Pages that link to "Item:Q1039913"
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The following pages link to Aerodynamic optimization of turbomachinery blades using evolutionary methods and ANN-based surrogate models (Q1039913):
Displaying 14 items.
- Wind turbine design through evolutionary algorithms based on surrogate CFD methods (Q402206) (← links)
- Multi-objective optimization of turbomachinery using improved NSGA-II and approximation model (Q646297) (← links)
- A fully adaptive hybrid optimization of aircraft engine blades (Q837093) (← links)
- High-fidelity gradient-free optimization of low-pressure turbine cascades (Q2102011) (← links)
- Multi-fidelity shape optimization of hydraulic turbine runner blades using a multi-objective mesh adaptive direct search algorithm (Q2290065) (← links)
- Aerodynamic optimization of axial turbomachinery blades using parallel adaptive range differential evolution and Reynolds-averaged Navier-Stokes solutions (Q3082594) (← links)
- Multi-objective turbomachinery optimization using a gradient-enhanced multi-layer perceptron (Q3184225) (← links)
- Optimization using surrogate models and partially converged computational fluid dynamics simulations (Q3503373) (← links)
- U-Net-Based Surrogate Model for Evaluation of Microfluidic Channels (Q5057695) (← links)
- (Q5852419) (← links)
- A Conceptual Alternative Machine Learning-Based Method for Mesh Sensitivities Calculation in a Turbomachinery Blades Optimisation Framework (Q5880407) (← links)
- Rotorcraft low-noise trajectories design: black-box optimization using surrogates (Q6088531) (← links)
- Discrete adjoint gradient evaluations for linear stress and vibration analysis (Q6108672) (← links)
- A blade altering toolbox for automating rotor design optimization (Q6537199) (← links)
