語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Polynomial Chaos Methods for Hyperbo...
~
Iaccarino, Gianluca.
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations = Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations/ by Mass Per Pettersson, Gianluca Iaccarino, Jan Nordström.
其他題名:
Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /
作者:
Pettersson, Mass Per.
其他作者:
Iaccarino, Gianluca.
面頁冊數:
XI, 214 p. 60 illus., 54 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Fluid mechanics. -
電子資源:
https://doi.org/10.1007/978-3-319-10714-1
ISBN:
9783319107141
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations = Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /
Pettersson, Mass Per.
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations
Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /[electronic resource] :by Mass Per Pettersson, Gianluca Iaccarino, Jan Nordström. - 1st ed. 2015. - XI, 214 p. 60 illus., 54 illus. in color.online resource. - Mathematical Engineering,2192-4732. - Mathematical Engineering,.
Random Field Representation -- Polynomial Chaos Methods -- Numerical Solution of Hyperbolic Problems -- Linear Transport -- Nonlinear Transport -- Boundary Conditions and Data -- Euler Equations -- A Hybrid Scheme for Two-Phase Flow -- Appendices.
This monograph presents computational techniques and numerical analysis to study conservation laws under uncertainty using the stochastic Galerkin formulation. With the continual growth of computer power, these methods are becoming increasingly popular as an alternative to more classical sampling-based techniques. The approach described in the text takes advantage of stochastic Galerkin projections applied to the original conservation laws to produce a large system of modified partial differential equations, the solutions to which directly provide a full statistical characterization of the effect of uncertainties. Polynomial Chaos Methods of Hyperbolic Partial Differential Equations focuses on the analysis of stochastic Galerkin systems obtained for linear and non-linear convection-diffusion equations and for a systems of conservation laws; a detailed well-posedness and accuracy analysis is presented to enable the design of robust and stable numerical methods. The exposition is restricted to one spatial dimension and one uncertain parameter as its extension is conceptually straightforward. The numerical methods designed guarantee that the solutions to the uncertainty quantification systems will converge as the mesh size goes to zero. Examples from computational fluid dynamics are presented together with numerical methods suitable for the problem at hand: stable high-order finite-difference methods based on summation-by-parts operators for smooth problems, and robust shock-capturing methods for highly nonlinear problems. Academics and graduate students interested in computational fluid dynamics and uncertainty quantification will find this book of interest. Readers are expected to be familiar with the fundamentals of numerical analysis. Some background in stochastic methods is useful but not necessary.
ISBN: 9783319107141
Standard No.: 10.1007/978-3-319-10714-1doiSubjects--Topical Terms:
555551
Fluid mechanics.
LC Class. No.: TA357-359
Dewey Class. No.: 620.1064
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations = Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /
LDR
:03610nam a22004095i 4500
001
963614
003
DE-He213
005
20200705003005.0
007
cr nn 008mamaa
008
201211s2015 gw | s |||| 0|eng d
020
$a
9783319107141
$9
978-3-319-10714-1
024
7
$a
10.1007/978-3-319-10714-1
$2
doi
035
$a
978-3-319-10714-1
050
4
$a
TA357-359
072
7
$a
TGMF
$2
bicssc
072
7
$a
TEC009070
$2
bisacsh
072
7
$a
TGMF
$2
thema
082
0 4
$a
620.1064
$2
23
100
1
$a
Pettersson, Mass Per.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1258651
245
1 0
$a
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations
$h
[electronic resource] :
$b
Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties /
$c
by Mass Per Pettersson, Gianluca Iaccarino, Jan Nordström.
250
$a
1st ed. 2015.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2015.
300
$a
XI, 214 p. 60 illus., 54 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Mathematical Engineering,
$x
2192-4732
505
0
$a
Random Field Representation -- Polynomial Chaos Methods -- Numerical Solution of Hyperbolic Problems -- Linear Transport -- Nonlinear Transport -- Boundary Conditions and Data -- Euler Equations -- A Hybrid Scheme for Two-Phase Flow -- Appendices.
520
$a
This monograph presents computational techniques and numerical analysis to study conservation laws under uncertainty using the stochastic Galerkin formulation. With the continual growth of computer power, these methods are becoming increasingly popular as an alternative to more classical sampling-based techniques. The approach described in the text takes advantage of stochastic Galerkin projections applied to the original conservation laws to produce a large system of modified partial differential equations, the solutions to which directly provide a full statistical characterization of the effect of uncertainties. Polynomial Chaos Methods of Hyperbolic Partial Differential Equations focuses on the analysis of stochastic Galerkin systems obtained for linear and non-linear convection-diffusion equations and for a systems of conservation laws; a detailed well-posedness and accuracy analysis is presented to enable the design of robust and stable numerical methods. The exposition is restricted to one spatial dimension and one uncertain parameter as its extension is conceptually straightforward. The numerical methods designed guarantee that the solutions to the uncertainty quantification systems will converge as the mesh size goes to zero. Examples from computational fluid dynamics are presented together with numerical methods suitable for the problem at hand: stable high-order finite-difference methods based on summation-by-parts operators for smooth problems, and robust shock-capturing methods for highly nonlinear problems. Academics and graduate students interested in computational fluid dynamics and uncertainty quantification will find this book of interest. Readers are expected to be familiar with the fundamentals of numerical analysis. Some background in stochastic methods is useful but not necessary.
650
0
$a
Fluid mechanics.
$3
555551
650
0
$a
Numerical analysis.
$3
527939
650
0
$a
Fluids.
$3
671110
650
1 4
$a
Engineering Fluid Dynamics.
$3
670525
650
2 4
$a
Numerical Analysis.
$3
671433
650
2 4
$a
Fluid- and Aerodynamics.
$3
768779
700
1
$a
Iaccarino, Gianluca.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1258652
700
1
$a
Nordström, Jan.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1258653
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319107158
776
0 8
$i
Printed edition:
$z
9783319107134
776
0 8
$i
Printed edition:
$z
9783319356129
830
0
$a
Mathematical Engineering,
$x
2192-4732
$3
1255094
856
4 0
$u
https://doi.org/10.1007/978-3-319-10714-1
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入