Using genetic algorithm for the optimization of seismic behavior of steel planar frames with semi-rigid connections

Oskouei, Asghar Vatani; Fard, Sahand Sarioletlagh; Aksoğan, Orhan

doi:10.1007/s00158-011-0697-9

Cited by 12 publications

(1 citation statement)

References 15 publications

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“…After the 1994 Northridge and the 1995 Kobe earthquake, widespread analytical studies and experimental tests were commenced to examine the viability of using bolted connections in steel structures in high-seismicity zones [9][10][11]. A review of past literature shows that semi-rigid connections may be considered for seismic application where a large spectrum of such behavior positively influences structure strength and stability [12][13][14]. This research acknowledges that semi-rigid connections are characterized by reliable flexibility and appropriate rotational capacity.…”

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confidence: 99%

Hybrid Krill Herd-ANN Model for Prediction Strength and Stiffness of Bolted Connections

et al. 2021

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The behavior of beam-to-column connections significantly influences the stability, strength, and stiffness of steel structures. This is particularly important in extreme non-elastic responses, i.e., earthquakes, and sudden column removal, as the fluctuation in strength and stiffness affects both supply and demand. Accordingly, it is essential to accurately estimate the strength and stiffness of connections in the analysis of and design procedures for steel structures. Beginning with the state-of-the-art, the capacity of three available component-based mechanical models to estimate the complex mechanical properties of top- and seat-angle connections with double-web angles (TSACWs), with variable parameters, were investigated. Subsequently, a novel hybrid krill herd algorithm-artificial neural network (KHA-ANN) model was proposed to acquire an informational model from the available experimental dataset. Using several statistical metrics, including the corresponding coefficient of variation (CoV), correlation coefficient (R), and the correlation coefficient provided by the Taylor diagram, this study revealed that the krill herd-ANN model achieved the most reliable predictive accuracy for the strength and stiffness of top- and seat-angle connections with double web angles.

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confidence: 99%