Data Driven Analysis and Modeling of Turbulent Flows
Series: Computation and Analysis of Turbulent Flows;
- Publisher's listprice EUR 195.00
-
82 719 Ft (78 780 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 8 272 Ft off)
- Discounted price 74 447 Ft (70 902 Ft + 5% VAT)
82 719 Ft
Availability
Not yet published.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher Academic Press
- Date of Publication 18 April 2025
- ISBN 9780323950435
- Binding Paperback
- No. of pages414 pages
- Size 229x152 mm
- Language English 700
Categories
Long description:
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 methods
. Methods for estimation and control using data assimilation and machine learning approaches
. Finally, novel modeling techniques that combine physical insights with machine learning
This 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.
. Exploration of techniques for discovering coherent structures within turbulent flows, introducing advanced decomposition methods
. Methods for estimation and control using data assimilation and machine learning approaches
. Finally, novel modeling techniques that combine physical insights with machine learning
Table of Contents:
1. Introduction to data-driven modeling
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
