Experimental Investigation on Mechanical Properties of Glass Fiber–Nanoclay–Epoxy Composites Under Water-Soaking: A Comparative Study Using RSM and ANN DOI Open Access
Manjunath Shettar, Ashwini Bhat,

Nagaraj N. Katagi

et al.

Journal of Composites Science, Journal Year: 2025, Volume and Issue: 9(4), P. 195 - 195

Published: April 21, 2025

Fiber-reinforced polymer composites are exposed to severe environmental conditions throughout their intended lifespan. It is essential investigate how they age when cold and hot water increase the durability of fiber-reinforced composites. This work uses a hand lay-up process create with different weight percentages glass fiber, nanoclay, epoxy. ASTM guidelines followed for performing tensile flexural tests. The input parameters, varying wt.% fiber continuous, aging condition deemed categorical factor. mechanical properties considered as response variables (output). optimized using Response Surface Methodology (RSM), while Artificial Neural Networks (ANNs) provide reliable predictive model high correlation coefficients. findings demonstrate that ANNs outperform RSM in strength prediction, whereas offers greater accuracy modeling. SEM analysis fracture surfaces reveals causes specimen failure under load, distinct differences between dry, cold, boiling water-soaked specimens.

Language: Английский

Enhancing Performance of Beam-Column Joints in Reinforced Concrete Structures Using Carbon Fiber-Reinforced Polymers (CFRP): A Novel Review DOI Creative Commons
Gift Onyinyechi Oloni, Abdulkhalik J. Abdulridha

Hybrid Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100444 - 100444

Published: March 1, 2025

Language: Английский

Citations

0
Mechanical Performance of Recycled Woven Basalt Fiber-Reinforced Composites for Sustainable Manufacturing Applications DOI
Mohamed Chairi, Elpida Piperopoulos, G. Di Bella

et al.

Applied Composite Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Language: Английский

Citations

0
Experimental Investigation on Mechanical Properties of Glass Fiber–Nanoclay–Epoxy Composites Under Water-Soaking: A Comparative Study Using RSM and ANN DOI Open Access
Manjunath Shettar, Ashwini Bhat,

Nagaraj N. Katagi

et al.

Journal of Composites Science, Journal Year: 2025, Volume and Issue: 9(4), P. 195 - 195

Published: April 21, 2025

Fiber-reinforced polymer composites are exposed to severe environmental conditions throughout their intended lifespan. It is essential investigate how they age when cold and hot water increase the durability of fiber-reinforced composites. This work uses a hand lay-up process create with different weight percentages glass fiber, nanoclay, epoxy. ASTM guidelines followed for performing tensile flexural tests. The input parameters, varying wt.% fiber continuous, aging condition deemed categorical factor. mechanical properties considered as response variables (output). optimized using Response Surface Methodology (RSM), while Artificial Neural Networks (ANNs) provide reliable predictive model high correlation coefficients. findings demonstrate that ANNs outperform RSM in strength prediction, whereas offers greater accuracy modeling. SEM analysis fracture surfaces reveals causes specimen failure under load, distinct differences between dry, cold, boiling water-soaked specimens.

Language: Английский

Citations

0