期刊
COMPUTERS & FLUIDS
卷 197, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compfluid.2019.104391
关键词
-
资金
- German Research Foundation (DFG) [283792184]
- German Research Foundation (DFG) within the research training group SiMET [281041241/GRK2218]
In a previous work, the feasibility of coupling magnetic resonance imaging (MRI) measurements and computational fluid dynamics (CFD) was presented, called CFD-MRI. Using a lattice Boltzmann based topology optimisation approach, the method can be described as a Navier-Stokes filter for flow MRI measurements. The main objective of this article is the analysis and quantification of CFD-MRI for its ability to reduce statistical measurement noise. For this, MRI data was analysed and used as basis for synthetic data, where noise was added to a simulation result. Thus, the noise-free data is known and a thorough analysis can be performed. The results show a very high agreement with the original data, even with high statistical noise in the input data and limited information available. (C) 2019 Elsevier Ltd. All rights reserved.
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