To remain competitive in the global market, automotive companies scrutinise product development processes for time and cost savings incurred bringing new vehicles to market. As a result, virtual durability simulation can be utilised early in the design process to reduce the number of costly physical prototypes, assuming that high fidelity models are used. The compromise between model accuracy and computational efficiency present a challenge that will be adressed by the authors. Neuronal networks, as computationally efficient mathematical models, will be shown as viable tool for development of high fidelity models of nonlinear hysteretic components within a virtual durability simulation.
Streamlining automotive product development using neural networks
Verbesserung der Fahrzeug-Produktentwicklung mit Hilfe neuronaler Netzwerke
International Journal of Vehicle Design ; 47 , 1-4 ; 19-36
2008
18 Seiten, 15 Bilder, 2 Tabellen, 12 Quellen
Aufsatz (Zeitschrift)
Englisch
neuronales Netzwerk , rechnerunterstützter Produktentwurf , Rechnersimulation , Anwendung im Fahrzeugbau , Wettbewerbsfähigkeit , virtuelle Prototypentwicklung , Simulationsmodellbildung , mathematisches Modell , Kostenersparnis , Zeiteinsparung , Lebensdauer , Empfindlichkeitsanalyse , Nichtlinearität , mechanische Hysterese
Streamlining automotive product development using neural networks
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|Streamlining automotive product development using neural networks
Online Contents | 2008
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