Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method
A new approach based on the multi-dimensional Lagrangian interpolation method, which is widely used in the finite element method, is proposed for the prediction of stress concentration factor for tubular joints. When comparing with the parametric regression method, this new method uses the same set...
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sg-ntu-dr.10356-1022292020-03-07T11:43:40Z Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method Lee, Chi King Chiew, Sing Ping Lie, Seng Tjhen Sopha, T. School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering::Structures and design A new approach based on the multi-dimensional Lagrangian interpolation method, which is widely used in the finite element method, is proposed for the prediction of stress concentration factor for tubular joints. When comparing with the parametric regression method, this new method uses the same set of numerical parametric study results as its inputs. The accuracy of the proposed method is validated by applying it to predict the stress concentration factor and hot spot stress of partially overlapped circular hollow section K-joints. Numerical results indicated that the new method is more reliable and accurate than the parametric regression method. Accepted version 2014-03-14T01:14:36Z 2019-12-06T20:51:58Z 2014-03-14T01:14:36Z 2019-12-06T20:51:58Z 2011 2011 Journal Article Lee, C. K., Chiew, S. P., Lie, S. T., & Sopha, T. (2011). Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method. Engineering Fracture Mechanics, 78(6), 1008-1028. 0013-7944 https://hdl.handle.net/10356/102229 http://hdl.handle.net/10220/18893 10.1016/j.engfracmech.2010.11.013 en Engineering fracture mechanics © 2011 Elsevier. This is the author created version of a work that has been peer reviewed and accepted for publication by Engineering Fracture Mechanics, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI:http://dx.doi.org/10.1016/j.engfracmech.2010.11.013]. 44 p. application/pdf |
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DRNTU::Engineering::Civil engineering::Structures and design Lee, Chi King Chiew, Sing Ping Lie, Seng Tjhen Sopha, T. Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
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A new approach based on the multi-dimensional Lagrangian interpolation method, which is widely used in the finite element method, is proposed for the prediction of stress concentration factor for tubular joints. When comparing with the parametric regression method, this new method uses the same set of numerical parametric study results as its inputs. The accuracy of the proposed method is validated by applying it to predict the stress concentration factor and hot spot stress of partially overlapped circular hollow section K-joints. Numerical results indicated that the new method is more reliable and accurate than the parametric regression method. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Lee, Chi King Chiew, Sing Ping Lie, Seng Tjhen Sopha, T. |
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Article |
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Lee, Chi King Chiew, Sing Ping Lie, Seng Tjhen Sopha, T. |
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Lee, Chi King |
title |
Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
title_short |
Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
title_full |
Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
title_fullStr |
Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
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Stress concentration factor prediction by the multi-dimensional Lagrangian interpolation method |
title_sort |
stress concentration factor prediction by the multi-dimensional lagrangian interpolation method |
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2014 |
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https://hdl.handle.net/10356/102229 http://hdl.handle.net/10220/18893 |
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1681034661434753024 |