Machine-Learning Methods for Complex Flows

We are delighted to introduce this Special Issue focused on novel machine-learning (ML) methods aimed at predicting, modeling, and controlling a variety of complex fluid flow scenarios [...]

Bibliographic Details
Main Authors: Ricardo Vinuesa, Soledad Le Clainche
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Energies
Subjects:
n/a
Online Access:https://www.mdpi.com/1996-1073/15/4/1513
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author Ricardo Vinuesa
Soledad Le Clainche
author_facet Ricardo Vinuesa
Soledad Le Clainche
author_sort Ricardo Vinuesa
collection DOAJ
description We are delighted to introduce this Special Issue focused on novel machine-learning (ML) methods aimed at predicting, modeling, and controlling a variety of complex fluid flow scenarios [...]
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spelling doaj.art-891d1e16bdea47ce88da2cb4b3f0176a2023-11-23T19:45:22ZengMDPI AGEnergies1996-10732022-02-01154151310.3390/en15041513Machine-Learning Methods for Complex FlowsRicardo Vinuesa0Soledad Le Clainche1FLOW, Engineering Mechanics, KTH Royal Institute of Technology, 114 28 Stockholm, SwedenSchool of Aerospace Engineering, Universidad Politécnica de Madrid, 28040 Madrid, SpainWe are delighted to introduce this Special Issue focused on novel machine-learning (ML) methods aimed at predicting, modeling, and controlling a variety of complex fluid flow scenarios [...]https://www.mdpi.com/1996-1073/15/4/1513n/a
spellingShingle Ricardo Vinuesa
Soledad Le Clainche
Machine-Learning Methods for Complex Flows
Energies
n/a
title Machine-Learning Methods for Complex Flows
title_full Machine-Learning Methods for Complex Flows
title_fullStr Machine-Learning Methods for Complex Flows
title_full_unstemmed Machine-Learning Methods for Complex Flows
title_short Machine-Learning Methods for Complex Flows
title_sort machine learning methods for complex flows
topic n/a
url https://www.mdpi.com/1996-1073/15/4/1513
work_keys_str_mv AT ricardovinuesa machinelearningmethodsforcomplexflows
AT soledadleclainche machinelearningmethodsforcomplexflows