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authorClaudius "keldu" Holeksa <mail@keldu.de>2025-11-12 13:31:23 +0100
committerClaudius "keldu" Holeksa <mail@keldu.de>2025-11-12 13:31:23 +0100
commitba544718d4796aad5eb80631b4ac27ca5392a934 (patch)
tree8c5cec73d77a8edcf39da9d6766d132f146e71f0
parent67539da96c5980e9631a6aa16a19ce454a638ad3 (diff)
downloadphd-fluid_mechanics_report-ba544718d4796aad5eb80631b4ac27ca5392a934.tar.gz
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@@ -201,6 +201,11 @@ The Lattice-Boltzmann-Method offers an efficient mesoscopic alternative.
Instead of solving the Navier-Stokes equations directly, LBM is a celullar automaton on an equidistant grid based on a stochastic particle
distribution among discretized velocities, so called descriptors.
+#figure(
+image("d3q27.jpg"),
+caption: An example of a discrete 27 velocity descriptor
+)
+
Through these stochastic behaviours, the macroscopic quantities such as velocity and pressure emerge naturally, recovering the Stokes flow
or Navier-Stokes flow.
@@ -211,4 +216,6 @@ dependencies @krueger2017lbm.
=== Immersed Boundary Method
+To couple a particle dynamics system with the LBM modell,
+
=== Homogenized Lattice-Boltzmann