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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Integral squeeze film damper (ISFD) is a new type of structure that appeared on the basis of traditional squeeze film damper (SFD). Since the oil film in ISFD is a segmented structure without annular flow, the nonlinearity of the oil film force has been improved to a great extent. The dynamic characteristic coefficients of ISFD have a close relationship with its damping performance. This work investigates and studies the dynamic characteristic parameters of ISFD by means of numerical analysis and experimental validation techniques in order to examine the dynamic features and unveil the damping mechanism. The ISFD solid and fluid analysis models are created, and the computational fluid dynamics (CFD) and mechanical performance analyses are completed. The force acting on the ISFD’s S-type elastomer under excitation conditions is revealed in the mechanical property analysis, and the flow characteristics of the internal oil film are investigated in the CFD analysis. It is discovered that the ISFD has good linear damping and stiffness characteristics, and numerical analytical values for the ISFD’s damping and stiffness coefficients are obtained. By constructing a bi-directional excitation test rig, the experimental values of the ISFD stiffness coefficient and damping coefficient are determined. These values are in close agreement with the results of the numerical analysis, confirming the accuracy of the ISFD’s numerical analysis conclusions.

Details

Title
Research on Dynamic Characteristic Coefficients of Integral Squeeze Film Damper
Author
Yan, Wei 1 ; Lu, Jinlong 1 ; Pan, Jiabao 1   VIAFID ORCID Logo  ; Liu, Jinduo 1 ; Fuyang, Chengming 1 ; Ye, Dongdong 2 

 School of Mechanical Engineering, Anhui Polytechnic University, Wuhu 241000, China; [email protected] (W.Y.); [email protected] (J.P.); [email protected] (J.L.); [email protected] (C.F.) 
 Anhui Polytechnic Industrial Innovation Technology Research Co., Ltd., Wuhu 241000, China; [email protected]; School of Artificial Intelligence, Anhui Polytechnic University, Wuhu 241000, China 
First page
274
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20751702
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3046963404
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.