Data underlying the research of particle-laden pipe flow by MRI and DNS
doi:10.4121/21679796.v1
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doi: 10.4121/21679796
doi: 10.4121/21679796
Datacite citation style:
Hogendoorn, Willian; Breugem, Wim-Paul; Poelma, Christian; Frank, David; Bruschewski, Martin et. al. (2023): Data underlying the research of particle-laden pipe flow by MRI and DNS. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21679796.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
This data set contains bulk velocity normalised intrinsic liquid velocity (U) and solid volume fraction (C) profiles for particle-laden pipe flows for six different cases. This data is obtained using Magnetic Resonance Imaging/Velocimetry (MRI/V) and Direct Numerical Simulations (DNS). The data corresponds to the paper (Fig. 6): "From nearly homogeneous to core-peaking suspensions: insight in suspension pipe flows using MRI and DNS" by Hogendoorn et al.
history
- 2023-12-11 first online, published, posted
publisher
4TU.ResearchData
format
.txt files with velocity and concentration profiles
funding
- Flows Unveiled: Multimodal Measurement in Opaque Two-Phase Flows (grant code 725183) [more info...] European Research Council
- Numerical simulation of complex flows in complex geometries (grant code 2023.009) NWO
organizations
Delft University of Technology, Faculty of Mechanical Engineering (ME), Department of Process & Energy; Rostock University, Lehrstuhl für fur Strömungsmechanik
DATA
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- 1,400 bytesMD5:
9d4c90d51009a41fbf7b6c61c3f44290
readme.txt - 17,880 bytesMD5:
45e5fb154ff6158b799771df7ed922be
data.txt -
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