On an improved adaptive reduced-order model for the computation of steady-state vibrations in large-scale non-conservative systems with friction joints
On an improved adaptive reduced-order model for the computation of steady-state vibrations in large-scale non-conservative systems with friction joints
Joints are commonly used in many large-scale engineering systems to ease assembly, and ensure structural integrity and effective load transmission. Most joints are designed around friction interfaces, which can transmit large static forces, but tend to introduce stick-slip transition during vibrations, leading to a nonlinear dynamic system. Tools for the complex numerical prediction of such nonlinear systems are available today, but their use for large-scale applications is regularly prevented by high computational cost. To address this issue, a novel adaptive reduced-order model (ROM) has recently been developed, significantly decreasing the computational time for such high fidelity simulations. Although highly effective, significant improvements to the proposed approach is presented and demonstrated in this paper, further increasing the efficiency of the ROM. An energy-based error estimator was developed and integrated into the nonlinear spectral analysis, leading to a significantly higher computational speed by removing insignificant static modes from the stuck contact nodes in the original reduced basis, and improving the computational accuracy by eliminating numerical noise. The effectiveness of the new approach was shown on an industrial-scale fan blades system with a dovetail joints, showing that the improved adaptive method can be 2–3 times more computationally efficient than the original adaptive method especially at high excitation levels but also effectively improve the accuracy of the original method.
3283–3300
Yuan, J.
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Schwingshackl, C.
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Wong, C.
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Salles, L.
1b179daa-7bb9-4f34-8b5f-dfc05b496969
Yuan, J.
4bcf9ce8-3af4-4009-9cd0-067521894797
Schwingshackl, C.
9d5d0411-fd2a-4438-8c25-b8b9870647f3
Wong, C.
d81bef05-7955-4a7e-a33d-a15eb961d215
Salles, L.
1b179daa-7bb9-4f34-8b5f-dfc05b496969
Yuan, J., Schwingshackl, C., Wong, C. and Salles, L.
(2020)
On an improved adaptive reduced-order model for the computation of steady-state vibrations in large-scale non-conservative systems with friction joints.
Nonlinear Dynamics, 103, .
(doi:10.1007/s11071-020-05890-2).
Abstract
Joints are commonly used in many large-scale engineering systems to ease assembly, and ensure structural integrity and effective load transmission. Most joints are designed around friction interfaces, which can transmit large static forces, but tend to introduce stick-slip transition during vibrations, leading to a nonlinear dynamic system. Tools for the complex numerical prediction of such nonlinear systems are available today, but their use for large-scale applications is regularly prevented by high computational cost. To address this issue, a novel adaptive reduced-order model (ROM) has recently been developed, significantly decreasing the computational time for such high fidelity simulations. Although highly effective, significant improvements to the proposed approach is presented and demonstrated in this paper, further increasing the efficiency of the ROM. An energy-based error estimator was developed and integrated into the nonlinear spectral analysis, leading to a significantly higher computational speed by removing insignificant static modes from the stuck contact nodes in the original reduced basis, and improving the computational accuracy by eliminating numerical noise. The effectiveness of the new approach was shown on an industrial-scale fan blades system with a dovetail joints, showing that the improved adaptive method can be 2–3 times more computationally efficient than the original adaptive method especially at high excitation levels but also effectively improve the accuracy of the original method.
Text
s11071-020-05890-2
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Accepted/In Press date: 6 August 2020
e-pub ahead of print date: 17 August 2020
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Local EPrints ID: 478903
URI: http://eprints.soton.ac.uk/id/eprint/478903
ISSN: 0924-090X
PURE UUID: 666735d2-a84b-47e8-8e53-2d2961fd80ff
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Date deposited: 12 Jul 2023 16:47
Last modified: 17 Mar 2024 04:20
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Author:
J. Yuan
Author:
C. Schwingshackl
Author:
C. Wong
Author:
L. Salles
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