Expertise
Optimisation and uncertainty quantification
Design of experiments, metamodels, multi-objective Pareto optimisation, topology optimisation and uncertainty quantification for material and process variability.
Named methods
- Latin Hypercube design of experiments
- Kriging and gradient boosting metamodels
- physics-informed metamodels
- genetic algorithm optimisation
- multi-objective Pareto fronts
- iterative metamodel refinement
- topology optimisation with adaptive multi-resolution
- fatigue and stress constraints
- anisotropic material topology optimisation
- uncertainty quantification for material and process variability
Contribution to a work package
Flowphys can own optimisation and UQ work packages that turn simulation campaigns into robust design spaces and Pareto sets under real manufacturing tolerances.