291 to 300 of 682 Results
Nov 20, 2023 -
Ion Flow Through Neural Ion Membrane: scripts and data
MS Excel Spreadsheet - 8.8 KB -
MD5: 1a3b68260ec58055e9ae5180a40e5f4f
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Nov 20, 2023 -
Ion Flow Through Neural Ion Membrane: scripts and data
MS Excel Spreadsheet - 8.8 KB -
MD5: 21995c570dee94a4ee4d9e2b26c89034
|
Nov 20, 2023 -
Ion Flow Through Neural Ion Membrane: scripts and data
MATLAB Data - 30.9 KB -
MD5: 955a22effe64547fd8172d27f6820bee
|
Sep 12, 2023 - Publication: Microfluidic experiments
Karadimitriou, Nikolaos; Steeb, Holger; Valavanides, Marios, 2022, "Pressure and volumetric flux measurements intended to scale relative permeability under steady state, co-flow conditions, in a PDMS micromodel", https://doi.org/10.18419/DARUS-2816, DaRUS, V2
The current repository contains raw data collected during a systematic laboratory study, examining the flow rate dependency of steady-state, co-injection of two-immiscible fluids within a microfluidic pore network model. The study is presented in the paper by Karadimitriou et al., 2023. The two fluids were the wetting phase (WP), FluorinertTM, FC77... |
MPEG-4 Video - 36.3 MB -
MD5: 890fc0239d6ccf279ba5bea92d4d9d3a
Visual example of the co-flow of the wetting and the non-wetting phase in the pore space. |
Sep 6, 2023 - Publication: Development of stochastically reconstructed 3D porous media micromodels using additive manufacturing: numerical and experimental validation
Lee, Dongwon; Ruf, Matthias; Yiotis, Andreas; Steeb, Holger, 2023, "Numerical investigation results of 3D porous structures using stochastic reconstruction algorithm", https://doi.org/10.18419/DARUS-3244, DaRUS, V1
This dataset contains the outcomes of conducted numerical simulations, rooted in designs generated using a stochastic algorithm devised by Quiblie (1984), Adler et al. (1990), and Hyman et al. (2014). Moreover, the investigation employed Lattice Boltzmann simulation, as used in previous study by Psihogios et al. (2007), where the simulations were f... |
Sep 6, 2023 -
Numerical investigation results of 3D porous structures using stochastic reconstruction algorithm
7Z Archive - 65.0 MB -
MD5: d8a1138be37f2ed3b66e90fff018d70b
Designed domains with fixed_lambda (porosity : 0.45, lambda : 45) |
Sep 6, 2023 -
Numerical investigation results of 3D porous structures using stochastic reconstruction algorithm
7Z Archive - 179.6 MB -
MD5: 00de6a2984a3b4b93f332a9509c5a0b8
Designed domains with relative lambda (fixed ratio of lambda (lambda = domain_size/20)) (porosity : 0.15, 0.25 and 0.45, lambda : 5, 10, 15, 20, 25, 30 and 35) |
Sep 6, 2023 -
Numerical investigation results of 3D porous structures using stochastic reconstruction algorithm
7Z Archive - 16.6 MB -
MD5: ce09ef2f10faac195400daf147fc2f28
Designed representative domains (porosity : 0.25, lambda : 15, 25, 35 and 45). |
Sep 6, 2023 -
Numerical investigation results of 3D porous structures using stochastic reconstruction algorithm
7Z Archive - 41.5 MB -
MD5: ae268f22d3c33d06f2557324b2354eca
Designed representative domains (porosity : 0.15 and 0.35, lambda : 15, 25, 35 and 45). |
