p-Adaptive Refinement Based on Stress Recovery Technique Considering Ordinary Kriging Interpolation in L-Shaped Domain
| Autor: | Kwang S. Woo, Jae S. Ahn |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Polynomial
Mathematical optimization Article Subject General Mathematics lcsh:Mathematics General Engineering Estimator Basis function 02 engineering and technology Superconvergence lcsh:QA1-939 01 natural sciences Finite element method 010101 applied mathematics 020303 mechanical engineering & transports 0203 mechanical engineering Kriging lcsh:TA1-2040 Applied mathematics 0101 mathematics lcsh:Engineering (General). Civil engineering (General) Legendre polynomials Mathematics Interpolation |
| Zdroj: | Mathematical Problems in Engineering, Vol 2017 (2017) |
| ISSN: | 1563-5147 |
| Popis: | The primary objectives of this study are twofold. Firstly, the original SPR method of stress recovery has been modified by incorporating the kriging interpolation technique to fit a polynomial to the derivatives recovered at the Gauss points. For this purpose, the p-version of finite element analysis is performed to produce the stresses at the fixed 10×10 Gauss points where the integrals of Legendre polynomials are used as a basis function. In contrast to the conventional least square method for stress recovery, the weight factor is determined by experimental and theoretical variograms for interpolation of stress data, unlike the conventional interpolation methods that use an equal weight factor. Secondly, an adaptive procedure for hierarchical p-refinement in conjunction with a posteriori error based on the modified SPR (superconvergent patch recovery) method is proposed. Thirdly, a new error estimator based on the limit value approach is proposed by predicting the exact strain energy to verify the kriging-based SPR method. The validity of the proposed approach has been tested by analyzing two-dimensional plates with a rectangular cutout in the presence of stress singularity. |
| Databáze: | OpenAIRE |
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