000			02254cam a22003138i 4500
001			24020035
005			20260730150345.0
008			250205s2025 enk b 001 0 eng
010			_a 2024054711
020			_a9780323950435
040			_aDLC _beng _erda _cDLC _dDLC
042			_apcc
050	0	0	_aTA357 .D38 2025
082	0	0	_a629.132/32 _223/eng/20250213
245	1	0	_aData Driven Analysis and Modeling of Turbulent Flows : _bData Driven Analysis and Modeling of Turbulent Flows _cKarthik Duraisamy (Editor)
260			_bAcademic Press
263			_a2025
300			_a414 Pages.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_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 learning _cProvided by publisher.
650		0	_aTurbulence _xMathematical models. _2Data Driven Analysis and Modeling of Turbulent Flows
650		0	_aTurbulence _xStatistical methods. _2Data Driven Analysis and Modeling of Turbulent Flows
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBOOK
999			_c13004 _d13004