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<p>Structural optimization is crucial in advancing simulation-based engineering by potentially improving design sustainability and resilience. However, optimizing for specific criteria often results in inefficient or vulnerable designs when evaluated against other critical factors. Among these factors, structural safety—particularly buildings’ resistance to progressive collapse (PC)—has garnered increasing attention. Despite significant experimental and numerical studies, the integration of PC resistance into structural optimization remains underexplored. This paper introduces a computational framework, termed Optimization-based Robust Design to Progressive Collapse (ObRDPC), combining simulation-based optimization techniques with PC-resistant design principles. The methodology also incorporates an automated strategy for considering soil-structure interaction (SSI), an aspect usually ignored in optimization-based structural design. The proposed framework is validated through five case studies involving 3D reinforced concrete skeleton buildings, each subjected to two load-bearing element removal scenarios using the Alternate Path method. Results demonstrate the pivotal role of SSI in achieving efficient designs and accurately assessing PC robustness. Neglecting SSI can lead to material usage differences of up to 24.29% and 22.09% in superstructure design following corner and exterior column failures, respectively. Findings also indicate that increasing the number of stories enhances structural robustness. In contrast, buildings with 8-meter spans may incur over 50% higher environmental impact to withstand the failure of a load-bearing element. The study also provides insights into load redistribution mechanisms that beams, columns, and foundations adopt to improve structural resilience. Finally, practical design guidelines are provided to support the replicability and real-world application of the framework, promoting sustainable and resilient infrastructure.</p>

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An integrated framework for optimization-based robust design to progressive collapse of RC skeleton buildings incorporating soil-structure interaction effects

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月1日

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  • Iván Negrin,
  • Ernesto Chagoyén,
  • Moacir Kripka,
  • Víctor Yepes

摘要

Structural optimization is crucial in advancing simulation-based engineering by potentially improving design sustainability and resilience. However, optimizing for specific criteria often results in inefficient or vulnerable designs when evaluated against other critical factors. Among these factors, structural safety—particularly buildings’ resistance to progressive collapse (PC)—has garnered increasing attention. Despite significant experimental and numerical studies, the integration of PC resistance into structural optimization remains underexplored. This paper introduces a computational framework, termed Optimization-based Robust Design to Progressive Collapse (ObRDPC), combining simulation-based optimization techniques with PC-resistant design principles. The methodology also incorporates an automated strategy for considering soil-structure interaction (SSI), an aspect usually ignored in optimization-based structural design. The proposed framework is validated through five case studies involving 3D reinforced concrete skeleton buildings, each subjected to two load-bearing element removal scenarios using the Alternate Path method. Results demonstrate the pivotal role of SSI in achieving efficient designs and accurately assessing PC robustness. Neglecting SSI can lead to material usage differences of up to 24.29% and 22.09% in superstructure design following corner and exterior column failures, respectively. Findings also indicate that increasing the number of stories enhances structural robustness. In contrast, buildings with 8-meter spans may incur over 50% higher environmental impact to withstand the failure of a load-bearing element. The study also provides insights into load redistribution mechanisms that beams, columns, and foundations adopt to improve structural resilience. Finally, practical design guidelines are provided to support the replicability and real-world application of the framework, promoting sustainable and resilient infrastructure.