Environmental analysis-driven structural optimization for hybrid structural systems

Integrating Life Cycle Assessment (LCA) methodologies within Structural Design Optimiza-tion (SDO) is essential for advancing sustainable engineering practices. This study presents a robust framework that merges structural optimization techniques with LCA to assess and mit-igate the environmental impacts associated with industrial steel-timber hybrid buildings. Focusing on generative design applications, the research employs a Visual Programming Language (VPL) environment to optimize the size, shape, and topology of a single-story in-dustrial space frame structure. The optimization process emphasizes material efficiency and Global Warming Potential (GWP) as key environmental metrics. Two primary scenarios are analyzed: one utilizing pure steel elements and the other permitting hybrid configurations that incorporate glulam timber. Multi-objective evolutionary algorithms (MOEAs) facilitate the identification of Pareto-optimal solutions, balancing structural performance with environ-mental considerations. Results indicate that hybrid configurations achieve substantial GWP reductions relative to conventional steel structures, while still delivering comparable struc-tural integrity. Sensitivity analyses identify critical design variables—such as cross-sectional area, span lengths, and support conditions—that significantly affect the interplay between en-vironmental and structural performance objectives. This research underscores the importance of incorporating environmental parameters early in the design process to foster sustainable practices within the construction sector.