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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Dresden6 - current status and future of morphology-adaptive Eulerian modeling of multiphase flows</dc:title><dc:creator>Schlegel,	Fabian	(Avtor)
	</dc:creator><dc:creator>Ben Hadj Ali,	Amine	(Avtor)
	</dc:creator><dc:creator>Colombo,	Marco	(Avtor)
	</dc:creator><dc:creator>Tekavčič,	Matej	(Avtor)
	</dc:creator><dc:subject>numerical simulations</dc:subject><dc:subject>multiphase flows</dc:subject><dc:subject>morphology-adaptive method</dc:subject><dc:subject>separated effect tests</dc:subject><dc:subject>integral tests</dc:subject><dc:description>Multiphase flows are of great relevance to a wide range of industries, and their simulation using Computational Fluid Dynamics (CFD) is an important pillar for conducting design studies and gaining physical insight. However, a particular challenge in the simulation of multiphase flows is the occurrence of different morphologies or flow regimes, i.e. dispersed vs. segregated. The established simulation frameworks that have been developed over the years are usually only applicable to a specific morphology and level of detail. The simulation of a combination of morphologies is particularly challenging, and adaptive approaches are sought where the trade-off between level of detail and time to solution is mainly a matter of spatial resolution, rather than the fundamental choice of a method. In this respect, the Euler-Euler model has crucial properties that make it a good basis. This paper gives an overview of existing morphology-adaptive Eulerian methods, also often referred to as hybrid Eulerian methods. It is the result of a joint effort of the Dresden6 initiative, a loose association of research groups already active in this field. It gives an honest picture of current shortcomings and future development prospects. The aim of the work is to start a homogenization process by establishing a common terminology and listing suitable test cases that can be used for benchmarking, i.e. verification and validation.</dc:description><dc:publisher>Elsevier</dc:publisher><dc:date>2026</dc:date><dc:date>2026-04-29 11:12:36</dc:date><dc:type>Neznano</dc:type><dc:identifier>29230</dc:identifier><dc:identifier>UDK: 53</dc:identifier><dc:identifier>ISSN pri članku: 1879-0747</dc:identifier><dc:identifier>DOI: 10.1016/j.compfluid.2026.107085</dc:identifier><dc:identifier>COBISS_ID: 276253187</dc:identifier><dc:source>Nizozemska</dc:source><dc:language>sl</dc:language><dc:rights>© 2026 The Authors.</dc:rights></metadata>
