NUMECA is now Cadence
Blade Design Optimization
FINE™/Design3D is used to optimize the aerodynamics performances of a centrifugal compressor wheel pre-designed with FINE/Agile™.
The blades count and shape are automatically varied to maximize the total-to-total efficiency.
The compressor efficiency has increased by almost 2% without re-fitting or conversion of the preliminary design geometry. All this in less than 4 hours on a standard workstation.
Yannick Baux, Head of Turbomachinery, NUMECA International.
OPTIMIZATION SETUP DEFINITION
- 500k cells – Mixing plane – CPU Booster
- CPU time = 0.6 CPU.h/MPts
- Turnaround time =4 minon 4 cores
- Lower bound on Mass flow
- Lower bound on TT Efficiency
- Hub curve x8
- Beta angles x6
- Blade thickness x6
- Inlet Theta angle x1
- Blade count x1
DESIGN OF EXPERIMENTS POPULATION
The number of samples computed to build the DoE is kept minimal, one CFD run per free parameter. The full database computation requires no more than half an hour on a standard workstation (12 cores). Advanced data analysis tools allow verifying the accuracy of the surrogate model.
Fill the Design of Experiments
- Only 22 samples (= nb of parameters)
- Can be processed in parallel
- Turnaround time = 8 min on 44 cores (or 3h 20min on 4 cores)
Evaluate the accuracy of the surrogate model: Leave-One-Out
- For each point, build a surrogate model with all others and compare the predicted value with the accurate value from the CFD run.
OPTIMUM SEARCH (SEQUENTIAL)
Sequential search: minimum number of runs to reach the optimum design.
One candidate per design iteration
Best design 93:
- EFFTT = 0.8816
- MF = 2.052 kg/s
- PR = 1.179
78 sequential runs in the search
CPU time = 27.8 CPU.h
Turnaround time = 7h on 4 cores
OPTIMUM SEARCH (PARALLEL)
Parallel search: one point evaluate the optimum while the others explore the design space to minimize the turnaround time.
Three candidates per design iteration
One point evaluate the optimum, the others explore.
Best Design 137:
- EFFTT = 0.8826
- MF = 2.050 kg/s
- PR = 1.179
128 runs in the search
3 processed in parallel
CPU time = 41.7 CPU.h
Turnaround time = 3h30min
ANALYSIS OF VARIANCE ANOVA
Which parameters have the most influence?
- Beta angles are the most influential parameters
- Blade count is second in terms of influence
- Thickness has almost no influence
|Efficiency raise of +1,8%|
In less than 4 hours on a standard workstation, you have increased the efficiency of your preliminary design by almost 2%.