Searched for: author%3A%22Lau%2C+F.%22
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document
Gamme, S. (author), De Oliveira Andrade, G.L. (author), Ragni, D. (author), Lau, F. (author)
A fast, linear scaling vortex method is presented to study inviscid incompressible flow problems involving one or more actuator disks. Building upon previous efforts that were limited to axi-symmetric flow cases, the proposed methodology is able to handle arbitrary configurations with no symmetry constraints. Applications include the conceptual...
conference paper 2017
document
De Oliveira Andrade, G.L. (author), Balbino dos Santos Pereira, R. (author), Timmer, W.A. (author), Ragni, D. (author), Lau, F. (author), van Bussel, G.J.W. (author)
There are many ways to learn from data. Our first experiment consisted in reproducing the way aerodynamicists work [2] with a genetic optimizer. The data pool was too narrow and asymptotic tendencies were unreliable. Our 2nd Experiment, a simple version of [4], had a virtually unlimited data pool and used neural networks. Results were better,...
poster 2016