Multiobjective optimization on adhesive bonding of aluminum‐carbon fiber laminate

Eduardo Valdés, J. D Mosquera‐Artamonov, Celso Cruz, Jaime Taha-Tijerina

Resultado de la investigaciónrevisión exhaustiva

Resumen

This work presents a multi‐objective optimization methodology to find compromise adhesive bonding schemes that possess a great shear load and a low percentage of remaining fiber in the bonding. The joining overlap, adhesive type, and prior surface finishing are considered. The Pareto front of the multi‐objective response surface model is found with an Nondominated Sorting Genetic algorithm. The adhesive bonding factors are the adhesive (MP55420, Betamate 120, and DC‐80), the surface finishing (acetone cleaned and atmospheric plasma), and the overlapping distance of the test coupons.
Idioma originalEnglish
Páginas (desde-hasta)621-634
Número de páginas14
PublicaciónComputational Intelligence
Volumen37
N.º1
Fecha en línea anticipada7 ene 2021
DOI
EstadoPublished - feb 2021

Nota bibliográfica

Publisher Copyright:
© 2021 Wiley Periodicals LLC.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Matemática computacional
  • Inteligencia artificial

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