MATHEMATICAL SIMULATION OF ROOM CLIMATE PARAMETERS
Abstract
The efficient air distribution is directly connected with the possibility of predicting the reliable air parameters. The reliable description of speed and temperature fields in the housing capacity is provided by the mathematical simulation methods based on Navier-Stokes differential equations. To estimate the room climate provided by ventilation and air conditioning systems, the parameter reflecting heat sensitivity should be used. This parameter is detected using three-dimensional fields of thermophysical values obtained by mathematical simulation. The paper presents results of room climate mathematical simulation for three different schemes of air distribution in a room. The Predicted Mean Vote obtained by mathematical simulation using C language software code allows analyzing three schemes of the air distribution for the room climate.
About the Author
DARIA M. Denisikhina
Saint-Petersburg State University of Architecture and Civil Engineering
Russian Federation
Russian Federation
References
1. Nielsen P.V., Allard F., Awbi H.B., Davidson L., Schälin A. Computational fluid dynamics in ventilation design. REHVA Guide Book 10. RHEVA. 2007.
2. Li Y., Nielsen P.V. CFD and ventilation research . Indoor Air. 2011. V. 21(6). Pp. 442–453.
3. Villafruela J.M., Castro F., José J.F., Saint-Martin J. Comparison of air change efficiency, contaminant removal effectiveness and infection risk as IAQ indices in isolation rooms. Energy and Buildings. 2013. V. 57. Pp. 210–219.
4. Rim D., Novoselac A. Ventilation effectiveness as an indicator of occupant exposure to particles from indoor sources. Building and Environment. 2010. V. 45. Pp. 1214–1224.
5. Walikewitz N., Janicke B., Langner M., Meier F., Endlicher W. The difference between the mean radiant temperature and the air temperature within indoor environments: A case study during summer conditions. Building and Environment. 2015. V. 84. Pp. 151–161.
6. Fanger P.O. Calculation of thermal comfort: introduction of a basic comfort equation. ASHRAE Transactions. 1967. V. 73(2). II.4.1–III.4.20
7. Hoof J. Forty years of Fangers model of thermal comfort: comfort for all? Indoor Air. 2008. V. 18. Pp. 182–201.
8. Cheng Y., Fong M. L., Yao T., Lin Z., Fong K. F. Uniformity of stratum-ventilated thermal environment and thermal sensation. Indoor Air. 2014. V. 24. Pp. 521–532.
9. Dudarev A.A., Sotnikov A.G. Mikroklimaticheskii komfort i vozdukhoraspredelenie: neskol'ko shagov navstrechu [Room climate and air distribution: a few steps forward]. Inzhenernye Sistemy. AVOK – Severo-Zapad. 2013. No. 1. Pp. 16–23. (rus)
10. Nguyen A. T., Singh M. K., Reiter S. An adaptive thermal comfort model for hot humid SouthEast Asia. Building and Environment. 2012. V. 56. Pp. 291–300.
11. Zhou X., Ouyang Q., Zhu Y., Feng C., Zhang X. Experimental study of the influence of anticipated control on human thermal sensation and thermal comfort. Indoor Air. 2014. V. 24. Pp. 171–177.
12. ASHRAE Fundamentals Handbook 2013, SI edition, American Society of Heating, Refrigerating, and Air-Conditioning Engineers. Atlanta. 2013.
13. Fedorovich G.V. Parametry mikroklimata, obespechivayushchie komfortnye usloviya truda [Room climate parameters for comfortable working conditions]. Bezopasnost' i okhrana truda. 2010. No. 1. Pp. 75–79. (rus)
14. Timofeeva E.I., Fedorovich G.V. Ekologicheskii monitoring parametrov mikroklimata [Environmental monitoring of room clomate]. Moscow : NTM-Zashchita. 2005. 212 p. (rus)
15. Najjaran A. Determining natural convection heat transfer coefficient of human body . TSEST Transaction on Control and Mechanical Systems. 2012. V. 1. No. 8. Pp. 362–369.
16. Voelker C., Maempel S., Kornadt O. Measuring the human body’s microclimate using a thermal manikin//Indoor Air. 2014. V. 24. Pp. 567–579.
17. Denisikhina D.M. Konvektivno-radiatsionnyi teploobmen cheloveka v zadachakh matematicheskogo modelirovaniya raspredelennykh parametrov mikroklimata v pomeshcheniyakh [Convective and radiative heat transfer of human body for mathematical simulation of room climate distribution parameters]. Vestnik grazhdanskikh ingenerov. 2014. No. 8. Pp. 143–150. (rus)
18. Heschl C., Inthavong K., Sanz W., Tu J.Y. Nonlinear eddy viscosity modeling and experimental study of jet spreading rates // Indoor Air. 2014. V. 24. Pp. 93–102.
Review
For citations:
Denisikhina D.M. MATHEMATICAL SIMULATION OF ROOM CLIMATE PARAMETERS. Vestnik of Tomsk state university of architecture and building. 2015;(3):183-193. (In Russ.)
Views:
569
Email this article 