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      KCI등재

      VIC# 자료동화 기법을 통해 재구축된 유동장의 상사성에 관한 비교 연구

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      https://www.riss.kr/link?id=A105580289

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      다국어 초록 (Multilingual Abstract)

      The present study compares flow fields reconstructed by data assimilation method with different combinations of parameters. As a data assimilation method, Vortex-in-Cell-sharp (VIC#), which supplements additional constraints and multigrid approximation to Vortex-in-Cell-plus (VIC+), is used to reconstruct flow fields from scattered particle tracks. Two parameters, standard deviation of Gaussian radial basis function (RBF) and grid spacing, are mainly tested using artificial data sets which contain few particle tracks. Consequent flow fields are analyzed in terms of flow structure sizes. It is demonstrated that sizes of the flow structures are proportional to an actual scale of the standard deviation of RBF. It implies that a combination of larger grid spacing and smaller standard deviation which preserves the actual standard deviation is able to save computational resources in case of a low track density. In addition, a simple comparison using an experimental data filled with dense particle tracks is conducted.
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      The present study compares flow fields reconstructed by data assimilation method with different combinations of parameters. As a data assimilation method, Vortex-in-Cell-sharp (VIC#), which supplements additional constraints and multigrid approximatio...

      The present study compares flow fields reconstructed by data assimilation method with different combinations of parameters. As a data assimilation method, Vortex-in-Cell-sharp (VIC#), which supplements additional constraints and multigrid approximation to Vortex-in-Cell-plus (VIC+), is used to reconstruct flow fields from scattered particle tracks. Two parameters, standard deviation of Gaussian radial basis function (RBF) and grid spacing, are mainly tested using artificial data sets which contain few particle tracks. Consequent flow fields are analyzed in terms of flow structure sizes. It is demonstrated that sizes of the flow structures are proportional to an actual scale of the standard deviation of RBF. It implies that a combination of larger grid spacing and smaller standard deviation which preserves the actual standard deviation is able to save computational resources in case of a low track density. In addition, a simple comparison using an experimental data filled with dense particle tracks is conducted.

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      참고문헌 (Reference)

      1 Nocedal, J., "Updating quasi-Newton matrices with limited storage" 35 (35): 773-782, 1980

      2 Schanz, D., "Towards high-resolution 3D flow field measurements at cubic meter scales" 2016

      3 Schanz, D., "Shake-The-Box: Lagrangian particle tracking at high particle image densities" 57 (57): 70-, 2016

      4 Schanz, D., "Shake The Box: A highly efficient and accurate tomographic particle tracking velocimetry method using prediction of particle positions" 2013

      5 Schneiders, J. F. G., "Resolving vorticity and dissipation in a turbulent boundary layer by tomographic PTV and VIC+" 58 (58): 27-, 2017

      6 Casa L. D. C., "Radial basis function interpolation of unstructured, three-dimensional, volumetric particle tracking velocimetry data" 24 (24): 065304-, 2013

      7 Schneiders, J. F. G., "Pressure estimation from single-snapshot tomographic PIV in a turbulent boundary layer" 57 (57): 53-, 2016

      8 Schanz, D., "New Results in Numerical and Experimental Fluid Mechanics XI" Springer 587-597, 2018

      9 Huhn, F., "Large-scale volumetric flow measurement in a pure thermal plume by dense tracking of helium-filled soap bubbles" 58 (58): 116-, 2017

      10 Wieneke, B., "Iterative reconstruction of volumetric particle distribution" 24 (24): 024008-, 2012

      1 Nocedal, J., "Updating quasi-Newton matrices with limited storage" 35 (35): 773-782, 1980

      2 Schanz, D., "Towards high-resolution 3D flow field measurements at cubic meter scales" 2016

      3 Schanz, D., "Shake-The-Box: Lagrangian particle tracking at high particle image densities" 57 (57): 70-, 2016

      4 Schanz, D., "Shake The Box: A highly efficient and accurate tomographic particle tracking velocimetry method using prediction of particle positions" 2013

      5 Schneiders, J. F. G., "Resolving vorticity and dissipation in a turbulent boundary layer by tomographic PTV and VIC+" 58 (58): 27-, 2017

      6 Casa L. D. C., "Radial basis function interpolation of unstructured, three-dimensional, volumetric particle tracking velocimetry data" 24 (24): 065304-, 2013

      7 Schneiders, J. F. G., "Pressure estimation from single-snapshot tomographic PIV in a turbulent boundary layer" 57 (57): 53-, 2016

      8 Schanz, D., "New Results in Numerical and Experimental Fluid Mechanics XI" Springer 587-597, 2018

      9 Huhn, F., "Large-scale volumetric flow measurement in a pure thermal plume by dense tracking of helium-filled soap bubbles" 58 (58): 116-, 2017

      10 Wieneke, B., "Iterative reconstruction of volumetric particle distribution" 24 (24): 024008-, 2012

      11 Gesemann, S., "From noisy particle tracks to velocity, acceleration and pressure fields using B-splines and penalties" 2016

      12 Schneiders, J. F. G., "Dense velocity reconstruction from tomographic PTV with material derivatives" 57 (57): 139-, 2016

      13 Jeon, Y. J., "4D flow field reconstruction from particle tracks by VIC+ with additional constraints and multigrid approximation" 2018

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 선정 (재인증) KCI등재
      2018-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
      2012-04-01 평가 등재후보 탈락 (기타)
      2010-01-01 평가 등재후보 1차 FAIL (등재후보1차) KCI등재후보
      2009-01-01 평가 등재후보학술지 유지 (등재후보1차) KCI등재후보
      2008-01-01 평가 등재후보학술지 유지 (등재후보1차) KCI등재후보
      2006-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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