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Civil-Comp Conferences
ISSN 2753-3239 CCC: 6
PROCEEDINGS OF THE SEVENTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING Edited by: P. Ivanyi, J. Kruis and B.H.V. Topping
Paper 13.5
Complexity Adaptation Strategy for Order-Adaptive Elements E.D. Mora1,2 and N. Khaji1
1Graduate School of Advanced Science and Engineering,
Hiroshima University, Japan
E.D. Mora, N. Khaji, "Complexity Adaptation Strategy for
Order-Adaptive Elements", in P. Ivanyi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Seventeenth International Conference on
Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 6, Paper 13.5, 2023, doi:10.4203/ccc.6.13.5
Keywords: frame elements, high-order elements, nonlinear elements, p-adaptive.
Abstract
Many studies have worked on reducing dynamic analysis convergence problems.
Currently, there are some robust algorithms. However, they can fail when dealing with
complex structures due to numerical and especially physical instabilities. Some of
them can also be time-consuming procedures. On the other hand, the intrinsic
truncated error in structural analysis decreases when the shape function order is raised
(p-refinement). Nevertheless, this action will increase the complexity and, thus,
structural convergence problems. Therefore, the solution proposed is to adapt the
complexity when physical instabilities are predicted, and Hermite interpolation can
be used to state well-posed results. The physical instability can be predicted by
analyzing strain energy outliers and moment-curvature rule abnormalities. Moreover,
to get more realistic results, nonlinear elements with plastic length were developed.
Since no previous references have worked with these kinds of nonlinear high-order
elements, using a set of sigmoid functions in the stiffness matrix integral was the
solution to obtain generalized high-order Timoshenko beams. Another contribution of
this work was establishing an appropriate manner of getting the maximum permissible
error in p-adaptive methods. Finally, some examples were made to prove the
formulation’s robustness and show how influential the truncated error can be.
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