An extended subset of nominal modes method for coated blisks with thickness mistuning of coatings and blisks
Autor: | Junnan Gao, Xianfei Yan, Kunpeng Xu, Wei Sun |
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Rok vydání: | 2020 |
Předmět: |
Materials science
Basis (linear algebra) Iterative method business.industry Mechanical Engineering 02 engineering and technology Structural engineering Mistuning 01 natural sciences Finite element method Matrix (mathematics) 020303 mechanical engineering & transports 0203 mechanical engineering 0103 physical sciences Node (circuits) Boundary value problem business 010301 acoustics Subspace topology |
Zdroj: | Archive of Applied Mechanics. 90:2007-2024 |
ISSN: | 1432-0681 0939-1533 |
DOI: | 10.1007/s00419-020-01707-1 |
Popis: | The thickness mistuning of coatings and blisks cannot be predicted before manufacturing process, and the mistuning patterns normally tend to be random, which has not been investigated in opened studies. A novel finite element model (FEM) is developed to incorporate variable thicknesses of the coatings and the blisks. The FEM requires only the sector-level node coordinates of the uncoated blisks and is validated by the ANSYS software. Nevertheless, the classical subset of nominal modes (SNM) cannot capture the accuracy of coated blisks with thickness mistuning and to solve the eigenproblem of the full-order FEM will require expensive computational cost. As a consequence, on the basis of a subspace iteration method, an extended SNM is developed to improve the computational efficiency, where the initial mode matrix of the iteration is obtained by using the Craig–Bampton method and the cyclic symmetric boundary conditions. This paper presents a numerical comparison of the classical SNM, the extended SNM and the full-order FEM. The results suggest that the developed FEM and the extended SNM are effective for the analysis with thickness mistuning of the coatings and the substrate. Compared with the solution time of the eigenproblem for the full-order FEM, it is reduced by roughly 89.5% for the extended SNM. |
Databáze: | OpenAIRE |
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