Kevin G. Wang, Philip S. Beran, Shunxiang Cao

DOI Number: N/A

Conference number: IFASD-2017-212

Adjoint-based mesh adaptation is applied to the prediction of flutter with a direct, Hopf bifurcation method. Adjoint variables are computed with respect to the objective of flutter speed, and regarded as an a posteriori indicator of the relative importance of local conditions to this objective. The magnitude of adjoint variables is then used to drive mesh adaptation for improved accuracy. The methodology is demonstrated on the model problem of a onedimensional thin panel in supersonic flow. The structure is modeled using the von Karman plate theory, the fluid pressure distribution on the panel is modeled using piston theory, and the combined system of equations is discretized using a finite difference method. Mesh adaptation is used to take an initially uniform mesh and locally refine it to better resolve parts of the panel that are judged to be relatively more important to flutter prediction. Three mesh-adaptation criteria are compared and contrasted based on: (1) strict adjoint-based mesh adaptation using the adjoint variables, (2) feature-based mesh adaptation using the solution curvature, and (3) a relaxed adjoint-based mesh adaptation using a combination of the adjoint variable and the solution curvature. The results show that for coarse meshes, criteria leveraging adjoints clearly outperform feature-based adaptation for predicting the critical dynamic pressure at flutter onset.

Read the full paper here

Email
Print
LinkedIn
The paper above was part of  proceedings of a CEAS event and as such the author has signed a publication agreement to have their paper published in the repository. In the case this paper is found somewhere else CEAS always links to the other source.  CEAS takes great care in making the correct content available to the reader. If any mistakes are found  in the listings please contact us directly at papers@aerospacerepository.org and we will correct the listing promptly.  CEAS cannot be held liable either for mistakes in editorial or technical aspects, nor for omissions, nor for the correctness of the content. In particular, CEAS does not guarantee completeness or correctness of information contained in external websites which can be accessed via links from CEAS’s websites. Despite accurate research on the content of such linked external websites, CEAS cannot be held liable for their content. Only the content providers of such external sites are liable for their content. Should you notice any mistake in technical or editorial aspects of the CEAS site, please do not hesitate to inform us.