Optimization and Computational Fluid Dynamics - Department of ...

46 Gábor Janiga
Temperature variations [K]
50
40
30
20
10
0
0.006 0.007 0.008 0.009 0.01 0.011 0.012
Average mass flow-rate of CO [g/s]
Fig. 2.16 Feasible configurations for Case B. To improve clarity only a part of the results
are shown here
erable variations have been tested by the optimization procedure, exploring
the whole parameter space before identifying the best solution. Such large
variations would certainly not have been considered by a human being carrying
out a manual optimization. The automatic optimization requires in this
case a considerable computing time but leads to a reduction of the pollutant
emission (CO) by a factor 2.5 and of the temperature variation by a factor
exceeding 20, compared to the worst feasible configuration (Fig. 2.18).
2.5 Optimization of the Standard k–ω Turbulence
Model Parameters (Case C)
Numerical simulations based on RANS are widely used for engineering problems
and complex geometries, due to a high computational efficiency. The
determination of the closure constants for RANS turbulence models is based
on dimensional analysis, theoretical observations or experiments for some
special cases like channel or pipe flows. Such experiments often consider twodimensional
flows, so that most model developments are originally suited for
two-dimensional situations. Nevertheless, these models are mostly used in
quite different – usually complex three-dimensional – configurations so that