Experimental and Numerical Study of Swirling ... - Solid Mechanics
Experimental and Numerical Study of Swirling ... - Solid Mechanics Experimental and Numerical Study of Swirling ... - Solid Mechanics
Experi imental and Numerical N Stud dy of Swirling g Flow in Scaveenging Processs for 2-Stroke Marin ne Diesel Engin nes Figur re 6.16: Normal lized Reynolds Shear Stress S Component ts at z . 1 Figur re 6.17: Normal lized Reynolds Shear Stress S Component ts at z . 5 6.2.5 Normali ized Reynoolds Shear Stresses ( uv ´´) m (´´) uv m (´´) uw m (´´) uw m Chapter 6 (´ vw ´) m (´ vw ´) m At z , for all the shear stress components the RSM mmodel prediccts 1 compar ratively lower peak values compared too experimentaal data (Figurres 4.24, 4. 27 & 4.30) respectively. u´ w ´ and vw ´´ ´ are maximumm in the vortex core an nd near wall region (Figurre 6.16). Simmilar to experrimental resullts discusse ed in section 4.2.6, vv z is large in thhe vortex regioon whereas thhe vrv z is i dominant in i the near wwall region. u u´´ v have lowwer values thaan uw ´´ and a vw ´´ but t the spatial ddistribution too some extentt shows simillar features s as the exper rimental dataa. However, aat z in figuree 6.17, uv ´´ hhas 5 decayed d and has similar distributioon as experimmental data. Inn case of u´ w ´ and v´ w ´ also, the model m predictss decay in the magnitude annd enlargement of the zones z having peak values. The magnitudde of peak vaalues for all thhe 160 Numerical Modeling
Experimental and Numerical Study of Swirling Flow in Scavenging Process for 2-Stroke Marine Diesel Engines Chapter 6 shear stress components are under predicted compared to experimental data in figures 4.29 & 4.32 respectively. 6.3 Discussion The results of CFD simulations presented in this chapter do not show a satisfactory agreement with the experimental data. However, there are some qualitative features like profiles of velocity and modeled Reynolds stress components that, to some extent, have reasonable agreements. The factors affecting the performance of the CFD models possibly lie both in the treatment of turbulence and the numerical aspects. The performance of RANS based models for swirling flows have already been discussed in Section 2.4. Numerically, defining the boundary conditions at the inlet of the computational domain has very significant impact. In the current simulations, a constant value of the parameters like velocity components and turbulence parameters like k and have been given at the inlet. Considering the real experimental setup, this approach may not be good because the inlet in the computational domain is placed after the guide vanes and close to the contraction section. The profile of velocity components may not be uniform at that radial position. The possible reasons are the wake that is generated behind the guide vanes and the upstream effect of in-cylinder swirling flow (PVC and instability waves). Both of these factors can make the velocity profiles and magnitude, at the selected inlet position (a radial distance of 200 mm from cylinder axis in this case), nonuniform and unsteady respectively. Similar effect can be on the turbulence parameters like k , and Reynolds stress components. This requires experimental measurements to be conducted in order to define the realistic boundary conditions. (Dong et al, 1993) also studied the effect of different inlet profiles for the velocity components in a swirling flow and suggested experimentally measured profiles for better simulation results. In case of outlet, since the outlet pipe length is very long, therefore, the effect of outlet boundary condition on the in-cylinder swirling flow may not be very significant. (Xia et al., 1997) have found significant effect of outlet boundary conditions but at regions close to outlet i.e. only to a small upstream distance from the outlet. The other aspect is the RANS modeling approach itself. In the RANS based models, the turbulent scales are not fully or partly resolved. Instead the whole range of turbulent scales is modeled and the simulation results represent the influence of all the turbulent scales. Thus RANS have a strong damping influence on any resolved turbulence or unsteady structures, which is desirable for steady state flows (Gyllenram et al., 2008). In case of unsteady flows, the time dependent features that unsteady RANS (URANS) may resolve is restricted only to the coherent periodic motions and not the wide range of frequencies of broadband turbulence (Spencer et al., 2009). The unsteady behavior requires the turbulence model to be able to distinguish between resolvable and unresolvable scales and the RANS based equations 161 Numerical Modeling
