Interpolation and update in dynamic data-driven application simulations

Craig C. Douglas; Yalchin Efendiev; Richard Ewing; Raytcho Lazarov; Martin J. Cole; Greg Jones; Chris R. Johnson

doi:10.1007/978-1-4020-5877-6_22

Interpolation and update in dynamic data-driven application simulations

Craig C. Douglas, Yalchin Efendiev^*, Richard Ewing, Raytcho Lazarov, Martin J. Cole, Greg Jones, Chris R. Johnson

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Scopus citations

Abstract

In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can significantly improve the prediction results and thus important for applications. The frequency of sensor data updating in the simulations is related to streaming capabilities and addressed within DDDAS framework (Douglas et al., 2003). We discuss the update of permeability and initial data.

Original language	English (US)
Title of host publication	Air, Water and Soil Quality Modelling for Risk and Impact Assessment
Pages	235-246
Number of pages	12
DOIs	https://doi.org/10.1007/978-1-4020-5877-6_22
State	Published - 2007
Externally published	Yes

Publication series

Name	NATO Security through Science Series C: Environmental Security
ISSN (Print)	1871-4668

Keywords

Dynamic data driven application
Multiscale
Porous media
Update

ASJC Scopus subject areas

General Environmental Science

Access to Document

10.1007/978-1-4020-5877-6_22

Cite this

Douglas, C. C., Efendiev, Y., Ewing, R., Lazarov, R., Cole, M. J., Jones, G., & Johnson, C. R. (2007). Interpolation and update in dynamic data-driven application simulations. In Air, Water and Soil Quality Modelling for Risk and Impact Assessment (pp. 235-246). (NATO Security through Science Series C: Environmental Security). https://doi.org/10.1007/978-1-4020-5877-6_22

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title = "Interpolation and update in dynamic data-driven application simulations",

abstract = "In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can significantly improve the prediction results and thus important for applications. The frequency of sensor data updating in the simulations is related to streaming capabilities and addressed within DDDAS framework (Douglas et al., 2003). We discuss the update of permeability and initial data.",

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author = "Douglas, {Craig C.} and Yalchin Efendiev and Richard Ewing and Raytcho Lazarov and Cole, {Martin J.} and Greg Jones and Johnson, {Chris R.}",

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language = "English (US)",

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Interpolation and update in dynamic data-driven application simulations. / Douglas, Craig C.; Efendiev, Yalchin; Ewing, Richard et al.
Air, Water and Soil Quality Modelling for Risk and Impact Assessment. 2007. p. 235-246 (NATO Security through Science Series C: Environmental Security).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Interpolation and update in dynamic data-driven application simulations

AU - Douglas, Craig C.

AU - Efendiev, Yalchin

AU - Ewing, Richard

AU - Lazarov, Raytcho

AU - Cole, Martin J.

AU - Jones, Greg

AU - Johnson, Chris R.

PY - 2007

Y1 - 2007

N2 - In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can significantly improve the prediction results and thus important for applications. The frequency of sensor data updating in the simulations is related to streaming capabilities and addressed within DDDAS framework (Douglas et al., 2003). We discuss the update of permeability and initial data.

AB - In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can significantly improve the prediction results and thus important for applications. The frequency of sensor data updating in the simulations is related to streaming capabilities and addressed within DDDAS framework (Douglas et al., 2003). We discuss the update of permeability and initial data.

KW - Dynamic data driven application

KW - Multiscale

KW - Porous media

KW - Update

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U2 - 10.1007/978-1-4020-5877-6_22

DO - 10.1007/978-1-4020-5877-6_22

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SN - 1402058756

SN - 9781402058752

T3 - NATO Security through Science Series C: Environmental Security

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EP - 246

BT - Air, Water and Soil Quality Modelling for Risk and Impact Assessment

ER -

Interpolation and update in dynamic data-driven application simulations

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

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