Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	November 2019
Genre:	Naturwissensch., Medizin, Technik
	C / Classical and Continuum Physics / engineering / Engineering Fluid Dynamics / Fluid mechanics / Fluid- and Aerodynamics / Fluids / Mathematical physics / Numerical and Computational Physics, Simulation / Physics / Theoretical, Mathematical and Computational Physics
ISBN:	9783030276065
EAN-Code:	9783030276065
Verlag:	Springer Nature EN
Einband:	Gebunden
Sprache:	English
Serie:	#143 - Notes on Numerical Fluid Mechanics and Multidisciplinary Design
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	799 gr
Seiten:	412
Illustration:	X, 412 p. 314 illus., 273 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book gathers the proceedings of the Seventh Symposium on Hybrid RANS-LES Methods, which was held on September 17-19 in Berlin, Germany. The different chapters, written by leading experts, reports on the most recent developments in flow physics modelling, and gives a special emphasis to industrially relevant applications of hybrid RANS-LES methods and other turbulence-resolving modelling approaches. The book addresses academic researchers, graduate students, industrial engineers, as well as industrial R&D managers and consultants dealing with turbulence modelling, simulation and measurement, and with multidisciplinary applications of computational fluid dynamics (CFD), such as flow control, aero-acoustics, aero-elasticity and CFD-based multidisciplinary optimization. It discusses in particular advanced hybrid RANS-LES methods. Further topics include wall-modelled Large Eddy Simulation (WMLES) methods, embedded LES, Lattice-Bolzman methods and turbulence-resolving applications and a comparison of the LES methods with both hybrid RANS-LES and URANS methods. Overall, the book provides readers with a snapshot on the state-of-the-art in CFD and turbulence modelling, with a special focus to hybrid RANS-LES methods and their industrial applications.