4.6 Article

Critical Failure Mode Determination of Steel Moment Frames by Plastic Analysis Optimization Principles

期刊

BUILDINGS
卷 13, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/buildings13082008

关键词

plastic theory; steel moment frame; optimizer; dolphin echolocation; failure analysis

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Determining the failure or failure mode of structures has always been a challenge for civil engineers. Traditional methods of analysis are costly and complex, while plastic analysis offers a simpler approach. However, as structures become more complex, the effectiveness of plastic analysis diminishes due to the increasing number of potential mechanism combinations. To overcome this, optimizers have been used in the field of structural engineering to efficiently solve problems with large search spaces. This research focuses on implementing the plastic theory of steel frames using MATLAB software and proposes a novel binary dolphin echolocation algorithm to optimize the plastic analysis method.
Determining the failure or failure mode of structures has long been a challenge for civil engineers. Traditional methods for analyzing structures are costly and complex. Plastic analysis, which involves combining pre-defined mechanisms, offers a less complex approach. However, as the number of potential mechanism combinations, or the search space, increases with the growing complexity of structural members, the effectiveness of this method diminishes. To address this issue, optimizers have been applied in the field of structural engineering to efficiently solve problems with large search spaces. Population-based meta-heuristic algorithms are widely used for their reduced dependency on input parameters. This research focuses on implementing the plastic theory of steel frames using MATLAB software, employing virtual work concepts and pre-defined mechanism combinations. A novel binary dolphin echolocation algorithm is proposed based on the principles of the primary algorithm. This algorithm is then utilized to optimize the plastic analysis method and determine the failure load factor and critical failure mode for sample frames. Additionally, the grey wolf optimizer and whale optimization algorithm are applied to optimize the problem, and the performance of all three algorithms is compared. The results demonstrate that the proposed algorithm yields accurate results with a minor margin of error compared to the other two algorithms.

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