Interpolation and update in dynamic data-driven application simulations Academic Article

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. Springer 2007.

authors

• Efendiev, Yalchin
• Lazarov, Raytcho

published proceedings

• AIR, WATER AND SOIL QUALITY MODELLING FOR RISK AND IMPACT ASSESSMENT

author list (cited authors)

• Douglas, C. C., Efendiev, Y., Ewing, R., Lazarov, R., Cole, M. J., Jones, G., & Johnson, C. R.

citation count

• 4

complete list of authors

• Douglas, Craig C||Efendiev, Yalchin||Ewing, Richard||Lazarov, Raytcho||Cole, Martin J||Jones, Greg||Johnson, Chris R

publication date

• January 2007

publisher

• Springer Nature  Publisher

published in

• NATO Security through Science Series C: Environmental Security  Journal

keywords

• Dynamic Data Driven Application
• Multiscale
• Porous Inedia
• Update

Digital Object Identifier (DOI)

• 10.1007/978-1-4020-5877-6_22

start page

• 235

end page

• +

URL

• http://dx.doi.org/10.1007/978-1-4020-5877-6_22