New design approach for compact evacuated tube collector/storage units

Author's Department

Mechanical Engineering Department

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Mohamed Osman, Omar Huzayyin, Mohamed El-Morsi

Document Type

Research Article

Publication Title

Journal of Energy Storage

Publication Date

Fall 11-1-2022




The conventional collector design procedures require extensive time and computational cost. This paper presents a systematic methodology for designing novel evacuated tube collector/storage systems (ETCS). This paper presents a novel methodology that integrates the system decomposition concept with different numerical modeling techniques to optimize the ETCS performance with minimum computational requirements. The presented methodology includes using a single evacuated tube filled with phase change material as the system building block (SBB) of the ETCS system. The enthalpy-porosity and effective heat capacity (EHC) computational fluid dynamics (CFD) methods are used to model the SBB of the novel ETCS based on the required level of details. The CFD models are used to investigate the effect of design configurations and the type of PCM on the thermal performance of the SBB. Moreover, a simplified model for the SBB is developed and used to design an efficient collector/storage unit. The results showed that the EHC model saved the computational time from 2350 min to 6 min compared to the conventional enthalpy-porosity technique with an error of <5 %. Moreover, the use of Rubitherm SP58 increased the energy storage capacity (ESC) of the SBB to 505 kJ compared 417 kJ,375 kJ, and 293 kJ for PCMs Alex 600, paraffin 54, and C22, respectively. The simplified model is used to generate a new design for the ETCS based on the optimum SBB design that uses SP58 with a glass diameter of 58 mm and length 1800 mm. The final ETCS design obtained from the design algorithm consists of four parallel sets of tubes with five tubes in each set. The paper showed the capability of the proposed methodology to design an effective and practical ETCS using minimum computational time and cost.

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