@inproceedings{oai:jaxa.repo.nii.ac.jp:00002942,
 author = {中澤, 嵩 and Nakazawa, Takashi},
 book = {宇宙航空研究開発機構特別資料: 第50回流体力学講演会/第36回航空宇宙数値シミュレーション技術シンポジウム論文集, JAXA Special Publication: Proceedings of the 50th Fluid Dynamics Conference / the 36th Aerospace Numerical Simulation Symposium},
 month = {Feb},
 note = {第50回流体力学講演会/第36回航空宇宙数値シミュレーション技術シンポジウム (2018年7月4日-6日. 宮崎市民プラザ), 宮崎市, 宮崎, 50th Fluid Dynamics Conference /the 36th Aerospace Numerical Simulation Symposium (July 4-6, 2018. Miyazaki Citizen's Plaza), Miyazaki, Japan, This paper presents optimal design using Adaptive Mesh Refinement (AMR) with shape optimization method. The method suppresses time periodic flows driven only by the non-stationary boundary condition at a sufficiently low Reynolds number using Snapshot Proper Orthogonal Decomposition (Snapshot POD). For shape optimization, the eigenvalue in Snapshot POD is defined as a cost function. The main problems are Reynolds Average Navier-Stokes problems and eigenvalue problems of Snapshot POD. An objective functional is described using Lagrange multipliers and finite element method. Two-dimensional cavity flow with a disk-shaped isolated body is adopted. The nonstationary boundary condition is defined on the top boundary and non-slip boundary condition for side and bottom boundaries and for the disk boundary. For numerical demonstration, the disk boundary is used as the design boundary. Using H1 gradient method for domain deformation, all triangles over a mesh are deformed as the cost function decreases, where the sensitivities in the boundary integration type and the volume integration type are adopted to comparison both. To avoid decreasing the numerical accuracy based on squeezing triangles, AMR is applied throughout the shape optimization process to maintain equal numerical accuracy to that of a mesh in the initial domain., 形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: AA1830029013, レポート番号: JAXA-SP-18-005},
 pages = {131--134},
 publisher = {宇宙航空研究開発機構(JAXA), Japan Aerospace Exploration Agency (JAXA)},
 title = {数理・データ科学の融合による流体制御},
 volume = {JAXA-SP-18-005},
 year = {2019}
}