Improvement of the structural design of reinforced concrete columns in a residential building through economic and environmental criteria using Monte Carlo simulations

Abstract The application of data analysis methodologies to the construction sector—specifically, to the design of concrete structures—can offer significant advantages in terms of structural performance, economic efficiency, and environmental impact. This study evaluates, through a series of fully executable case studies of reinforced concrete columns, the most efficient alternative from both an economic and environmental perspective. For the economic analysis, changes in the prices of concrete and steel reinforcement materials in Spain over the past 30 years were examined. Subsequently, Monte Carlo simulations were employed to generate representative macroeconomic scenarios (stable, pessimistic, optimistic and combined) with a 95% confidence interval, considering market uncertainty parameters, periods of economic stability, and downturns identified from the historical time series analysed. This approach made it possible to identify the case study corresponding to the minimum-cost column solution. In addition, environmental impact was included as a selection criterion for the structural elements. The results were obtained using the Life Cycle Assessment methodology. Among the most significant findings were price differences of up to 12.18% between case studies under the same macroeconomic scenario, as well as a 17.64% increase in CO 2 -equivalent emissions—representing an additional 8.53 tonnes of CO 2 -eq for the same structural solution. This research demonstrates that the use of such tools can contribute significantly and proactively to a more optimised and sustainable design of reinforced concrete structural elements.