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Boundary layer challenges: A comparative analysis of two efficient meshless approaches

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dc.citedby1
dc.contributor.authorAlshammari A.O.en_US
dc.contributor.authorKhan M.N.en_US
dc.contributor.authorAhmad I.en_US
dc.contributor.authorid59156924200en_US
dc.contributor.authorid57205304990en_US
dc.contributor.authorid57220824630en_US
dc.date.accessioned2025-03-03T07:43:05Z
dc.date.available2025-03-03T07:43:05Z
dc.date.issued2024
dc.description.abstractThis article presents two meshless computational techniques: the radial basis function (RBF) method and the polynomial method, for numerically analyzing boundary layer problems, with a specific focus on singularly perturbed two-point boundary value problems. Both of these suggested meshless methods offer an advantage over globally supported meshless techniques, as they involve approximating derivatives by employing a constrained set of nodes located in the neighborhood of each collocation node. As a result, they demand significantly reduced computational effort compared to the globally supported collocation method. To assess the accuracy of these methods, we employ the maximum error norm, and the results are presented in the form of tables and graphs. The simulation results demonstrate that both approaches exhibit robust performance in addressing the investigated boundary layer problems. ? 2024 The Author(s)en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo100743
dc.identifier.doi10.1016/j.padiff.2024.100743
dc.identifier.scopus2-s2.0-85195210383
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85195210383&doi=10.1016%2fj.padiff.2024.100743&partnerID=40&md5=3941f0c5f708c81a94d443fac1dede8e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36562
dc.identifier.volume10
dc.publisherElsevier B.V.en_US
dc.relation.ispartofAll Open Access; Gold Open Access
dc.sourceScopus
dc.sourcetitlePartial Differential Equations in Applied Mathematics
dc.titleBoundary layer challenges: A comparative analysis of two efficient meshless approachesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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