Front transport reduction for complex moving fronts: Nonlinear model reduction for an advection–reaction–diffusion equation with a Kolmogorov–Petrovsky–Piskunov …
This work addresses model order reduction for complex moving fronts, which are
transported by advection or through a reaction–diffusion process. Such systems are …
transported by advection or through a reaction–diffusion process. Such systems are …
[HTML][HTML] ModelFLOWs-app: data-driven post-processing and reduced order modelling tools
A Hetherington, A Corrochano… - Computer Physics …, 2024 - Elsevier
This article presents an innovative open-source software named ModelFLOWs-app, 1
written in Python, which has been created and tested to generate precise and robust hybrid …
written in Python, which has been created and tested to generate precise and robust hybrid …
[HTML][HTML] Data repairing and resolution enhancement using data-driven modal decomposition and deep learning
A Hetherington, D Serfaty, A Corrochano, J Soria… - … Thermal and Fluid …, 2024 - Elsevier
This paper introduces a new series of methods which combine modal decomposition
algorithms, such as singular value decomposition and high-order singular value …
algorithms, such as singular value decomposition and high-order singular value …
Exploring the efficacy of a hybrid approach with modal decomposition over fully deep learning models for flow dynamics forecasting
R Abadía-Heredia, A Corrochano… - arXiv preprint arXiv …, 2024 - arxiv.org
Fluid dynamics problems are characterized by being multidimensional and nonlinear,
causing the experiments and numerical simulations being complex, time-consuming and …
causing the experiments and numerical simulations being complex, time-consuming and …
LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements
A Hetherington, JL Leonés, SL Clainche - arXiv preprint arXiv:2411.17433, 2024 - arxiv.org
This article introduces a novel methodology that integrates singular value decomposition
(SVD) with a shallow linear neural network for forecasting high resolution fluid mechanics …
(SVD) with a shallow linear neural network for forecasting high resolution fluid mechanics …
Low-cost singular value decomposition with optimal sensor placement
A Hetherington, SL Clainche - arXiv preprint arXiv:2311.09791, 2023 - arxiv.org
This paper presents a new method capable of reconstructing datasets with great precision
and very low computational cost using a novel variant of the singular value decomposition …
and very low computational cost using a novel variant of the singular value decomposition …