Abstract
The forced convection (air supply jet) and the natural convection (thermal plume of passenger) co-exist in an aircraft cabin simultaneously. Due to the notable difference of the Reynolds numbers for the two convection processes, the traditional RANS method can hardly simulate the forced/natural convection flows accurately at the same time. In addition, the large geometric ratio between the main air supply inlet and the whole cabin leads to difficulties in grid generation for the cabin space. An efficient computational model based on the standard k-e model is established to solve these problems. The coefficients in the dissipative equation are modified to compensate the enlarged numerical dissipation caused by coarse grid; meanwhile, the piecewise-defined turbulent viscosity is introduced to combine the forced and natural convection. The modified model is validated by available experimental results in a Boeing 737-200 mock-up. Furthermore, the unsteady characteristic of the aircraft cabin environment is obtained and analyzed. According to the frequency analysis, it turns out that the thermal plume is the main factor of the unsteady fluctuation in cabin.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Bosbach J, Lange S, Dehne T, Lauenroth G, Hesselbach F, Allzeit M (2013). Alternative ventilation concepts for aircraft cabins. CEAS Aeronautical Journal, 4: 301–313.
Cao X, Liu J, Pei J, Zhang Y, Li J, Zhu X (2014). 2D-PIV measurement of aircraft cabin air distribution with a high spatial resolution. Building and Environment, 82: 9–19.
Craven BA, Settles GS (2006). A computational and experimental investigation of the human thermal plume. Journal of Fluids Engineering, 128: 1251–1258.
Cui W, Wu T, Ouyang Q, Zhu Y (2017). Passenger thermal comfort and behavior: a field investigation in commercial aircraft cabins. Indoor Air, 27: 94–103.
Durbin PA, Reif BAP (2010). Statistical Theory and Modeling for Turbulent Flows. Chichester, UK: John Wiley & Sons.
Ge WT (2014). Optimization design of inner-structure of the slot-jet in aircraft cabin and investigation of multi-scale characteristic in slot turbulent jet flow. Master Thesis, Tianjin University, China. (in Chinese)
Hu X, You X (2015). Determination of the optimal control parameter range of air supply in an aircraft cabin. Building Simulation, 8: 465–476.
Isukapalli SS, Mazumdar S, George P, Wei B, Jones B, Weisel CP (2013). Computational fluid dynamics modeling of transport and deposition of pesticides in an aircraft cabin. Atmospheric Environment, 68: 198–207.
Kühn M, Bosbach J, Wagner C (2009). Experimental parametric study of forced and mixed convection in a passenger aircraft cabin mock-up. Building and Environment, 44: 961–970.
Launder BE, Spalding DB (1974). The numerical computation of turbulent flows. Computer Methods in Applied Mechanics and Engineering, 3: 269–289.
Li Y, Leung GM, Tang JW, Yang X, Chao CYH, et al. (2007). Role of ventilation in airborne transmission of infectious agents in the built environment—A multidisciplinary systematic review. Indoor Air, 17: 2–18.
Li M, Zhao B, Tu J, Yan Y (2015). Study on the carbon dioxide lockup phenomenon in aircraft cabin by computational fluid dynamics. Building Simulation, 8: 431–441.
Li F, Liu J, Ren J, Cao X, Zhu Y (2016). Numerical investigation of airborne contaminant transport under different vortex structures in the aircraft cabin. International Journal of Heat and Mass Transfer, 96: 287–295.
Li J, Liu J, Wang C, Jiang N, Cao X (2017). PIV methods for quantifying human thermal plumes in a cabin environment without ventilation. Journal of Visualization, 20: 535–548.
Licina D, Pantelic J, Melikov A, Sekhar C, Tham KW (2014). Experimental investigation of the human convective boundary layer in a quiescent indoor environment. Building and Environment, 75: 79–91.
Liu W, Wen J, Lin CH, Liu J, Long Z, Chen Q (2013). Evaluation of various categories of turbulence models for predicting air distribution in an airliner cabin. Building and Environment, 65: 118–131.
Liu Y, Zhao Y, Liu Z, Luo J (2016). Numerical investigation of the unsteady flow characteristics of human body thermal plume. Building Simulation, 9: 677–687.
