Optimization of melting time of solar thermal energy storage unit containing spring type heat transfer enhancer by Taguchi based grey relational analysis


Journal of Energy Storage, vol.47, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 47
  • Publication Date: 2022
  • Doi Number: 10.1016/j.est.2021.103671
  • Journal Name: Journal of Energy Storage
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Keywords: Solar thermal energy storage, Spring type heat transfer enhancer, Grey relational analysis, ANOVA, Melting time, Time dependant enhancement ratio, PHASE-CHANGE MATERIAL, CHANGE MATERIAL PCM, NUMERICAL-ANALYSIS, PERFORMANCE, NANOPARTICLES, CONDUCTIVITY, TEMPERATURE, ENCLOSURES, SYSTEM, TUBE
  • Gazi University Affiliated: Yes


© 2021 Elsevier LtdThe major concern of this research study was determining the optimum parameters affecting melting time of paraffin wax used for storing artificial solar energy and time dependant enhancement ratio of thermal energy storage unit using Taguchi based grey relational analysis. The influence of the varied wire diameter, spring diameter and spring pitch on the performance of melting time and time dependant enhancement ratio of latent heat thermal energy storage unit was examined. L9 (three factors, three levels) orthogonal array was selected to design experiments. The obtained experimental results were optimized using grey relational analysis taking account the optimization as a single-objective problem instead of multi-objective problem. The optimal levels as the highest wire diameter and spring pitch and the lowest spring diameter with grey relational analysis was determined. The contribution ratios of parameters were identified by applying ANOVA analysis to find out which factor had more impact on melting time and time dependant enhancement ratio. The correlation equations of melting time and time dependant enhancement ratio depending on determining parameters were carried out by using the Regression analysis. The confirmation results revealed that the obtained data from Regression analysis were line up with the experimental results according to error analysis.