4.7 Article

Multi-objective optimization of a phase change material-based shell-and-tube heat exchanger for cold thermal energy storage: experiments and numerical modeling

期刊

APPLIED THERMAL ENGINEERING
卷 215, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2022.119047

关键词

Phase change materials; Shell-and-tube heat exchanger; Thermal energy storage; Experimental validation; Multi-objective optimization; Genetic algorithm

资金

  1. Italian Ministry of Economic Development [RdS-PAR 2019-2021?]

向作者/读者索取更多资源

Latent heat thermal storage based on phase change material (PCM) in shell-and-tube heat exchangers can reduce power consumption of air conditioning systems. By optimizing the charging/discharging time of PCM and the operating conditions of the chiller, better performance can be achieved. Experimental validation shows that the optimal solution leads to a reduction in the inlet temperature by 1.25℃ and a maximum utilization of PCM by 40% of the initial amount. Further optimization results in a shell diameter reduction of 12 cm to exploit 72% of the PCM potential.
In recent years, significantly increasing demand for air conditioning systems has led to higher power con-sumption during on-peak hours. If optimized, latent heat thermal storage for chiller systems - thanks to its high storage density and compact structure - can reduce installed cooling capacity and allow the chiller to operate more continuously. Starting from the existing design, this work presents a multi-objective optimization frame-work to improve the storage performance of a phase change material (PCM)-based shell-and-tube heat exchanger. To address this issue - based on experimental data - a 2D axial-symmetric transient numerical model is first developed. To investigate the overall performance of the system - depending on geometrical features and chiller operating conditions - a parametric analysis is performed. Then, by coupling the numerical model developed in COMSOL Multiphysics environment with MATLAB, the system performance is optimized through the genetic algorithm (GA), i.e., minimizing PCM charging/discharging time, by varying the chiller operating conditions. The optimal solution is achieved under a water mass flow rate of 0.095 kg/s, implying a reduction in the inlet temperature of 1.25 ? with respect to the reference case. Results are further validated through experimental tests and discussed looking at the PCM melting and solidification processes for better exploitation of this storage technique. As the main outcome of the model optimization on user's demand, the maximum amount of PCM that can be fully exploited is equal to 40 % of the initial one. Therefore, based on this value, a further optimization step by GA is performed to define the minimum heat transfer area, resulting in a shell diameter reduction of 12 cm to exploit 72 % of the PCM potential.

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