000			03899nam a22003735i 4500
001			104037
003			DE-He213
005			20230102113156.0
007			cr nn 008mamaa
008			150219s2015 gw | s |||| 0|eng d
020			_a9783319146812
024	7		_a10.1007/978-3-319-14681-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
050		4	_aTL701 2015 EB
100	1		_aMontomoli, Francesco _eautor _9669772
245	1	0	_aUncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines _cby Francesco Montomoli, Mauro Carnevale, Antonio D'Ammaro, Michela Massini, Simone Salvadori.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XIII, 90 páginas 49 ilustraciones, 31 ilustraciones a color.)
490	0		_aSpringerBriefs in Applied Sciences and Technology _x2191-530X
505	0		_aManufacturing in Service Uncertainty and Impact on Life and Performance -- Limitations in Turbomachinery CFD -- Uncertainty Quantification Applied to Gas Turbine Components -- Overview of Uncertainty Quantification Methods -- Future Developments.
520	3		_aThis book introduces novel design techniques developed to increase the safety of aircraft engines. The authors demonstrate how the application of uncertainty methods can overcome problems in the accurate prediction of engine lift, caused by manufacturing error. This in turn ameliorates the difficulty of achieving required safety margins imposed by limits in current design and manufacturing methods. This text shows that even state-of-the-art computational fluid dynamics (CFD) are not able to predict the same performance measured in experiments; CFD methods assume idealised geometries but ideal geometries do not exist, cannot be manufactured and their performance differs from real-world ones. By applying geometrical variations of a few microns, the agreement with experiments improves dramatically, but unfortunately the manufacturing errors in engines or in experiments are unknown. In order to overcome this limitation, uncertainty quantification considers the probability density functions of manufacturing errors. It is then possible to predict the overall variation of the jet engine performance using stochastic techniques. Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines demonstrates that some geometries are not affected by manufacturing errors, meaning that it is possible to design safer engines. Instead of trying to improve the manufacturing accuracy, uncertainty quantification when applied to CFD is able to indicate an improved design direction. This book will be of interest to  gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students may also find it of use.
650		7	_aAviones _xMotores _vDiseño y construcción _2embne _9189176
650		7	_aIncertidumbre (Teoría de la información) _667868 _2embne _9667868
700	1		_aCarnevale, Mauro _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/764145858160323022497/
700	1		_aD'Ammaro, Antonio _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aMassini, Michela _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/531145857919123020437/
700	1		_aSalvadori, Simone _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/407145857931923020280/
776	0	8	_iEdición impresa: _z9783319146829
776	0	8	_iEdición impresa: _z9783319146805
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-14681-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b06/2019 _dz _ek _feng _ggw _h0
999			_c104037 _d104037 _x1