Abstract. Wake steering models for control purposes are typically based on analytical wake descriptions tuned to match experimental or numerical data. This study explores whether a data-driven surrogate model with high degree of physical interpretation can accurately describe the redirected wake. A linear trained large-eddy-simulation data estimates parameters such as deficit, center location a...

The global exploring feature of the surrogate model makes it a useful intermedia for design optimization. accuracy is closely related with efficiency optima-search. cokriging approach described in present studies can significantly improve and cut down turnaround time spent on modeling process. Compared to universal Kriging method, method interpolates not only sampling data, but also their assoc...

A methodology is proposed for optimal shaping of permanent magnets with non-conventional and complex geometries, used in synchronous motors. The algorithm includes artificial neural network-based surrogate model and multi-objective search based optimization method that will lead to Pareto front solutions. An interior permanent magnet topology with crescent-shaped magnets is also introduced as t...

Numerical simulations of groundwater flow are used to analyze and predict the response an aquifer system its change in state by approximating solution fundamental physical equations. The most classical methodologies, such as Finite Difference (FD) Element (FE) Methods, use iterative solvers which associated with high computational cost. This study proposes a physics-based convolutional encoder-...