Prediction of failure load in flat-joggle-flat co-cured composite joints using artificial neural networks
Author:
Publisher
Elsevier BV
Subject
Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science
Reference8 articles.
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4. Artificial Neural Network prediction of Cu-Al2O3 composite properties prepared by powder metallurgy method;Amirjan;J. Mater. Res. Technol.,2013
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1. Dual-scale reinforcement of co-cure single lap joints through graphene nanoparticles and CFRP Z-pin;Materials Letters;2024-09
2. Influence of different manufacturing techniques on GFRP flat-joggle-flat composite joints using multi-scale reinforcements for enhancing shear properties;Materials Research Express;2024-05-01
3. Thermal degradation and fire retardant behaviour of natural fibre reinforced polymeric composites- A comprehensive review;Journal of Materials Research and Technology;2024-05
4. Enhancing shear strength in 3D printed single lap composite joints: A multi‐faceted exploration of GNP integration, print orientation, utilizing artificial neural networks, and dynamic analysis;Journal of Applied Polymer Science;2024-03-17
5. Effect of CFRP pin reinforcement and manufacturing technique on shear and dynamic properties of flat-joggle-flat composite joints;Materials Letters;2024-02
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