Predicting the effect of voids generated during RTM on the low-velocity impact behaviour by machine learning-based surrogate models

  1. Mendikute, J.
  2. Baskaran, M.
  3. Llavori, I.
  4. Zugasti, E.
  5. Aretxabaleta, L.
  6. Aurrekoetxea, J.
Revue:
Composites Part B: Engineering

ISSN: 1359-8368

Année de publication: 2023

Volumen: 260

Type: Article

DOI: 10.1016/J.COMPOSITESB.2023.110790 GOOGLE SCHOLAR lock_openeBiltegia editor

Objectifs de Développement Durable

La source de données: Scopus