000			02511nam a2200361 i 4500
001			CR9781108896214
003			UkCbUP
005			20240730160810.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			200108s2023||||enk o ||1 0|eng|d
020			_a9781108896214 (ebook)
020			_z9781108842143 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA901 _b.D375 2023
082	0	0	_a532 _223
245	0	0	_aData-driven fluid mechanics : _bcombining first principles and machine learning : based on a von Karman Institute lecture series / _cedited by Miguel A. Mendez, Andrea Ianiro, Bernd R. Noack, Steven L. Brunton.
264		1	_aCambridge : _bCambridge University Press, _c2023.
300			_a1 online resource (xviii, 448 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 12 Jan 2023).
520			_aData-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.
650		0	_aFluid mechanics _xData processing. _974846
700	1		_aMendez, Miguel Alfonso, _eeditor. _974847
700	1		_aIaniro, Andrea, _eeditor. _974848
700	1		_aNoack, Bernd R., _eeditor. _974849
700	1		_aBrunton, Steven L. _q(Steven Lee), _d1984- _eeditor. _974850
776	0	8	_iPrint version: _z9781108842143
856	4	0	_uhttps://doi.org/10.1017/9781108896214
942			_cEBK
999			_c84271 _d84271