Abstract
Heat transfer has a great effect on the energy saving of buildings. The main challenge is the description of turbulence effect. The present study conducts a computational fluid dynamics simulation of non-isothermal indoor airflow with contaminant diffusion to test the capability of four two-equation turbulence models. All two-equation turbulence models predict the similar velocity distribution, temperature distribution and concentration distribution. The SST \(k{-}\omega\) model obtains larger turbulent viscosity far away from walls than \(k{-}\varepsilon\) models, meaning that the gradients of velocity, temperature and concentration is small. The SST \(k{-}\omega\) model and the RNG \(k{-}\varepsilon\) model capture a large thermal plume above heaters. The computed temperature and carbon dioxide concentration are compared with the measurement. The standard \(k{-}\varepsilon\) model and the realizable \(k{-}\varepsilon\) model are capable of predicting a better temperature distribution. The realizable \(k{-}\varepsilon\) model has a good performance in simulating the concentration of \({\mathrm{CO}}_2\).
Similar content being viewed by others
References
Cao Q, Liu M, Li X, Lin C-H, Wei D, Ji S, Zhang TT, Chen Q (2022) Influencing factors in the simulation of airflow and particle transportation in aircraft cabins by CFD. Build Environ 207:108413
Cheng JC, Kwok HH, Li AT, Tong JC, Lau AK (2021) Sensitivity analysis of influence factors on multi-zone indoor airflow CFD simulation. Sci Total Environ 761:143298
Ebrahimi M, Mohseni M, Aslani A, Zahedi R (2022) Investigation of thermal performance and life-cycle assessment of a 3D printed building. Energy Build 272:112341
Evola G, Popov V (2006) Computational analysis of wind driven natural ventilation in buildings. Energy Build 38(5):491–501
Gilani S, Montazeri H, Blocken B (2016) CFD simulation of stratified indoor environment in displacement ventilation: validation and sensitivity analysis. Build Environ 95:299–313
Hussain S, Oosthuizen PH, Kalendar A (2012) Evaluation of various turbulence models for the prediction of the airflow and temperature distributions in atria. Energy Build 48:18–28
Launder BE, Spalding DB (1972). Lectures in mathematical models of turbulence
Li X, Yan Y, Tu J (2019) Effects of surface radiation on gaseous contaminants emission and dispersion in indoor environment - a numerical study. Int J Heat Mass Transf 131:854–862
Liu W, Wen J, Lin C-H, Liu J, Long Z, Chen Q (2013) Evaluation of various categories of turbulence models for predicting air distribution in an airliner cabin. Build Environ 65:118–131
Menter FR (1994) Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J 32(8):1598–1605
Nimarshana P, Attalage R, Perera KKC (2022) Quantification of the impact of RANS turbulence models on airow distribution in horizontal planes of a generic building under cross-ventilation for prediction of indoor thermal comfort. J Build Eng 52:104409
Pei G, Rim D (2021) Quality control of computational fluid dynamics (CFD) model of ozone reaction with human surface: Effects of mesh size and turbulence model. Build Environ 189:107513
Piña-Ortiz A, Hinojosa J, Xamán J, Navarro J (2018) Test of turbulence models for heat transfer within a ventilated cavity with and without an internal heat source. Int Commun Heat Mass Transfer 94:106–114
Posner J, Buchanan C, Dunn-Rankin D (2003) Measurement and prediction of indoor air flow in a model room. Energy Build 35(5):515–526
Rohdin P, Moshfegh B (2011) Numerical modelling of industrial indoor environments: a comparison between different turbulence models and supply systems supported by field measurements. Build Environ 46(11):2365–2374
Shan X, Xu W, Lee Y-K, Lu W-Z (2019) Evaluation of thermal environment by coupling CFD analysis and wireless-sensor measurements of a full-scale room with cooling system. Sustain Cities Soc 45:395–405
Shih T-H, Liou WW, Shabbir A, Yang Z, Zhu J (1995) A new \(k-\varepsilon\) eddy viscosity model for high reynolds number turbulent flows. Comput Fluids 24(3):227–238
Taghinia J, Rahman MM, Siikonen T (2015) Numerical simulation of airflow and temperature fields around an occupant in indoor environment. Energy Build 104:199–207
Tian Z, Tu J, Yeoh G, Yuen R (2007) Numerical studies of indoor airflow and particle dispersion by large Eddy simulation. Build Environ 42(10):3483–3492
Wang J, Priestman GH, Tippetts JR (2006). Modelling of strongly swirling flows in a complex geometry using unstructured meshes. Int J Numer Methods Heat Fluid Flow 16(8). Publisher: Emerald Group Publishing Limited 910–926
Wang M, Lin C-H, Chen Q (2012) Advanced turbulence models for predicting particle transport in enclosed environments. Build Environ 47:40–49
Wu P, Zhou J, Li N (2021) Influences of atrium geometry on the lighting and thermal environments in summer: CFD simulation based on-site measurements for validation. Build Environ 197:107853
Xu M, Yamanaka T, Kotani H (2001) Vertical profiles of temperature and contaminant concentration in rooms ventilated by displacement with heat loss through room envelopes. Indoor Air 11(2):111–119
Yakhot V (1993) Renormalization group modeling and turbulence simulations. In: International conference on near-wall turbulent flows, Arizona, Tempe
Zahedi R, Babaee Rad A (2022) Numerical and experimental simulation of gasliquid two-phase flow in 90-degree elbow. Alex Eng J 61(3):2536–2550
Zahedi R, Shaghaghi A, Tahooneh MT, Ahmadi A (2023) Numerical simulation of combustion of sulfide-biomass concentrate ingredients and contaminants in copper furnace smelting. Fut Energy 2(1):1–8
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Liu, X., Deng, B., Han, X. et al. Numerical Simulation of Temperature and Carbon Dioxide Distribution in Indoor Environment Using Two-Equation Turbulence Models. Iran J Sci Technol Trans Civ Eng 47, 1893–1907 (2023). https://doi.org/10.1007/s40996-022-01007-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40996-022-01007-4