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<p>This study aims to investigate the potential for maximizing the energy storage capacity of various types of sand, including Manufactured sand, Plaster sand, and River sand. The research examines input parameters such as flow rate and time, combining response surface methodology with face centred composite design to conduct experiments. A second-order polynomial equation is employed to assess the outcome of the dependent variable from the selected quadratic model, an ANOVA technique is conducted to evaluate the model importance and found that the model is significant for all the sand types. The predicted energy storage values are 1328.039&#xa0;kJ for Manufactured sand, 1227.054&#xa0;kJ for Plaster sand, and 1011.425&#xa0;kJ for River sand, based on optimal input parameters. These predicted values were compared with experimental outcomes, revealing an acceptable margin of error. The findings suggest that time is a critical factor influencing energy storage capacity and highlights the importance of selecting appropriate materials to improve energy storage efficiency.</p>

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Design optimization of sand based energy storage system using response surface methodology

  • 期刊论文

  • 发表日期：

    2025年8月11日

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  • S. Ananth,
  • P. Selvakumar

摘要

This study aims to investigate the potential for maximizing the energy storage capacity of various types of sand, including Manufactured sand, Plaster sand, and River sand. The research examines input parameters such as flow rate and time, combining response surface methodology with face centred composite design to conduct experiments. A second-order polynomial equation is employed to assess the outcome of the dependent variable from the selected quadratic model, an ANOVA technique is conducted to evaluate the model importance and found that the model is significant for all the sand types. The predicted energy storage values are 1328.039 kJ for Manufactured sand, 1227.054 kJ for Plaster sand, and 1011.425 kJ for River sand, based on optimal input parameters. These predicted values were compared with experimental outcomes, revealing an acceptable margin of error. The findings suggest that time is a critical factor influencing energy storage capacity and highlights the importance of selecting appropriate materials to improve energy storage efficiency.