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Studies on hydrodynamic characteristics of viscous incompressible flows around flexible hydrofoils are of practical importance for the design and performance optimization of marine structures such as ship rudders and stabilizing fins. The aim of this paper is to extend a radial basis function based ghost cell method to simulate flows around single or multiple flexible moving hydrofoils in array arrangement. The numerical model is based on a ghost cell finite difference method for considering the influence of the immersed boundaries on the flow. Also, a compact supported radial basis function (CSRBF) is introduced to track the complex flexible boundary with some controlling points of the body surface. Based on the present method, the uniform flow around a flexible hydrofoil swimming like a fish is simulated. Good grid convergence of drag and lift coefficients demonstrates the accuracy and reliability of the present method. Also, the hydrodynamics patterns of the flexible hydrofoil under different oscillation frequencies are studied. Further, the thrust generation mechanism of the hydrofoil is explained. Afterwards, flows around the undulating hydrofoils in array arrangement are simulated. The force coefficients and wake patterns under different distances and oscillation frequencies are investigated. It is observed that the thrust coefficients of the hydrofoils under narrow arrangement and high oscillation frequencies have significant amplification effects. In addition, the critical frequency at zero thrust reduces.
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Keywords:
- Cartesian grid /
- radial basis function /
- flexible hydrofoils /
- array arrangement
[1] Zabihi M, Lari K, Amiri H 2017 J. Mech. Sci. Technol. 31 3539Google Scholar
[2] Yang J M 2016 J. Hydrodyn. Ser. B 28 713Google Scholar
[3] 王力, 田方宝 2018 中国科学: 物理学 力学 天文学 48 094703Google Scholar
Wang L, Tian F B 2018 Sci. China Phys. Mech. Astron. 48 094703Google Scholar
[4] Al-Marouf M, Samtaney R 2017 J. Comput. Phys. 337 339Google Scholar
[5] Huang W X, Chang C B, Sung H J 2011 J. Comput. Phys. 230 5061Google Scholar
[6] Tullio M D D, Pascazio G 2016 J. Comput. Phys. 325 201Google Scholar
[7] 吴晓笛, 刘华坪, 陈浮 2017 22 224702Google Scholar
Wu X D, Liu H P, Chen F 2017 Acta Phys. Sin. 22 224702Google Scholar
[8] Yeo K S, Ang S J, Shu C 2010 Comput. Fluids 39 403Google Scholar
[9] Tian F B, Wang W, Wu J, Sui Y 2016 Comput. Fluids 124 1Google Scholar
[10] Bergmann M, Iollo A, Mittal R 2014 Bioinspiration Biomimetics 9 046001Google Scholar
[11] Khalid M S U, Akhtar I, Dong H 2016 J. Fluids Struct. 66 19Google Scholar
[12] Khalid M S U, Akhtar I, Imtiaz H, Dong H, Wu B 2018 Ocean Eng. 157 108Google Scholar
[13] Mittal R, Dong H, Bozkurttas M, Najjar F M, Vargas A, Loebbecke A V 2008 J. Comput. Phys. 227 4825Google Scholar
[14] 王亮, 吴锤结 2011 力学学报 43 18Google Scholar
Wang L, Wu C J 2011 Chin. J. Theor. Appl. Mech. 43 18Google Scholar
[15] 王文全 2014 计算力学学报 31 646Google Scholar
Wang W Q 2014 Chin. J. Comput. Mech. 31 646Google Scholar
[16] 辛建建, 石伏龙, 金秋 2017 66 186
Xin J J, Shi F L, Jin Q 2017 Acta Phys. Sin. 66 186
[17] Xin J J, Shi F L, Jin Q, Lin C 2018 Comput. Fluids 176 210Google Scholar
[18] Leer B V 1979 J. Comput. Phys. 32 101Google Scholar
[19] Van d V H A, Kohn R V, Iserles A, Ciarlet P G, Wright M H 2006 Iterative Krylov Methods for Large Linear Systems (Cambridge: Cambridge University Press) pp133–135
[20] Liu G R, Gu Y T 2005 An Introduction to Meshfree Methods and Their Programming (Netherlands: Springer) p73
[21] Sui Y, Chew Y T, Roy P, Low H T 2007 Int. J. Numer. Methods Fluids 53 1727Google Scholar
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[1] Zabihi M, Lari K, Amiri H 2017 J. Mech. Sci. Technol. 31 3539Google Scholar
[2] Yang J M 2016 J. Hydrodyn. Ser. B 28 713Google Scholar
[3] 王力, 田方宝 2018 中国科学: 物理学 力学 天文学 48 094703Google Scholar
Wang L, Tian F B 2018 Sci. China Phys. Mech. Astron. 48 094703Google Scholar
[4] Al-Marouf M, Samtaney R 2017 J. Comput. Phys. 337 339Google Scholar
[5] Huang W X, Chang C B, Sung H J 2011 J. Comput. Phys. 230 5061Google Scholar
[6] Tullio M D D, Pascazio G 2016 J. Comput. Phys. 325 201Google Scholar
[7] 吴晓笛, 刘华坪, 陈浮 2017 22 224702Google Scholar
Wu X D, Liu H P, Chen F 2017 Acta Phys. Sin. 22 224702Google Scholar
[8] Yeo K S, Ang S J, Shu C 2010 Comput. Fluids 39 403Google Scholar
[9] Tian F B, Wang W, Wu J, Sui Y 2016 Comput. Fluids 124 1Google Scholar
[10] Bergmann M, Iollo A, Mittal R 2014 Bioinspiration Biomimetics 9 046001Google Scholar
[11] Khalid M S U, Akhtar I, Dong H 2016 J. Fluids Struct. 66 19Google Scholar
[12] Khalid M S U, Akhtar I, Imtiaz H, Dong H, Wu B 2018 Ocean Eng. 157 108Google Scholar
[13] Mittal R, Dong H, Bozkurttas M, Najjar F M, Vargas A, Loebbecke A V 2008 J. Comput. Phys. 227 4825Google Scholar
[14] 王亮, 吴锤结 2011 力学学报 43 18Google Scholar
Wang L, Wu C J 2011 Chin. J. Theor. Appl. Mech. 43 18Google Scholar
[15] 王文全 2014 计算力学学报 31 646Google Scholar
Wang W Q 2014 Chin. J. Comput. Mech. 31 646Google Scholar
[16] 辛建建, 石伏龙, 金秋 2017 66 186
Xin J J, Shi F L, Jin Q 2017 Acta Phys. Sin. 66 186
[17] Xin J J, Shi F L, Jin Q, Lin C 2018 Comput. Fluids 176 210Google Scholar
[18] Leer B V 1979 J. Comput. Phys. 32 101Google Scholar
[19] Van d V H A, Kohn R V, Iserles A, Ciarlet P G, Wright M H 2006 Iterative Krylov Methods for Large Linear Systems (Cambridge: Cambridge University Press) pp133–135
[20] Liu G R, Gu Y T 2005 An Introduction to Meshfree Methods and Their Programming (Netherlands: Springer) p73
[21] Sui Y, Chew Y T, Roy P, Low H T 2007 Int. J. Numer. Methods Fluids 53 1727Google Scholar
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