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<strong>Experimental</strong> <strong>and</strong> <strong>Numerical</strong> <strong>Study</strong> <strong>of</strong> <strong>Swirling</strong> Flow in Scavenging Process for 2-Stroke<br />
Marine Diesel Engines<br />
Chapter 6<br />
shear stress components are under predicted compared to experimental data<br />
in figures 4.29 & 4.32 respectively.<br />
6.3 Discussion<br />
The results <strong>of</strong> CFD simulations presented in this chapter do not show a<br />
satisfactory agreement with the experimental data. However, there are some<br />
qualitative features like pr<strong>of</strong>iles <strong>of</strong> velocity <strong>and</strong> modeled Reynolds stress<br />
components that, to some extent, have reasonable agreements. The factors<br />
affecting the performance <strong>of</strong> the CFD models possibly lie both in the<br />
treatment <strong>of</strong> turbulence <strong>and</strong> the numerical aspects.<br />
The performance <strong>of</strong> RANS based models for swirling flows have already been<br />
discussed in Section 2.4. <strong>Numerical</strong>ly, defining the boundary conditions at<br />
the inlet <strong>of</strong> the computational domain has very significant impact. In the<br />
current simulations, a constant value <strong>of</strong> the parameters like velocity<br />
components <strong>and</strong> turbulence parameters like k <strong>and</strong> have been given at<br />
the inlet. Considering the real experimental setup, this approach may not be<br />
good because the inlet in the computational domain is placed after the guide<br />
vanes <strong>and</strong> close to the contraction section. The pr<strong>of</strong>ile <strong>of</strong> velocity<br />
components may not be uniform at that radial position. The possible reasons<br />
are the wake that is generated behind the guide vanes <strong>and</strong> the upstream<br />
effect <strong>of</strong> in-cylinder swirling flow (PVC <strong>and</strong> instability waves). Both <strong>of</strong> these<br />
factors can make the velocity pr<strong>of</strong>iles <strong>and</strong> magnitude, at the selected inlet<br />
position (a radial distance <strong>of</strong> 200 mm from cylinder axis in this case), nonuniform<br />
<strong>and</strong> unsteady respectively. Similar effect can be on the turbulence<br />
parameters like k , <strong>and</strong> Reynolds stress components. This requires<br />
experimental measurements to be conducted in order to define the realistic<br />
boundary conditions. (Dong et al, 1993) also studied the effect <strong>of</strong> different<br />
inlet pr<strong>of</strong>iles for the velocity components in a swirling flow <strong>and</strong> suggested<br />
experimentally measured pr<strong>of</strong>iles for better simulation results. In case <strong>of</strong><br />
outlet, since the outlet pipe length is very long, therefore, the effect <strong>of</strong> outlet<br />
boundary condition on the in-cylinder swirling flow may not be very<br />
significant. (Xia et al., 1997) have found significant effect <strong>of</strong> outlet boundary<br />
conditions but at regions close to outlet i.e. only to a small upstream distance<br />
from the outlet.<br />
The other aspect is the RANS modeling approach itself. In the RANS based<br />
models, the turbulent scales are not fully or partly resolved. Instead the<br />
whole range <strong>of</strong> turbulent scales is modeled <strong>and</strong> the simulation results<br />
represent the influence <strong>of</strong> all the turbulent scales. Thus RANS have a strong<br />
damping influence on any resolved turbulence or unsteady structures, which<br />
is desirable for steady state flows (Gyllenram et al., 2008). In case <strong>of</strong> unsteady<br />
flows, the time dependent features that unsteady RANS (URANS) may<br />
resolve is restricted only to the coherent periodic motions <strong>and</strong> not the wide<br />
range <strong>of</strong> frequencies <strong>of</strong> broadb<strong>and</strong> turbulence (Spencer et al., 2009). The<br />
unsteady behavior requires the turbulence model to be able to distinguish<br />
between resolvable <strong>and</strong> unresolvable scales <strong>and</strong> the RANS based equations<br />
161<br />
<strong>Numerical</strong> Modeling