Abstract
For the optimal design of cooling and heating devices, the properties of the included fluids are crucial. The temperature dependence of viscosity deserves attention, as changes can be one order of magnitude or more. Here we examine the influence on convective motions by simulating a heating and cooling experiment with a vertical cylinder by finite element computational fluid dynamics (CFD) models. Such an experimental setup in which flow patterns are determined by transient viscous convection has not been simulated before. Evaluating the general behavior of the experiment in 2D, we find a dynamic phase after and before phases with moderate changes. Flow patterns in the dynamic phase change significantly with the temperature range of the experiment. We compare the outcome of the numerical models with results from laboratory experiments, finding major discrepancies concerning the flow patterns in the dynamic phase. 3D modeling shows weaker dynamics but does not show good timing with the experiment. The study depicts the importance of parameter dependencies for convective motions and demonstrates the capabilities and limitations of models to reproduce details of viscous convection.
Highlights
Viscous fluids are crucial components used in various applications
As most applications deal with heat transfer, it is the temperature dependence that is of specific interest, in particular when dealing with a wide temperature range
We examine the outcome of the constructed model andback check thea sensibility concerning reached an ambient high temperature, the cylinder is put into bath with temperature parameters and the temperature range
Summary
Viscous fluids are crucial components used in various applications. They are used as lubricants, in heat exchangers, etc., generally in cooling and heating facilities at very different scales. It is a common observation that viscosity has the highest variability among the four parameters mentioned The coefficient ς 0 in for Arrhenius equation often preferred: Treto f transform it to a functional formulation is independent of the choice of a reference point. The formulations in Equation (4) depend modeling work reported here.on the constants Tre f , ς re f = ς( Tre f ), a and λ. During the cooling phase that follows, the temperature at the two observation points numerical model with the results measured in the laboratory. The two temperature sensors are located on the cylinder
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
