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Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning free ebook download

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Mechanical Engineering

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Catalogue

Author(s):	Miguel A. Mendez, Andrea Ianiro, Bernd R. Noack

Date:	2023	Format:	PDF	Language:	English	ISBN/ASIN:	1108842143
Pages:	468	OCR:		Quality:		ISBN13:
Uploader:	rubybook	Upload Date:	1/25/2023 4:47:30 AM

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Data-driven methods have become an essential part of the methodological portfolio of fluid dynamicists, motivating students and practitioners to gather practical knowledge from a diverse range of disciplines. These fields include computer science, statistics, optimization, signal processing, pattern recognition, nonlinear dynamics, and control. Fluid mechanics is historically a big data field and offers a fertile ground for developing and applying data-driven methods, while also providing valuable shortcuts, constraints, and interpretations based on its powerful connections to basic physics. Thus, hybrid approaches that leverage both methods based on data as well as fundamental principles are the focus of active and exciting research. Originating from a one-week lecture series course by the von Karman Institute for Fluid Dynamics, this book presents an overview and a pedagogical treatment of some of the data-driven and machine learning tools that are leading research advancements in model-order reduction, system identification, flow control, and data-driven turbulence closures.

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3169501	Book	https://nitroflare.com/view/4F4AB5540796...		30.00	rubybook

Tags: Combining Data-Driven Fluid Learning Machine Mechanics Principles

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Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning free ebook download

Category: Mechanical Engineering

Description: Click to see full description

Category:
Mechanical Engineering