02084cam a22002658i 45000010009000000050017000090080041000260100017000670200018000840400028001020420008001300500020001380820032001582450141001902600019003312630009003503000015003593360026003743370028004003380027004285040051004555201128005066500092016346500092017262402003520260730150345.0250205s2025    enk      b    001 0 eng    a  2024054711  a9780323950435  aDLCbengerdacDLCdDLC  apcc00aTA357 .D38 202500a629.132/32223/eng/2025021310aData Driven Analysis and Modeling of Turbulent Flows :bData Driven Analysis and Modeling of Turbulent FlowscKarthik Duraisamy (Editor)  bAcademic Press  a2025  a414 Pages.  atextbtxt2rdacontent  aunmediatedbn2rdamedia  avolumebnc2rdacarrier  aIncludes bibliographical references and index.  aData-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 learningcProvided by publisher. 0aTurbulencexMathematical models.2Data Driven Analysis and Modeling of Turbulent Flows  0aTurbulencexStatistical methods.2Data Driven Analysis and Modeling of Turbulent Flows