000 03444nam a22005535i 4500
001 978-3-319-21506-8
003 DE-He213
005 20200420220219.0
007 cr nn 008mamaa
008 151005s2016 gw | s |||| 0|eng d
020 _a9783319215068
_9978-3-319-21506-8
024 7 _a10.1007/978-3-319-21506-8
_2doi
050 4 _aTL787-4050.22
072 7 _aTRP
_2bicssc
072 7 _aTTDS
_2bicssc
072 7 _aTEC002000
_2bisacsh
082 0 4 _a629.1
_223
245 1 0 _aApplication of Surrogate-based Global Optimization to Aerodynamic Design
_h[electronic resource] /
_cedited by Emiliano Iuliano, Esther Andr�es P�erez.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIV, 72 p. 33 illus., 22 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Tracts in Mechanical Engineering,
_x2195-9862
520 _aAerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive - this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogate and reduced-order models can provide a valuable alternative at a much lower computational cost. In this context, this volume offers advanced surrogate modeling applications and optimization techniques featuring reasonable computational resources. It also discusses basic theory concepts and their application to aerodynamic design cases. It is aimed at researchers and engineers who deal with complex aerodynamic design problems on a daily basis and employ expensive simulations to solve them.
650 0 _aEngineering.
650 0 _aComputer simulation.
650 0 _aFluid mechanics.
650 0 _aEngineering design.
650 0 _aAerospace engineering.
650 0 _aAstronautics.
650 1 4 _aEngineering.
650 2 4 _aAerospace Technology and Astronautics.
650 2 4 _aEngineering Fluid Dynamics.
650 2 4 _aEngineering Design.
650 2 4 _aSimulation and Modeling.
700 1 _aIuliano, Emiliano.
_eeditor.
700 1 _aP�erez, Esther Andr�es.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319215051
830 0 _aSpringer Tracts in Mechanical Engineering,
_x2195-9862
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-21506-8
912 _aZDB-2-ENG
942 _cEBK
999 _c51807
_d51807