{"title":"A structured adaptive mesh refinement strategy with a sharp interface direct-forcing immersed boundary method for moving boundary problems","authors":"Mehdi Badri Ghomizad, Hosnieh Kor, K. Fukagata","doi":"10.1299/JFST.2021JFST0014","DOIUrl":null,"url":null,"abstract":"We develop a versatile and accurate structured adaptive mesh refinement (S-AMR) strategy with a moving least square sharp-direct forcing immersed boundary method (IBM) for incompressible fluid-structure interaction (FSI) simulations. The computational grid consists of several nested blocks in different refinement levels. While blocks with the coarsest grid cover the entire computational domain, the computational domain is locally refined at the location of solid boundary (moving or fixed) by bisecting selected blocks in every coordinate direction. The grid topology and data structure is managed by an extended version of Afivo toolkit (Teunissen and Ebert, 2018), where a novel technique is introduced for conservative data transfer between the coarser and the finer blocks, particularly in velocity transformation for which the mass conservation plays a crucial role. In the present study, the continuity and Navier-Stokes equations for incompressible flows are spatially discretized with a second order central finite difference method using a collocated arrangement and are time-integrated using a semi-implicit second order fractional step method, although the proposed S-AMR strategy can be used with different discretization schemes. An IBM using a moving least square approach is utilized to impose boundary conditions. To handle FSI problems, all the governing equations for the dynamics of fluid and structure are simultaneously advanced in time by a predictorcorrector strategy. Several test cases of increasing complexity are solved in order to demonstrate the robustness and accuracy of the proposed method as well as its capability in simulation-driven mesh adaptivity.","PeriodicalId":44704,"journal":{"name":"Journal of Fluid Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Fluid Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1299/JFST.2021JFST0014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MECHANICS","Score":null,"Total":0}
引用次数: 3
Abstract
We develop a versatile and accurate structured adaptive mesh refinement (S-AMR) strategy with a moving least square sharp-direct forcing immersed boundary method (IBM) for incompressible fluid-structure interaction (FSI) simulations. The computational grid consists of several nested blocks in different refinement levels. While blocks with the coarsest grid cover the entire computational domain, the computational domain is locally refined at the location of solid boundary (moving or fixed) by bisecting selected blocks in every coordinate direction. The grid topology and data structure is managed by an extended version of Afivo toolkit (Teunissen and Ebert, 2018), where a novel technique is introduced for conservative data transfer between the coarser and the finer blocks, particularly in velocity transformation for which the mass conservation plays a crucial role. In the present study, the continuity and Navier-Stokes equations for incompressible flows are spatially discretized with a second order central finite difference method using a collocated arrangement and are time-integrated using a semi-implicit second order fractional step method, although the proposed S-AMR strategy can be used with different discretization schemes. An IBM using a moving least square approach is utilized to impose boundary conditions. To handle FSI problems, all the governing equations for the dynamics of fluid and structure are simultaneously advanced in time by a predictorcorrector strategy. Several test cases of increasing complexity are solved in order to demonstrate the robustness and accuracy of the proposed method as well as its capability in simulation-driven mesh adaptivity.
期刊介绍:
Journal of Fluid Science and Technology (JFST) is an international journal published by the Fluids Engineering Division in the Japan Society of Mechanical Engineers (JSME). JSME had been publishing Bulletin of the JSME (1958-1986) and JSME International Journal (1987-2006) by the continuous volume numbers. Considering the recent circumstances of the academic journals in the field of mechanical engineering, JSME reorganized the journal editorial system. Namely, JSME discontinued former International Journals and projected new publications from the divisions belonging to JSME. The Fluids Engineering Division acted quickly among all divisions and launched the premiere issue of JFST in January 2006. JFST aims at contributing to the development of fluid engineering by publishing superior papers of the scientific and technological studies in this field. The editorial committee will make all efforts for promoting strictly fair and speedy review for submitted articles. All JFST papers will be available for free at the website of J-STAGE (http://www.i-product.biz/jsme/eng/), which is hosted by Japan Science and Technology Agency (JST). Thus papers can be accessed worldwide by lead scientists and engineers. In addition, authors can express their results variedly by high-quality color drawings and pictures. JFST invites the submission of original papers on wide variety of fields related to fluid mechanics and fluid engineering. The topics to be treated should be corresponding to the following keywords of the Fluids Engineering Division of the JSME. Basic keywords include: turbulent flow; multiphase flow; non-Newtonian fluids; functional fluids; quantum and molecular dynamics; wave; acoustics; vibration; free surface flows; cavitation; fluid machinery; computational fluid dynamics (CFD); experimental fluid dynamics (EFD); Bio-fluid.