Artificial Intelligence Metamodeling Approach to Design Smart Composite Laminates with Bend-Twist Coupling

Daniel Restrepo-Montoya, Joham Alvarez-Montoya, Julian Sierra-Perez, Cesar Nieto-Londono

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The bend-twist coupling effect of anisotropic materials such as composite laminates can be used to create smart structures capable of adapting their shapes to changing operating conditions. This effect can be useful in wind energy systems with composite blades for improving the rotor operational range as a passive control strategy. However, it is difficult to design such structures in order to attain a desired angle when bent. This paper proposes a metamodel-based methodology to design laminates with bend-twist coupling effect by means of genetic algorithms (GA) and artificial neural networks (ANN) integrated with a finite element model (FEM) capable of defining the stacking sequence that a laminate needs to reach a certain twist angle when submitted to bending load. The genetic algorithm uses a deterministic tournament for selection, a two-point method for crossover and an ANN trained with FEM simulations is used as the fitness function for reducing computational time. This strategy could ease the design of this type of structures in practical scenarios.

Idioma originalInglés
Título de la publicación alojada2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas155-159
Número de páginas5
ISBN (versión digital)9781728145624
DOI
EstadoPublicada - nov. 2019
Publicado de forma externa
Evento2nd IEEE International Conference on Renewable Energy and Power Engineering, REPE 2019 - Toronto, Canadá
Duración: 2 nov. 20194 nov. 2019

Serie de la publicación

Nombre2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019

Conferencia

Conferencia2nd IEEE International Conference on Renewable Energy and Power Engineering, REPE 2019
País/TerritorioCanadá
CiudadToronto
Período2/11/194/11/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

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