A New Application of Dynamic Data Driven System in the Talbot-Ogden Model for Groundwater Infiltration
KAUST DepartmentPhysical Sciences and Engineering (PSE) Division
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AbstractThe TalbotOgden model is a mass conservative method to simulate flow of a wetting liquid in variably-saturated porous media. The principal feature of this model is the discretization of the moisture content domain into bins. This paper gives an analysis of the relationship between the number of bins and the computed flux. Under the circumstances of discrete bins and discontinuous wetting fronts, we show that fluxes increase with the number of bins. We then apply this analysis to the continuous case and get an upper bound of the difference of infiltration rates when the number of bins tends to infinity. We also extend this model by creating a two dimensional moisture content domain so that there exists a probability distribution of the moisture content for different soil systems. With these theoretical and experimental results and using a Dynamic Data Driven Application System (DDDAS), sensors can be put in soils to detect the infiltration fluxes, which are important to compute the proper number of bins for a specific soil system and predict fluxes. Using this feedback control loop, the extended TalbotOgden model can be made more efficient for estimating infiltration into soils.
CitationA New Application of Dynamic Data Driven System in the Talbot-Ogden Model for Groundwater Infiltration 2012, 9:1073 Procedia Computer Science
JournalProcedia Computer Science
Conference/Event name12th Annual International Conference on Computational Science, ICCS 2012