A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle - 07/09/17
pages | 12 |
Iconographies | 13 |
Vidéos | 0 |
Autres | 0 |
Abstract |
This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.
Le texte complet de cet article est disponible en PDF.Keywords : Optimization, Rail vehicle, Curved tracks, Safety, Robust design, Uncertainty
Plan
Vol 345 - N° 10
P. 712-723 - octobre 2017 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.
Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’achat d’article à l’unité est indisponible à l’heure actuelle.
Déjà abonné à cette revue ?