Data Driven Analysis and Modeling of Turbulent Flows
Paperback Engels 2025 9780323950435Samenvatting
Data-driven Analysis and Modeling of Turbulent Flows provides an integrated treatment of modern data-driven methods to describe, control, and predict turbulent flows through the lens of both physics and data science.
The book is organized into three parts:Exploration of techniques for discovering coherent structures within turbulent flows, introducing advanced decomposition methodsMethods for estimation and control using data assimilation and machine learning approachesFinally, novel modeling techniques that combine physical insights with machine learningThis book is intended for students, researchers, and practitioners in fluid mechanics, though readers from related fields such as applied mathematics, computational science, and machine learning will find it also of interest.
Specificaties
Lezersrecensies
Inhoudsopgave
2. Modal Decomposition
3. Resolvent analysis for turbulent flows
4. Data assimilation and flow estimation
5. Data-driven control
6. Constitutive Modeling
7. Parameter estimation and uncertainty quantification
8. Machine Learning Augmented modeling
9. Symbolic regression methods
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