DOI QR코드

DOI QR Code

Efficiency of Different Roof Vent Designs on Natural Ventilation of Single-Span Plastic Greenhouse

플라스틱 단동온실의 천창 종류에 따른 자연환기 효과

  • Rasheed, Adnan (Department of Agricultural Engineering, Kyungpook National University) ;
  • Lee, Jong Won (Department of Horticulture Environment System, Korea National College of Agriculture and Fisheries) ;
  • Kim, Hyeon Tae (Department of Bio-Industrial Machinery Enineering., GyeongsangNational University (Institute of Agricultural and Life Sciences)) ;
  • Lee, Hyun Woo (Department of Agricultural Engineering, Kyungpook National University)
  • 라쉬드아드난 (경북대학교 농업토목공학과) ;
  • 이종원 (한국농수산대학 원예환경시스템학과) ;
  • 김현태 (경상대학교 생물산업기계공학과) ;
  • 이현우 (경북대학교 농업토목공학과)
  • Received : 2019.06.30
  • Accepted : 2019.07.23
  • Published : 2019.07.30

Abstract

In the summer season, natural ventilation is commonly used to reduce the inside air temperature of greenhouse when it rises above the optimal level. The greenhouse shape, vent design, and position play a critical role in the effectiveness of natural ventilation. In this study, computational fluid dynamics (CFD) was employed to investigate the effect of different roof vent designs along with side vents on the buoyancy-driven natural ventilation. The boussinesq hypothesis was used to simulate the buoyancy effect to the whole computational domain. RNG K-epsilon turbulence model was utilized, and a discrete originates (DO) radiation model was used with solar ray tracing to simulate the effect of solar radiation. The CFD model was validated using the experimentally obtained greenhouse internal temperature, and the experimental and computed results agreed well. Furthermore, this model was adopted to compare the internal greenhouse air temperature and ventilation rate for seven different roof vent designs. The results revealed that the inside-to-outside air temperature differences of the greenhouse varied from 3.2 to $9.6^{\circ}C$ depending on the different studied roof vent types. Moreover, the ventilation rate was within the range from 0.33 to $0.49min^{-1}$. Our findings show that the conical type roof ventilation has minimum inside-to-outside air temperature difference of $3.2^{\circ}C$ and a maximum ventilation rate of $0.49min^{-1}$.

여름철에 자연환기는 온실의 온도를 낮추는데 중요한 역할을 한다. 온실의 형태, 환기창 종류, 환기창의 위치 등은 자연환기 성능에 큰 영향을 미친다. 본 연구에서는 전산유체역학(CFD)을 이용하여 다양한 천창구조에 대하여 측창에 따른 부력환기 효과를 비교분석 하였다. Boussinnesq 가정을 사용하여 전체 계산영역에 대한 부력효과를 시뮬레이션 하였다. 또한 RNG $K-{\varepsilon}$ 난류모델을 사용하였다. 일사량 효과를 시뮬레이션 하기 위해 Solar ray tracing과 함께 Discrete originates (DO) radiation 모델을 사용하였다. 실험온실 내부의 온도를 측정하여 CFD모델을 검증하였으며, 실험값과 계산값이 잘 일치하는 것으로 나타났다. 7가지의 천창구조에 대하여 온실의 내외부 온도차이와 환기횟수를 비교하였다. 내외부온도의 차이는 $3.2{\sim}9.6^{\circ}C$ 범위로 나타났고, 환기횟수는 $0.33{\sim}0.49min^{-1}$ 범위로 나타났다. 고깔형 천창구조 온실의 경우 내외부 온도차이가 $3.2^{\circ}C$로 가장 낮았고 환기횟수도 $0.49min^{-1}$로 가장 높게 나타나 환기효과가 가장 우수한 것으로 나타났다.

