns of framed buildings. Data on floor area, column area, column number, reinforcement and concrete quantities of columns was collected via taking off/measurement process from relevant architectural and structural drawings of 20 framed building obtained from practicing professionals and analysed using regression analysis. Results generated 4 predictive models: C_A = 0.013F_A – 1.378; C_N = 0.196F_A – 14.189; Conc_QTY = 0.056F_A+5.603 and R_QTY = 0.044Conc_QTY+1.793 for quantifying the total area, number and concrete of superstructure columns. The model assumes that the floor area is a good predictor variable when establishing the number, total cross-sectional area, concrete and reinforcement quantities of the columns. However, the statistical outputs further revealed that floor area is not a good predictor for establishing the volume of concrete in columns and also volume of concrete as a good predictor of reinforcement quantities. The predictive models are recommended for use during approximate estimating at the feasibility stage of building project to save time, generate approximate quantities for the quantity surveyor and provide the client a reliable estimate for columns erection.