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Numerical prediction of the stratification performance in domestic hot water storage tanks

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  • Chandra, Yogender Pal
  • Matuska, Tomas

Abstract

An efficient storage retains thermal stratification and improves the discharging performance. Turbulent mixing between hot and cold water is the prime source of stratification destruction. In this paper quantification of turbulent missing was achieved on the basis of temperature profile, MIX number, and Richardson number. The evaluated parameters include flow rate, ΔT, and diffuser design, henceforth a direct interdependence between each was thus established. Various CFD models were developed and experimentally validated on the test rig in order to find the optimal working conditions in discharge mode. The results proved numerically that the tank working conditions can be optimized by proper selection of inlet device. For instance, slotted type inlet device sustained maximum stratification even in as adverse a condition as of turbulent inflow & low ΔT. Perforated and simple inlet devices were capable of delivering best discharge efficiency only at low flow rate of 200 l/h and were showing insignificant dependency on ΔT. However, as flow rate is increased, ΔT dependency increased. Seeing the compounded benefits of slotted inlet devices and decreased ΔT, it was concluded that slotted inlet device delivered comparatively better thermal performance at both adverse conditions i.e. high flow & low ΔT and high flow & high ΔT, however, failed to outshine the rest of the inlet devices at low flow rate & low ΔT, and low flow rate & high ΔT. These research findings can serve as guidelines to optimize the storage tank design – more specifically, inlet device based design integrated with heating system, as thermal stratification and COP of heating system – heat pumps, for example, are inherently correlated. Heat pumps are high flow rate and low ΔT devices, while, solar systems are low flow rate and high ΔT devices, Thus, opting for accurate choice of inlet device for a particular operating condition is critical.

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  • Chandra, Yogender Pal & Matuska, Tomas, 2020. "Numerical prediction of the stratification performance in domestic hot water storage tanks," Renewable Energy, Elsevier, vol. 154(C), pages 1165-1179.
  • Handle: RePEc:eee:renene:v:154:y:2020:i:c:p:1165-1179
    DOI: 10.1016/j.renene.2020.03.090
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    References listed on IDEAS

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    1. Baeten, Brecht & Confrey, Thomas & Pecceu, Sébastien & Rogiers, Frederik & Helsen, Lieve, 2016. "A validated model for mixing and buoyancy in stratified hot water storage tanks for use in building energy simulations," Applied Energy, Elsevier, vol. 172(C), pages 217-229.
    2. Savicki, Darci L. & Vielmo, Horácio A. & Krenzinger, Arno, 2011. "Three-dimensional analysis and investigation of the thermal and hydrodynamic behaviors of cylindrical storage tanks," Renewable Energy, Elsevier, vol. 36(5), pages 1364-1373.
    3. Kalogirou, Soteris A. & Bojic, Milorad, 2000. "Artificial neural networks for the prediction of the energy consumption of a passive solar building," Energy, Elsevier, vol. 25(5), pages 479-491.
    4. Wang, Zilong & Zhang, Hua & Dou, Binlin & Huang, Huajie & Wu, Weidong & Wang, Zhiyun, 2017. "Experimental and numerical research of thermal stratification with a novel inlet in a dynamic hot water storage tank," Renewable Energy, Elsevier, vol. 111(C), pages 353-371.
    5. Han, Y.M. & Wang, R.Z. & Dai, Y.J., 2009. "Thermal stratification within the water tank," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 1014-1026, June.
    6. Kalogirou, Soteris A., 2000. "Long-term performance prediction of forced circulation solar domestic water heating systems using artificial neural networks," Applied Energy, Elsevier, vol. 66(1), pages 63-74, May.
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    5. Rendall, Joseph & Abu-Heiba, Ahmad & Gluesenkamp, Kyle & Nawaz, Kashif & Worek, William & Elatar, Ahmed, 2021. "Nondimensional convection numbers modeling thermally stratified storage tanks: Richardson's number and hot-water tanks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    6. Li, Qiong & Huang, Xiaoqiao & Tai, Yonghang & Gao, Wenfeng & Wenxian, L. & Liu, Wuming, 2021. "Thermal stratification in a solar hot water storage tank with mantle heat exchanger," Renewable Energy, Elsevier, vol. 173(C), pages 1-11.
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    11. Piyatida Trinuruk & Papangkorn Jenyongsak & Somchai Wongwises, 2022. "Comparative Study of Inlet Structure and Obstacle Plate Designs Affecting the Temperature Stratification Characteristics," Energies, MDPI, vol. 15(6), pages 1-25, March.
    12. Liang, Haobin & Liu, Liu & Zhong, Ziwen & Gan, Yixiang & Wu, Jian-Yong & Niu, Jianlei, 2022. "Towards idealized thermal stratification in a novel phase change emulsion storage tank," Applied Energy, Elsevier, vol. 310(C).
    13. Abd Elfadeel, Shehab M. & Amein, Hamza & El-Bakry, M. Medhat & Hassan, Muhammed A., 2021. "Assessment of a multiple port storage tank in a CPC-driven solar process heat system," Renewable Energy, Elsevier, vol. 180(C), pages 860-873.
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