Keywords

References

  1. Baeza, E.J., J.J. Perez-Parra, J.I. Montero, B.J. Bailey, J.C. Lopez and J.C. Gazquez. 2009. Analysis of the role of sidewall vents on buoyancy-driven natural ventilation in parraltype greenhouses with and without insect screens using computational fluid dynamics. Biosystems Engineering. 104(1): 86-96. https://doi.org/10.1016/j.biosystemseng.2009.04.008
  2. Bartzanas, T., T. Boulard and C. Kittas. 2004. Effect of vent arrangement on windward ventilation of a tunnel greenhouse. Biosystems Engineering. 88(4): 479-490. https://doi.org/10.1016/j.biosystemseng.2003.10.006
  3. Bartzanas, T., M. Kacira, H. Zhu, S. Karmakar, E. Tamimi, N. Katsoulas, I.B. Lee and C. Kittas. 2013. Computational fluid dynamics applications to improve crop production systems. Computers Electronics in Agriculture. 93: 151-167. https://doi.org/10.1016/j.compag.2012.05.012
  4. Benni, S., P. Tassinari, F. Bonora, A. Barbaresi, D.J.E. Torreggiani and Buildings. 2016. Efficacy of greenhouse natural ventilation: Environmental monitoring and cfd simulations of a study case. 125: 276-286. https://doi.org/10.1016/j.enbuild.2016.05.014
  5. Bournet, P., S.O. Khaoua and T. Boulard. 2007. Numerical prediction of the effect of vent arrangements on the ventilation and energy transfer in a multi-span glasshouse using a bi-band radiation model. Biosystems Engineering. 98(2):224-234. https://doi.org/10.1016/j.biosystemseng.2007.06.007
  6. Campen, J. and G. Bot. 2003. Determination of greenhousespecific aspects of ventilation using three-dimensional computational fluid dynamics. Biosystems Engineering. 84(1):69-77. https://doi.org/10.1016/S1537-5110(02)00221-0
  7. Fatnassi, H., T. Boulard, C. Poncet and M. Chave. 2006. Optimisation of greenhouse insect screening with computational fluid dynamics. Biosystems Engineering. 93(3): 301-312. https://doi.org/10.1016/j.biosystemseng.2005.11.014
  8. Haxaire, R., T. Boulard and M. Mermier. 2000. Greenhouse natural ventilation by wind forces. International Society for Horticultural Science (ISHS), Leuven, Belgium, 31-40.
  9. Hong, S.-W., V. Exadaktylos, I.-B. Lee, T. Amon, A. Youssef, T. Norton and D. Berckmans. 2017. Validation of an open source cfd code to simulate natural ventilation for agricultural buildings. Computers Electronics in Agriculture. 138:80-91. https://doi.org/10.1016/j.compag.2017.03.022
  10. Jung-Soo, H., L. In-Bok, K. Kyeong-Seok and H. Tae-Hwan. 2014. Analysis on internal airflow of a naturally ventilated greenhouse using wind tunnel and piv for cfd validation. Protected Horticulture and Plant Factory. 23(4): 391-400. https://doi.org/10.12791/KSBEC.2014.23.4.391
  11. Kacira, M., S. Sase and L. Okushima. 2004a. Effects of side vents and span numbers on wind-induced natural ventilation of a gothic multi-span greenhouse. Japan Agricultural Research Quarterly: JARQ. 38(4): 227-233. https://doi.org/10.6090/jarq.38.227
  12. Kacira, M., S. Sase and L. Okushima. 2004b. Optimization of vent configuration by evaluating greenhouse and plant canopy ventilation rates under wind-induced ventilation. Transactions of the ASAE. 47(6): 2059. https://doi.org/10.13031/2013.17803
  13. Lee, I.-B. and T.J.T.O.T.A. Short. 2001. Verification of computational fluid dynamic temperature simulations in a fullscale naturally ventilated greenhouse. Transactions of the ASAE. 44(1): 119-127. https://doi.org/10.13031/2013.2303
  14. Lee, I.-B. and Short. 2000. Two-dimensional numerical simulation of natural ventilation in a multi-span greenhouse. Transactions of the ASAE. 43(3): 757. https://doi.org/10.13031/2013.2759
  15. Lee, S.-Y., I.-B. Lee and R.-W. Kim. 2018. Evaluation of wind-driven natural ventilation of single-span greenhouses built on reclaimed coastal land. Biosystems Engineering. 171: 120-142. https://doi.org/10.1016/j.biosystemseng.2018.04.015
  16. Lopez, A., D.L. Valera and F. Molina-Aiz. 2011. Sonic anemometry to measure natural ventilation in greenhouses. Sensors. 11(10): 9820-9838. https://doi.org/10.3390/s111009820
  17. Mistriotis, A., G.P.A. Bot, P. Picuno and G. Scarascia-Mugnozza. 1997. Analysis of the efficiency of greenhouse ventilation using computational fluid dynamics. Agricultural and Forest Meteorology. 85(3): 217-228. https://doi.org/10.1016/S0168-1923(96)02400-8
  18. Pontikakos, C., K.P. Ferentinos, T.A. Tsiligiridis and A.B. Sideridis. 2006. Natural ventilation efficiency in a twin-span greenhouse using 3d computational fluid dynamics. Proceedings of the 3rd, Athens, Greece.
  19. Rasheed, A., J. Lee and H. Lee. 2018. Development and optimization of a building energy simulation model to study the effect of greenhouse design parameters. Energies. 11(8): 1-19.
  20. Senhaji, A., M. Mouqallid and H. Majdoubi. 2019. Cfd assisted study of multi-chapels greenhouse vents openings effect on inside airflow circulation and microclimate patterns. Open Journal of Fluid Dynamics. 9(2): 21.
  21. Shklyar, A. and A. Arbel. 2004. Numerical model of the threedimensional isothermal flow patterns and mass fluxes in a pitched-roof greenhouse. Journal of Wind Engineering and Industrial Aerodynamics. 92(12): 1039-1059. https://doi.org/10.1016/j.jweia.2004.05.008
  22. Tong, G., D. Christopher and B. Li. 2009. Numerical modelling of temperature variations in a chinese solar greenhouse. Computers Electronics in Agriculture. 68(1): 129-139. https://doi.org/10.1016/j.compag.2009.05.004