In recent years, significantly increasing demand for air conditioning systems has led to higher power consumption 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 framework 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 °C 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.
Multi-objective optimization of a phase change material-based shell-and-tube heat exchanger for cold thermal energy storage: experiments and numerical modeling
Mauro G. M.;Mongibello L.
2022-01-01
Abstract
In recent years, significantly increasing demand for air conditioning systems has led to higher power consumption 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 framework 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 °C 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
