Generative prediction of laser-induced rocket ignition with dynamic latent space representations

Accurate and predictive scale-resolving simulations of laser-ignited rocket engines are highly time-consuming because the problem includes turbulent fuel–oxidizer mixing dynamics, laser-induced energy deposition, and high-speed flame growth. This is conflated with the large design space primarily co...

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Bibliografische gegevens

Hoofdauteurs:	Tony Zahtila, Ettore Saetta, Murray Cutforth, Davy Brouzet, Diego Rossinelli, Gianluca Iaccarino
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Cambridge University Press 2026-01-01
Reeks:	Data-Centric Engineering
Onderwerpen:	autoencoder compression fast surrogate model latent-space trajectory modeling multifidelity
Online toegang:	https://www.cambridge.org/core/product/identifier/S263267362610063X/type/journal_article
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