2020
DOI: 10.48550/arxiv.2012.13418
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Error estimates for the Scaled Boundary Finite Element Method

Karolinne O. Coelho,
Philippe R. B. Devloo,
Sonia M. Gomes

Abstract: The Scaled Boundary Finite Element Method (SBFEM) is a technique in which approximation spaces are constructed using a semi-analytical approach. They are based on partitions of the computational domain by polygonal/polyhedral subregions, where the shape functions approximate local Dirichlet problems with piecewise polynomial trace data. Using this operator adaptation approach, and by imposing a starlike scaling requirement on the subregions, the representation of local SBFEM shape functions in radial and surfa… Show more

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Cited by 1 publication
(1 citation statement)
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“…The SBFEM is in its core nature a semi-analytical method which was first proposed by Wolf and Song [4,6] for modeling wave propagation in unbounded domains. However, over the last two decades, the SBFEM has been extended to various types of analyses including wave propagation in bounded domains [7], fracture mechanics [8,9,10], acoustics [11,12], contact mechanics [13,14], seepage [15], elasto-plasticity [16], damage analysis [17], adaptive analysis [18,19], among many others [20,21,22,23]. Due to its versatility and applicability to a wide class of problems, the SBFEM can be seen as a general numerical method to solve PDEs.…”
Section: Introductionmentioning
confidence: 99%
“…The SBFEM is in its core nature a semi-analytical method which was first proposed by Wolf and Song [4,6] for modeling wave propagation in unbounded domains. However, over the last two decades, the SBFEM has been extended to various types of analyses including wave propagation in bounded domains [7], fracture mechanics [8,9,10], acoustics [11,12], contact mechanics [13,14], seepage [15], elasto-plasticity [16], damage analysis [17], adaptive analysis [18,19], among many others [20,21,22,23]. Due to its versatility and applicability to a wide class of problems, the SBFEM can be seen as a general numerical method to solve PDEs.…”
Section: Introductionmentioning
confidence: 99%