Optimization and Computational Fluid Dynamics - Department of ...

6 Numerical Optimization for Advanced Turbomachinery Design 171
Isentropic Mach distribution
Y(m)
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
Initial database sample
After 1 modification
After 11 modifications
After 13 modifications
0
0 0.1 0.2 0.3 0.4 0.5
X/Cax
0.6 0.7 0.8 0.9 1
1.2
0.8
0.4
0
−0.4
(a)
Initial database sample
After 1 modification
After 13 modifications
−0.8
−1 −0.6 −0.2 0.2 0.6 1 1.4 1.8
X(m)
(b)
Fig. 6.17 Variation of (a) Mach number and (b) blade geometry during convergence
9. It indicates that during the first design iterations, the ANN predictions
are not very accurate because the database does not sufficiently cover the
relevant design space. However this shortcoming is remediated by adding
new geometries to the database. Since these blades are close to the desired
operating point they provide very valuable information and the ANN becomes
more and more accurate. Starting from iteration 13, the ANN predictions
are very reliable. This illustrates the self-learning capacity of the proposed