Evaluating the Validity of Computational Fluid Dynamics Model of Dispersion in a Complex Urban Geometry Using Two Sets of Experimental Measurements
Authors: Mohammad R. Kavian Nezhad, Carlos F. Lange, Brian A. Fleck
Abstract:
This research presents the validation study of a computational fluid dynamics (CFD) model developed to simulate the scalar dispersion emitted from rooftop sources around the buildings at the University of Alberta North Campus. The ANSYS CFX code was used to perform the numerical simulation of the wind regime and pollutant dispersion by solving the 3D steady Reynolds-averaged Navier-Stokes (RANS) equations on a building-scale high-resolution grid. The validation study was performed in two steps. First, the CFD model performance in 24 cases (eight wind directions and three wind speeds) was evaluated by comparing the predicted flow fields with the available data from the previous measurement campaign designed at the North Campus, using the standard deviation method (SDM), while the estimated results of the numerical model showed maximum average percent errors of approximately 53% and 37% for wind incidents from the North and Northwest, respectively. Good agreement with the measurements was observed for the other six directions, with an average error of less than 30%. In the second step, the reliability of the implemented turbulence model, numerical algorithm, modeling techniques, and the grid generation scheme was further evaluated using the Mock Urban Setting Test (MUST) dispersion dataset. Different statistical measures, including the fractional bias (FB), the mean geometric bias (MG), and the normalized mean square error (NMSE), were used to assess the accuracy of the predicted dispersion field. Our CFD results are in very good agreement with the field measurements.
Keywords: CFD, plume dispersion, complex urban geometry, validation study, wind flow.
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[1] 2018 revision of world urbanization prospects. Tech. rep., United Nations Department of Economic and Social Affairs (UNDESA), 2018.
[2] H. L. Higson, R. F. Griffiths “Concentration measurements around an isolated building: A comparison between wind tunnel and field data”, Atmospheric Environment, Vol. 28, No. 11, pp. 1827-1836, 1994.
[3] S. Oikawa, Y. Meng, “A field study of diffusion around a model cube in a suburban area”, Boundary-Layer Meteorology, Vol. 84, pp. 399-410, 1997.
[4] M. Lateb, R. N. Meroney, M. Yataghene, H. Fellouah, F. Saleh, M. C. Boufadel “On the use of numerical modeling for near-field pollutant dispersion in urban environment”, Environmental Pollution, Vol. 208, pp. 271-283, 2016.
[5] ASHRAE, “Building air intake and exhaust design”, ASHRAE Fundamental Handbook, American Society of Heating, Refrigerating and Air-conditioning Engineers, Atlanta, United States, 2011.
[6] N. S. Holmes, L. Morawska, “A review of dispersion modeling and its application to the dispersion of particles: an overview of different dispersion models available”, Atmospheric Environment, Vol. 40, pp. 5902-5928, 2006.
[7] ADMS 3 user guide, Cambridge Environmental Research Consultants Limited, Cambridge, UK, 2004.
[8] Tominaga, Y., Stathopoulos, T., “CFD simulation of near-field pollutant dispersion in the urban environment: A review of current modeling techniques”, Atmospheric Environment. Vol. 79, pp. 716-730, 2013.
[9] X. Huang, L. Gao, D. Guo, R. Yao, “Impacts of high-rise building on urban airflows and pollutant dispersion under different temperature stratifications: Numerical investigations”, Atmospheric Pollutant Research, Vol. 12, pp. 100-112, 2021.
[10] E. Keshavarzian, R. Jin, K. Dong, K. C. S. Kwok, Y. Zhang, M. Zhao, “Effect of pollutant source location on air pollutant dispersion around a high-rise building”, Applied Mathematical Modeling, Vol. 81, pp. 582-602, 2020.
[11] Y. Du, B. Blocken, S. Abbasi, S. Pirker, “Efficient and high-resolution simulation of pollutant dispersion in complex urban environments by island-based recurrence CFD”, Environmental Modelling and Software, Vol. 145, 2021.
