Characterizing the convective heat transfer on stator ventilation ducts for large hydro generators with a neural network

Abstract

Purpose – The purpose of this paper is to approximate the convective heat transfer using a few non-dimensional parameters in the design process of large synchronous machines. The computed convective wall heat transfer coefficient can be used in circuit models or can be defined in numerical heat conduction (HC) models to compute the thermal field in the solid domains without the time consuming computation of the fluid domain. Design/methodology/approach – Computational fluid dynamics (CFD) has been used to include a wide range of different designs, operating conditions and cooling schemes to ensure accurate results for a wide range of possible machines. Neural networks are used to correlate the computed heat transfer coefficients to various design parameters. The data set needed to define the weights and bias layers in the network has been obtained by several CFD simulations. A comparison of the evaluated solid temperatures with those obtained using the conjugate heat transfer (CHT) method has been carried...