PERFORMANCE PREDICTIONS OF AIR-COOLED CONDENSERS HAVING CIRCULAR AND ELLIPTIC CROSS-SECTIONS WITH ARTIFICIAL NEURAL NETWORKS

Year 2019, Volume: 5 Issue: 3, 105 - 114, 14.03.2019

Fatih Selimefendigil

https://doi.org/10.18186/thermal.539967

Cited By: 2

Abstract

In this study, mathematical
models of air cooled condensers with circular and elliptic cross-sections were
developed and performances were evaluated with artificial neural networks. Air
velocity, orientation angle and ambient temperature were used as the input to
the neural network structure while heat transfer rate to the air was used as
the output. The data sets were generated from high fidelity, computationally
inefficient expensive three dimensional computational fluid dynamics
simulations. It was observed that artificial neural network model replaces
computational fluid dynamics model and based on the mathematical model with
artificial neural network, elliptic condensers perform better in terms of heat
transfer compared to circular ones.

Keywords

Refrigeration, Elliptic, Computational Fluid Dynamics, Artificial Neural Network

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