Lu WZ, Leung AYT, Yan SH, So ATP (2005). A preliminary parametric study on performance of SARS virus cleaner using CFD simulation. International Journal for Numerical Methods in Fluids, 47: 1137–1146.
Poussou SB, Mazumdar S, Plesniak MW, Sojka PE, Chen Q (2010). Flow and contaminant transport in an airliner cabin induced by a moving body: Model experiments and CFD predictions. Atmospheric Environment, 44: 2830–2839.
Salmanzadeh M, Zahedi G, Ahmadi G, Marr DR, Glauser M (2012). Computational modeling of effects of thermal plume adjacent to the body on the indoor airflow and particle transport. Journal of Aerosol Science, 53: 29–39.
Spalding BD (1972). Lectures in Mathematical Models of Turbulence. Salt Lake City, USA: American Academic Press.
Townsend AA (1956). The Structure of Turbulent Shear Flow. Cambridge, UK: Cambridge University Press.
Wang H, Zhai ZJ (2012). Analyzing grid independency and numerical viscosity of computational fluid dynamics for indoor environment applications. Building and Environment, 52: 107–118.
Wang C, Liu J, Li J, Guo Y, Jiang N (2017). Turbulence characterization of instantaneous airflow in an aisle of an aircraft cabin mockup. Building and Environment, 116: 207–217.
Wang C, Liu J, Li J, Li F (2018). Chaotic behavior of human thermal plumes in an aircraft cabin mockup. International Journal of Heat and Mass Transfer, 119: 223–235.
Yan Y, Li X, Tu J (2016). Effects of passenger thermal plume on the transport and distribution characteristics of airborne particles in an airliner cabin section. Science and Technology for the Built Environment, 22: 153–163.
Yang C, Zhang X, Cao X, Liu J, He F (2015). Numerical simulations of the instantaneous flow fields in a generic aircraft cabin with various categories turbulence models. Procedia Engineering, 121: 1827–1835.
Yin H, Shen X, Huang Y, Feng Z, Long Z, Duan R, Lin CH, Wei D, Sasanapuri B, Chen Q (2016). Modeling dynamic responses of aircraft environmental control systems by coupling with cabin thermal environment simulations. Building Simulation, 9: 459–468.
Zhai ZJ, Zhang Z, Zhang W, Chen QY (2007). Evaluation of various turbulence models in predicting airflow and turbulence in enclosed environments by CFD: part 1—Summary of prevalent turbulence models. HVAC&R Research, 13: 853–870.
Zhang Y, Sun Y, Wang A, Topmiller JL, Bennett JS (2005). Experimental characterization of airflows in aircraft cabins: part II - Results and research recommendations. ASHRAE Transactions, 111(2): 53–59.
Zhang Z, Chen Q (2006). Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms. Atmospheric Environment, 40: 3396–3408.
Zhang Z, Zhang W, Zhai ZJ, Chen QY (2007). Evaluation of various turbulence models in predicting airflow and turbulence in enclosed environments by CFD: part 2—Comparison with experimental data from literature. HVAC&R Research, 13: 871–886.
Zhang Y, Liu J, Pei J, Wang C (2017). Statistical analysis of turbulent thermal convection in a cabin mockup. Building and Environment, 115: 34–41.
Zitek P, Vyhlidal T, Simeunovic G, Novakova L, Cižek J (2010). Novel personalized and humidified air supply for airliner passengers. Building and Environment, 45: 2345–2353.
Acknowledgements
The work described in this paper was supported by the National Basic Research Program of China (“973” project of China) (No. 2012CB720101), grants from the National Natural Science Foundation of China (No. 11672206 and No. 11972250) and the Key Program of Natural Science Foundation of Tianjin City (No. 19JCZDJC32000).
Author information
Authors and Affiliations
Corresponding author
Electronic Supplementary Material
Rights and permissions
About this article
Cite this article
Zhao, Y., Liu, Z., Li, X. et al. A modified turbulence model for simulating airflow aircraft cabin environment with mixed convection. Build. Simul. 13, 665–675 (2020). https://doi.org/10.1007/s12273-020-0609-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12273-020-0609-2