Sobol indices for dimension adaptivity in sparse grids

Richard P. Dwight; S de Smedt; Pejman Shoeibi Omrani

doi:10.1007/978-3-319-27517-8_15

Sobol indices for dimension adaptivity in sparse grids

Richard P. Dwight^*, S de Smedt, Pejman Shoeibi Omrani

^*Corresponding author for this work

Aerodynamics

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

4 Citations (Scopus)

Abstract

Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to conventional adaptation schemes on sparse grids (Gerstner and Griebel, Computing 71(1), 65-87, 2003), and seen to perform comparably,without requiring the expense associated with a look-ahead error estimate. It is demonstrated for an expensive computer model of contaminant flow over a barrier.

Original language	English
Title of host publication	Simulation-Driven Modeling and Optimization - ASDOM 2014
Publisher	Springer
Pages	371-395
Number of pages	25
Volume	153
ISBN (Print)	9783319275154
DOIs	https://doi.org/10.1007/978-3-319-27517-8_15
Publication status	Published - 2016
Event	3rd Workshop on Advances in Simulation-Driven Optimization and Modeling - Reykjavik, Iceland Duration: 8 Aug 2014 → 10 Aug 2014 Conference number: 3

Conference

Conference	3rd Workshop on Advances in Simulation-Driven Optimization and Modeling
Abbreviated title	ASDOM 2014
Country/Territory	Iceland
City	Reykjavik
Period	8/08/14 → 10/08/14

Keywords

CFD
Navier-stokes
Surrogate modelling
Uncertainity quantification

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10.1007/978-3-319-27517-8_15

Cite this

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title = "Sobol indices for dimension adaptivity in sparse grids",

abstract = "Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to conventional adaptation schemes on sparse grids (Gerstner and Griebel, Computing 71(1), 65-87, 2003), and seen to perform comparably,without requiring the expense associated with a look-ahead error estimate. It is demonstrated for an expensive computer model of contaminant flow over a barrier.",

keywords = "CFD, Navier-stokes, Surrogate modelling, Uncertainity quantification",

author = "Dwight, {Richard P.} and {de Smedt}, S and Omrani, {Pejman Shoeibi}",

year = "2016",

doi = "10.1007/978-3-319-27517-8_15",

language = "English",

isbn = "9783319275154",

volume = "153",

pages = "371--395",

booktitle = "Simulation-Driven Modeling and Optimization - ASDOM 2014",

publisher = "Springer",

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T1 - Sobol indices for dimension adaptivity in sparse grids

AU - Dwight, Richard P.

AU - de Smedt, S

AU - Omrani, Pejman Shoeibi

N1 - Conference code: 3

PY - 2016

Y1 - 2016

N2 - Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to conventional adaptation schemes on sparse grids (Gerstner and Griebel, Computing 71(1), 65-87, 2003), and seen to perform comparably,without requiring the expense associated with a look-ahead error estimate. It is demonstrated for an expensive computer model of contaminant flow over a barrier.

AB - Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to conventional adaptation schemes on sparse grids (Gerstner and Griebel, Computing 71(1), 65-87, 2003), and seen to perform comparably,without requiring the expense associated with a look-ahead error estimate. It is demonstrated for an expensive computer model of contaminant flow over a barrier.

KW - CFD

KW - Navier-stokes

KW - Surrogate modelling

KW - Uncertainity quantification

UR - http://www.scopus.com/inward/record.url?scp=84990966830&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-27517-8_15

DO - 10.1007/978-3-319-27517-8_15

M3 - Conference contribution

AN - SCOPUS:84990966830

SN - 9783319275154

VL - 153

SP - 371

EP - 395

BT - Simulation-Driven Modeling and Optimization - ASDOM 2014

PB - Springer

T2 - 3rd Workshop on Advances in Simulation-Driven Optimization and Modeling

Y2 - 8 August 2014 through 10 August 2014

ER -

Sobol indices for dimension adaptivity in sparse grids

Abstract

Conference

Keywords

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