This state-of-the-art review comprehensively evaluates the seismic design and performance assessment of concentrically braced frame (CBF) systems, specifically focusing on special concentrically braced frames (SCBFs). SCBFs have shown remarkable effectiveness in providing seismic resistance for various building types, including residential, commercial, and industrial structures. However, it is crucial to acknowledge that natural disasters can lead to significant losses in human lives, economic impact, social disruption, and damage to industrial facilities. Therefore, this review concentrates on the seismic design and performance assessment of SCBFs developed for complex industrial buildings. Despite significant research efforts in SCBF performance assessment, there remains a notable gap in comprehensive critical reviews focused on studying SCBFs in the context of irregular and complex industrial structures. Identifying this research gap and conducting an updated review incorporating recent advancements, particularly the integration of Artificial Intelligence (AI) techniques, becomes necessary. The major goal of this study is to assess existing research efforts and identify areas that need further inquiry. Furthermore, AI methods, such as Machine Learning (ML) techniques, are highly recommended to enhance the performance of SCBFs and effectively identify damaged structures after severe earthquakes. The review identifies the need for further investigation in this specific area. By addressing these research gaps and leveraging AI advancements, the resilience of industrial buildings can be enhanced, thereby mitigating the losses resulting from seismic events.

这项最先进的审查全面评估了同心支撑框架 (CBF) 系统的抗震设计和性能评估，特别关注特殊的同心支撑框架 (SCBF)。 SCBF 在为各种建筑类型（包括住宅、商业和工业结构）提供抗震性能方面表现出显着的有效性。然而，至关重要的是要认识到自然灾害可能导致重大人员伤亡、经济影响、社会混乱和工业设施损坏。因此，本文重点关注为复杂工业建筑开发的 SCBF 的抗震设计和性能评估。尽管在 SCBF 绩效评估方面做出了大量研究工作，但在不规则和复杂的产业结构背景下重点研究 SCBF 的综合批判性评论仍然存在显着差距。有必要识别这一研究差距，并结合最新进展，特别是人工智能 (AI) 技术的集成，进行更新的审查。这项研究的主要目标是评估现有的研究工作并确定需要进一步研究的领域。此外，强烈建议使用机器学习（ML）技术等人工智能方法来增强 SCBF 的性能并有效识别严重地震后受损的结构。审查确定了在这一特定领域进行进一步调查的必要性。通过解决这些研究差距并利用人工智能的进步，可以增强工业建筑的弹性，从而减轻地震事件造成的损失。