Reduced order modelling of intracranial aneurysm flow using proper orthogonal decomposition and neural networks
Michael MacRaild,
Ali Sarrami‐Foroushani,
Toni Lassila
et al.
Abstract:Reduced order modelling (ROMs) methods, such as proper orthogonal decomposition (POD), systematically reduce the dimensionality of high‐fidelity computational models and potentially achieve large gains in execution speed. Machine learning (ML) using neural networks has been used to overcome limitations of traditional ROM techniques when applied to nonlinear problems, which has led to the recent development of reduced order models augmented by machine learning (ML‐ROMs). However, the performance of ML‐ROMs is y… Show more
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