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A novel design methodology for preventing dislocation in the Zig-zag shroud

  • Chenhong Du ORCID logo EMAIL logo , Yanrong Wang , Di Li and Yuanyuan Jiang
Published/Copyright: January 31, 2025
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Abstract

Dislocation is defined as the inability of shrouded blades to return to their normal position after deformation caused by an external force. Numerous methods exist for designing shrouds of turbine engines, targeting structural strength, sealing performance, contact interface wear, or damping. However, these designs often fail when dislocation occurs, which is a common issue in engineering. Limited methods focus on preventing shroud dislocation. In this article, we classify the dislocation of zig-zag shrouds into two patterns. A method for calculating the equivalent stiffness of the contact interface is provided to determine the clearance of non-working surfaces. Through a series of static analysis, we introduce a method to adjust the shroud shape and assess its capability in preventing dislocation. All methods are tested on a low-pressure turbine blade.


Corresponding author: Chenhong Du, School of Energy and Power Engineering, Beihang University, Beijing, 100191, China, E-mail:

Funding source: National Science and Technology Major Project

Award Identifier / Grant number: 2017-IV-0002-0039

Funding source: National Science and Technology Major Project

Award Identifier / Grant number: 2022-IV-0010-0024

Acknowledgments

This work is supported by the National Science and Technology Major Project (No. 2017-IV-0002-0039) and National Science and Technology Major Project (No. 2022-IV-0010-0024).

  1. Research ethics: Not applicable.

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: Chenhong Du: writing, methodology, investigation. Yanrong Wang: methodology, funding acquisition, project administration. Di Li: conceptualization, supervision. Yuanyuan Jiang: methodology.

  4. Use of Large Language Models, AI and Machine Learning Tools: Xhang AI (https://xhang.buaa.edu.cn/) is used to improve language.

  5. Conflict of interests: The authors states no conflict of interest.

  6. Research funding: National Science and Technology Major Project (No. 2017-IV-0002-0039) National Science and Technology Major Project (No. 2022-IV-0010-0024).

  7. Data availability: Not applicable.

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Received: 2024-06-23
Accepted: 2025-01-17
Published Online: 2025-01-31
Published in Print: 2025-08-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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