2021
DOI: 10.1080/17480272.2021.1992648
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Artificial neural-network optimisation of nail size and spacings of plywood shear wall

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Cited by 1 publication
(1 citation statement)
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“…Dhonju et al (2017) examined the effects of nail spacing in panel, wall length, arrangement and configuration of studs and floor members, and vertical load on the shear performance of OSB shear walls. Demir et al (2023) used Artificial Neural Networks (ANN) to estimate the maximum load and displacement of shear walls sheathed with plywood according to various nail spacing and revealed the effect of nail size and spacing on the shear resistance of plywood shear walls in light-frame construction. Doudak et al (2006) experimented to find the effects of openings in light-frame shear walls such as windows and doors, on the shear modulus and strength characteristics of the wall.…”
Section: Introductionmentioning
confidence: 99%
“…Dhonju et al (2017) examined the effects of nail spacing in panel, wall length, arrangement and configuration of studs and floor members, and vertical load on the shear performance of OSB shear walls. Demir et al (2023) used Artificial Neural Networks (ANN) to estimate the maximum load and displacement of shear walls sheathed with plywood according to various nail spacing and revealed the effect of nail size and spacing on the shear resistance of plywood shear walls in light-frame construction. Doudak et al (2006) experimented to find the effects of openings in light-frame shear walls such as windows and doors, on the shear modulus and strength characteristics of the wall.…”
Section: Introductionmentioning
confidence: 99%