Data-driven multifidelity surrogate models for rocket engines injector design
Surrogate models of turbulent diffusive flames could play a strategic role in the design of liquid rocket engine combustion chambers. The present article introduces a method to obtain data-driven surrogate models for coaxial injectors, by leveraging an inductive transfer learning strategy over a U-N...
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| Main Authors: | Jose Felix Zapata Usandivaras, Michael Bauerheim, Bénédicte Cuenot, Annafederica Urbano |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
|
| Series: | Data-Centric Engineering |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S263267362400056X/type/journal_article |
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