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Found 4 papers, 1 papers with code
A predictive physics-aware hybrid reduced order model for reacting flows
The number of degrees of freedom is reduced from thousands of temporal points to a few POD modes with their corresponding temporal coefficients.
Improving aircraft performance using machine learning: a review
This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (experimental and numerical), aerodynamics, acoustics, combustion and structural health monitoring.
Advancing Reacting Flow Simulations with Data-Driven Models
The use of machine learning algorithms to predict behaviors of complex systems is booming.
Local manifold learning and its link to domain-based physics knowledge
In this paper, we show that PCA applied in local clusters of data (local PCA) is capable of detecting the intrinsic parameterization of the thermo-chemical state-space.
