A component-based reduced-order modeling framework decomposes multi-injector rocket combustors into trainable sub-models that couple to predict combustion dynamics across flow and geometry changes.
Deep Learning for Scalable Chemical Kinetics
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A critical review of AI surrogate models for multiscale combustion that compares supervised, unsupervised, and physics-guided methods, identifies transferability and consistency challenges, and outlines future opportunities.
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Component-Based Reduced-Order Modeling Framework for Rocket Combustion Dynamics in Multi-Injector Configurations
A component-based reduced-order modeling framework decomposes multi-injector rocket combustors into trainable sub-models that couple to predict combustion dynamics across flow and geometry changes.
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AI-Powered Surrogate Modelling for Multiscale Combustion: A Critical Review and Opportunities
A critical review of AI surrogate models for multiscale combustion that compares supervised, unsupervised, and physics-guided methods, identifies transferability and consistency challenges, and outlines future opportunities.