Eco‐ductile design of RC columns: Resolving the conflict between embodied carbon and curvature ductility

Abstract Reducing embodied carbon emissions in structural design is of critical importance in combating global climate change. However, the increased material usage and heavy confinement reinforcement required to meet high ductility demands in reinforced concrete columns directly conflict with environmental sustainability goals. This study utilizes a parametric computational approach based on Multi‐Objective Particle Swarm Optimization (MOPSO) to investigate the trade‐off relationship between curvature ductility (maximization) and embodied carbon emission (minimization). To reflect realistic engineering practices, the problem was formulated within a discrete design framework under strict ACI 318–19 detailing constraints, dynamically optimizing cross‐sectional dimensions, longitudinal reinforcement counts, and transverse tie spacing. Structural performance was evaluated through high‐fidelity non‐linear fiber section analyses (OpenSeesPy), integrating the Mander confinement model and ATC‐72 physical material failure limits. The assessment was conducted over a full‐factorial load matrix of 150 axial‐flexural demand combinations, applied to each of nine material cases spanning varying concrete strengths (C30–C50) and a transition from conventional (S420) to high‐strength steel grades (S500 and S550). The results reveal that the adoption of S550 steel yields a 7.4% reduction in median embodied carbon compared to the S420 baseline, while concurrently elevating global median curvature ductility from 10.10 to 11.13. This achieves material reduction by driving average longitudinal steel ratios down to code‐mandated boundaries (1.31%) without violating requisite ductility margins. Furthermore, a strict load‐driven boundary was identified, demonstrating that maximum curvature ductility consistently peaks within a moderate‐to‐high compression band ( n ∈ [0.1, 0.3)), while extreme demands ( n ≥0.3) physically truncate the feasible Pareto‐optimal design space. The derived Pareto fronts and design guideline matrices provide rule‐based strategies for practitioners to mathematically balance the carbon footprint and structural ductility under varying axial and eccentric demands.