http://www.cnr.it/ontology/cnr/individuo/prodotto/ID302222
High-fidelity global optimization of shape design by dimensionality reduction, metamodels and deterministic particle swarm (Articolo in rivista)
- Type
- Label
- High-fidelity global optimization of shape design by dimensionality reduction, metamodels and deterministic particle swarm (Articolo in rivista) (literal)
- Anno
- 2015-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1080/0305215X.2014.895340 (literal)
- Alternative label
Chen, Xi; Diez, Matteo; Kandasamy, Manivannan; Zhang, Zhiguo; Campana, Emilio Fortunato; Stern, Frederick (2015)
High-fidelity global optimization of shape design by dimensionality reduction, metamodels and deterministic particle swarm
in Engineering optimization (Print)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Chen, Xi; Diez, Matteo; Kandasamy, Manivannan; Zhang, Zhiguo; Campana, Emilio Fortunato; Stern, Frederick (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.scopus.com/record/display.url?eid=2-s2.0-84896418939&origin=inward (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Huazhong University of Science and Technology; University of Iowa; Consiglio Nazionale delle Ricerche (literal)
- Titolo
- High-fidelity global optimization of shape design by dimensionality reduction, metamodels and deterministic particle swarm (literal)
- Abstract
- Advances in high-fidelity shape optimization for industrial problems are presented, based on geometric variability assessment and design-space dimensionality reduction by Karhunen-Loève expansion, metamodels and deterministic particle swarm optimization (PSO). Hull-form optimization is performed for resistance reduction of the high-speed Delft catamaran, advancing in calm water at a given speed, and free to sink and trim. Two feasible sets (A and B) are assessed, using different geometric constraints. Dimensionality reduction for 95% confidence is applied to high-dimensional free-form deformation. Metamodels are trained by design of experiments with URANS; multiple deterministic PSOs achieve a resistance reduction of 9.63% for A and 6.89% for B. Deterministic PSO is found to be effective and efficient, as shown by comparison with stochastic PSO. The optimum for A has the best overall performance over a wide range of speed. Compared with earlier optimization, the present studies provide an additional resistance reduction of 6.6% at 1/10 of the computational cost. © 2014 © 2014 Taylor & Francis. (literal)
- Prodotto di
- Autore CNR
- Insieme di parole chiave
Incoming links:
- Autore CNR di
- Prodotto
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
- Insieme di parole chiave di