Design of Experiments and optimization of aircraft design
In the frame of a collaborative project with Dassault Aviation, Scilab Enterprises developed an advanced modeling and optimization platform (Scilab Optimisation Platform) integrating features in data analysis and Design of Experiment (DoE), and covering the following functional fields:
- Data management
- Modeling
- Optimization
Data management
- Load and generate existing DOE (iSight,…) : possibility to add its own DOE generator
- Response simulation using external tools (openFOAM, CATIA, CCM+,…) or Scilab functions
- 2D visualization of factors and responses
Modeling
Selection among various modelers: DACE (Kriging), LOLIMOT (LOcal LInear Model Tree, a fast neural network) ,
Parameter configuration
Multiple model management with best model selection
Possibility to select points:
- Learning point
- Validation points
- Bad points (simulation issues,…)
Visualisation and optimisation
Execution and 2D visualization:
- Response: all factors, two factors
- Correlation
Responses coefficients setting
Optimizer:
- Selection between various algorithms: non-linear (with optim), constraint (with fmincon), genetic algorithms (with optim_nsga2),…
- Possibility to add its own algorithm
- Interactive configuration
Visualization:
- Optimal point
- Pareto frontier
- Robustness