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FSI-complex fluids

Laufzeit: 01.01.2010 - 30.09.2017

Partner: Johannes-Gutenberg-Universität Mainz, Fachbereich Physik, Mathematik, Informatik

Förderung durch: DFG

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Kurzfassung



Materials encountered in industry and medicine often fall outside the classical models of Newtonian viscous fluids. The aim of the proposed project is to gain deep understanding of complex behavior of shear-dependent non-Newtonian fluids in time-dependent moving domains. Thus, our aims are two-fold: theoretical analysis of the corresponding mathematical model and the development of a reliable numerical scheme for experimental simulations. Non-Newtonian fluids we have in mind belong to the...

Materials encountered in industry and medicine often fall outside the classical models of Newtonian viscous fluids. The aim of the proposed project is to gain deep understanding of complex behavior of shear-dependent non-Newtonian fluids in time-dependent moving domains. Thus, our aims are two-fold: theoretical analysis of the corresponding mathematical model and the development of a reliable numerical scheme for experimental simulations. Non-Newtonian fluids we have in mind belong to the class of shear-thinning/shear-thickening fluids, for which the viscous stress tensor is a nonlinear function of the shear rate. They are extensively used in industry or biomedicine in order to simulate flow of technical oils, composites, polymers, biological fluids, etc. As an example the blood flow in compliant vessels will be considered in particular. To assure that the derived numerical schemes are robust and reliable for such complex models, an in-depth numerical analysis including convergence and error analysis will be necessary.
Founding

  • DFG-Eigene Stelle,  "Mathematical modelling and numerical simulation of shear dependent non-Newtonian fluids in time-dependent domains", ZA 613/1-1, 2010-2013
  •  DFG-Eigene Stelle,  "Mathematical modelling and numerical simulation of fluid-structure interaction for complex viscous fluids", HU 1885/1-2,  09/2015-09/2017,
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