A parametric study of adhesive bonded joints with composite material using black-box and grey-box machine learning methods: Deep neuron networks and genetic programming-Reference-Cited by-同舟云学术

A parametric study of adhesive bonded joints with composite material using black-box and grey-box machine learning methods: Deep neuron networks and genetic programming

Published:2021-07 Issue: Volume:217 Page:108894
ISSN:1359-8368
Container-title:Composites Part B: Engineering
language:en
Short-container-title:Composites Part B: Engineering

Author:

Gu Zewen,Liu Yiding,Hughes Darren J.,Ye Jianqiao,Hou Xiaonan

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Mechanics of Materials,Ceramics and Composites

Reference36 articles.

1. Life cycle engineering of lightweight structures;Herrmann;CIRP Annals,2018

2. An updated review of adhesively bonded joints in composite materials;Budhe;Int J Adhesion Adhes,2017

3. Effect of material, geometry, surface treatment and environment on the shear strength of single lap joints;Da Silva;Int J Adhesion Adhes,2009

4. Effects of composite adherend properties on stresses in double lap bonded joints;Mokhtari;Mater Des,2013

5. Effect of adhesive thickness, adhesive type and scarf angle on the mechanical properties of scarf adhesive joints;Liao;Int J Solid Struct,2013

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