Can I read Pareto Optimal Design of a Finned Latent Heat Thermal Energy Storage Unit Using a Novel Hybrid Technique on EtoBox?

Pareto Optimal Design of a Finned Latent Heat Thermal Energy Storage Unit Using a Novel Hybrid Technique by Hamid Maleki; Mehdi Ashrafi; Nastaran Zandy Ilghani; Marjan Goodarzi; Taseer Muhammad is a scholarly article available to read on EtoBox.

What is Pareto Optimal Design of a Finned Latent Heat Thermal Energy Storage Unit Using a Novel Hybrid Technique about?

A finned latent heat thermal energy storage (LHTES) unit is considered for optimization through a hybrid procedure based on computational fluid dynamics (CFD), grouped method of data handling (GMDH) type of artificial neural network (ANN), non-dominated sorting genetic algorithms (NSGA-II), and multi-criteria decisionmaking (MCDM). Considering that optimized fins have a tremendous impact on the efficiency of finned LHTES systems, this paper considers the design variables the geometrical parameters of fins (number, length, and volume fraction). Furthermore, two of the most significant thermal energy storage (TES) systems, phase change time and total stored energy are considered objective functions. The primary purpose is to minimize the phase change time and maximize the stored energy. For this purpose, first, the effects of design variables on objective functions are studied by CFD simulations. Afterward, by importing the numerical data into the GMDH-type ANN code, polynomials are derived to predict the values of the objective functions in terms of design variables. Then, Pareto optimal points are presented using the NSGA-II algorithm and GMDH predictive models. Finally, the object

Author

Hamid Maleki; Mehdi Ashrafi; Nastaran Zandy Ilghani; Marjan Goodarzi; Taseer Muhammad

Published

2021

Language

EN