Machine learning for optimal design of circular hollow section stainless steel stub columns: A comparative analysis with Eurocode 3 predictions

Abarkan, Ikram; Rabi, Musab; Ferreira, Felipe Piana Vendramell; Shamass, Rabee; Limbachiya, Vireen; Jweihan, Yazeed S.; Pinho Santos, Luis Fernando

doi:10.1016/j.engappai.2024.107952

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Verification Using Fem and Design Code1

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2024

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“…Several methods can be used to determine the strength of steel members along with laboratory tests to cover a wide range of parameters. One of these methods is machine learning which has been employed in different structural applications 29 – 31 . Another method is the finite element analysis, an important research pillar 32 – 34 .…”

Section: Verification Using Fem and Design Codementioning

confidence: 99%

Experimental and numerical investigations on the bending capacity of cold-formed steel box headers

Matloub,

Elayouby,

Ibrahim

et al. 2024

Sci Rep

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The study investigates the bending strength of tracks of box headers beyond AISI, which considers the capacity of individual channels alone. Both experimental and FEM are used, and the results are compared to AISI. The findings highlight tracks' significant role in the overall bending capacity. AISI is found to be conservative by 34% to 152%. Failure mode is different from code theoretical expectations for a single channel. Fastener close spacing marginally improves the capacity, while side fasteners offer significant enhancement, but track widening limits this enhancement. A modification to AISI is proposed considering track strength, with outcomes showing good accuracy.

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Section: Verification Using Fem and Design Codementioning

confidence: 99%