Multilevel computational model for cost and carbon optimisation of reinforced concrete floor systems

Abstract

The cost and carbon efficiency of building structures could be enhanced by the current developments in design automation and optimisation techniques. New ways to systematically assess design alternatives based on cost and carbon parameters are necessary. The study proposes a multilevel optimisation approach that combines Building Information Modelling (BIM) data and Finite Element Modelling (FEM) with a constrained genetic algorithm. The optimisation methodology is tested in a prototypical building floor system. Structural grid configurations, floor thicknesses and columns sizes and reinforcement details are identified. The results showed that the cost optimum design is 3% cheaper than the carbon optimum design but it has 7% more carbon. In addition, the concrete in the floor is the biggest contributor in both total cost and carbon. Relationships between cost- and carbon-optimum designs for the tested structural configuration are also discussed.