2017
DOI: 10.1002/fld.4386
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A generalised finite difference scheme based on compact integrated radial basis function for flow in heterogeneous soils

Abstract: Summary In the present paper, we develop a generalised finite difference approach based on compact integrated radial basis function (CIRBF) stencils for solving highly nonlinear Richards equation governing fluid movement in heterogeneous soils. The proposed CIRBF scheme enjoys a high level of accuracy and a fast convergence rate with grid refinement owing to the combination of the integrated RBF approximation and compact approximation where the spatial derivatives are discretised in terms of the information of… Show more

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Cited by 5 publications
(3 citation statements)
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References 38 publications
(112 reference statements)
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“…Instead of using Picard iteration, the extra information of the second derivatives in and can be implicitly calculated using the function values at all nodes on a grid line as shown in Ngo-Cong et al (2017). The values of the second and first derivatives of u against z at the nodal points on the z-grid line are then given by…”
Section: Appendixmentioning
confidence: 99%
“…Instead of using Picard iteration, the extra information of the second derivatives in and can be implicitly calculated using the function values at all nodes on a grid line as shown in Ngo-Cong et al (2017). The values of the second and first derivatives of u against z at the nodal points on the z-grid line are then given by…”
Section: Appendixmentioning
confidence: 99%
“…The RBF approximations can be constructed through differentiation (DRBF) or integration (IRBF). The governing equations of fluid dynamics have been successfully solved by the DRBF- and IRBF-based methods (Mai-Duy and Tanner, 2005, 2007; Dehghan and Shokri, 2008; Kosec and Šarler, 2008, 2013; Mohebbi et al , 2014; Ngo-Cong et al , 2017; Ebrahimijahan and Dehghan, 2021; Ebrahimijahan et al , 2020, 2022a, 2022b; Abbaszadeh et al , 2022; Mesgarani et al , 2022).…”
Section: Introductionmentioning
confidence: 99%
“…Shu & Yeo 26 further proposed the local RBF-DQ method using local supporting nodes. Recently, Tran-Cong and his collaborators, [27][28][29][30][31] further proposed the indirect radial basis function networks (IRBFN). They found that the IRBFN are more stable than the conventional RBF method.…”
Section: Introductionmentioning
confidence: 99%