Retrieval of parameters in micromixer with obstacle by cascade‐forward‐type artificial neural network: Comparison of four training algorithms under noisy data
Abstract:Two parameters are retrieved in a passive Y ‐type micromixer with circular obstacle by cascade‐forward‐type artificial neural network (CFANN). The governing equations are solved by the finite volume method, under specific boundary conditions. The numerical model is then used to compute velocity profile and mixing efficiency, for different values of the Reynolds number. Thus, the velocity profiles along with Reynolds number (Re) and mixing efficiency (η) constitute the input–output pair of data. These data are u… Show more
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