Development, Application and Validation of a Quick Optimization Method for the Class of Axial Fans

[+] Author and Article Information
Konrad Bamberger

University of Siegen Paul-Bonatz-Str. 9-11 57068 Siegen Germany

Thomas Carolus

University of Siegen Paul-Bonatz-Str. 9-11 57068 Siegen Germany

1Corresponding author.

ASME doi:10.1115/1.4036764 History: Received May 03, 2016; Revised April 19, 2017


This article discusses the development, application and validation of an optimization method for the impellers of axial fans. The method is supposed to be quick, accurate and applicable to optimization at an extensive range of design points. Optimality here means highest possible total-to-static efficiency for a given design point and is obtained by an evolutionary algorithm in which the target function is evaluated by CFD-trained artificial neural networks (ANN). The ANNs were trained with steady state CFD results of approximately 14,000 distinct impellers. After this considerable onetime effort, each new fan optimization can be performed within a few minutes. It is shown that the ANNs are reliably applicable to all typical design points of axial fans according to Cordier's diagram. Moreover, an extension of the design space towards the classic realm of mixed-flow or even centrifugal fans is observed. It is also shown that the optimization method successfully handles geometrical constraints. Another focus of this article is on the application of the newly developed optimization method to numerous design points. This yields two major findings: the estimation of maximum achievable total-to-static efficiency as a function of the targeted design point as well as a quantification of the improvement over fans designed with classic methods. Both investigations are supported by flow filed analyses to aerodynamically explain the findings. Experimental validation of the method was performed with a total of nine prototypes. The positive correlation between MLP, CFD and experiment successfully validates the methodology.

Copyright (c) 2017 by ASME
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