[12] F. T. Silva, N. C. Reis, J. M. Santos, E. V. Goulart, C. E. Alvarez, “The impact of urban block typology on pollutant dispersion” Journal of Wind Engineering and Industrial Aerodynamics, Vol. 210, 2021.
[13] A. Ricci, I. Kalkman, B. Blocken, M. Burlando, A. Freda, and M. Repetto, “Local-scale forcing effects on wind flows in an urban environment: Impact of geometrical simplifications” Journal of Wind Engineering and Industrial Aerodynamics, Vol. 170, pp. 238-255, 2017.
[14] S.J. Mattar, M. R. Kavian Nezhad, M. Versteege, C. F. Lange, B. A. Fleck, “Validation Process for Rooftop Wind Regime CFD Model in Complex Urban Environment Using an Experimental Measurement Campaign”, Energies, 2021.
[15] C.A. Biltoft, “Customer Report for Mock Urban Setting Test”, Technical report, DPG Document No. WDTC-FR-01–121. US Army Dugway Proving Ground, Dugway, Utah, 2001.
[16] A. Speranza, V. Lucarini, “Environmental science, physical principles and applications”, Encyclopedia of Condensed Matter Physics, pp. 146-156, 2005.
[17] X. Zheng, H. Montazeri, B. Blocken, “CFD simulations of wind flow and mean surface pressure for buildings with balconies: Comparison of RANS and LES” Building and Environment, Vol. 173, 2020.
[18] H. K.Versteeg, W. Malalasekera, “Introduction to Computational Fluid Dynamics”, Second Edi., vol. M. 2012.
[19] F. R. Menter, “Two-Equation Eddy-Viscosity Turbulence Models for Engineering Applications”, AIAA Journal, Vol. 32, No. 8, pp. 1598-1605, 1994.
[20] J. Franke, A. Hellsten, H. Schlünzen, and B. Carissimo, “Guideline for the CFD Simulation of Flows in the Urban Environment: COST Action 732 Quality Assurance and Improvement of Microscale Meteorological”, no. May. 2007.
[21] B. Blocken, T. Stathopoulos, J. Carmeliet, “CFD simulation of the atmospheric boundary layer: wall function problems” Atmospheric Environment, Vol. 41, pp. 238-252, 2007.
[22] P. J. Richards and R. P. Hoxey, “Appropriate boundary conditions for computational wind engineering models using the k-ε turbulence model,” J. Wind Eng. Ind. Aerodyn., vol. 46–47, no. C, pp. 145–153, 1993.
[23] WMO Guide to Meteorological Instruments and Methods of Observation WMO-No. 8 page I.5-13.
[24] M. Milliez · B. Carissimo “Numerical simulations of pollutant dispersion in an idealized urban area, for different meteorological conditions”, Boundary Layer Meteorology. 122 (3), pp. 321-342, 2007.
[25] R.P. Donnelly, T.J. Lyons, T. Flassak, “Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling”, Atmospheric Environment. Vol. 43, pp. 4416-4423, 2009.
[26] P. Kumar, A. Feiz, S. K. Singh, P. Ngae, “An urban scale inverse modelling for retrieving unknown elevated emissions with building-resolving simulations”, Atmospheric Environment. Vol. 140, pp. 135-146, 2016.
[27] M. L. Bahlali, E. Dupont, B. Carissimo “Atmospheric dispersion using a Lagrangian stochastic approach: Application to an idealized urban area under neutral and stable meteorological conditions”, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 193, 2019.
[28] C. Teea, E.Y.K. Nga, G. Xub, “Analysis of transport methodologies for pollutant dispersion modelling in urban environments”, Journal of Environmental Chemical Engineering, Vol. 8, 2020.
[29] Yee, E., Biltoft, C., “Concentration fluctuation measurements in a plume dispersing through a regular array of obstacles”, Boundary Layer Meteorology. 111 (3), pp. 363-415, 2004.
[30] J. C. Chang, S. R. Hanna, “Air quality model performance evaluation”, Meteorological Atmospheric Physics, 87 (1-3), pp. 167-196, 2004.