Technical Papers
Sep 12, 2024

Predictions of Wind-Induced Snow Redistribution on Long-Span Building Roofs Using Two-Way Coupled Simulations

Publication: Journal of Cold Regions Engineering
Volume 38, Issue 4

Abstract

The numerical simulation of wind-induced snowdrift often employs a one-way coupled scheme that neglects the interaction between moving snow particles and turbulent wind. However, this approach can result in significant errors when the mass concentration of snowdrift near the snow surface is high. To address this issue, a modified two-way coupled scheme for simulating three-dimensional wind-induced snowdrift was developed. This scheme reasonably considers the interaction between snow particles and turbulent wind and introduces a double-loop nested framework. To illustrate the effectiveness of this method, a simulation was conducted for large-scale wind and snow fields on the roof of a terminal building in northwest China. The results were compared with field observation data of snow depth, demonstrating the applicability and superiority of the proposed method. The modified two-way coupled scheme was shown to provide a more accurate simulation of wind-induced snowdrift compared to the one-way coupled scheme. Based on this improved accuracy, predictions of wind-induced snow redistribution on the building roof were made, considering a 100-year return period for wind and snow loads. These predictions are crucial for the safety design of long-span roof structures in cold regions.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

All data, models, and codes generated or used during the study appear in the published article.

Acknowledgments

The support from the National Key R&D Program of China (Grant No. 2017YFC0803300) is highly appreciated.

Notation

The following symbols are used in this paper:
A0
empirical coefficient of snow erosion/deposition;
A
area of obstacle related to drag force;
a
local speed of sound;
Cf
aerodynamic drag coefficient of the moving obstacle;
DP
particle size of the snow particle;
Dt
coefficient of turbulent diffusion;
g
gravitational acceleration constant;
Η
dimensional effectiveness factor;
Hsal
height of the saltation layer;
h
snow depth;
I
turbulence intensity;
k
turbulence kinetic energy;
Mt
turbulent Mach number;
Pg
surface pressure;
Prt
turbulent Prandtl number for energy;
p¯
mean wind pressure;
Qsal
saltation transport rate;
Sflux
flux of snow erosion/deposition on the domain boundary;
Sij
mean rate-of-strain tensor;
T
temperature;
Usal
mean wind speed in the saltation layer;
U0
mean wind speed at height 10 m;
u¯i
mean wind component;
ui
fluctuating wind component;
u*
friction velocity;
un
nonerodable friction velocity;
ut
threshold friction velocity;
u¯z
wind velocity at height z;
V
fluid volume within unit volume;
wf
snowfall velocity;
xi
spatial position components;
YM
contribution of fluctuating dilatation to the overall dissipation rate;
Zg
atmospheric boundary-layer height;
z0
roughness length;
Φ
mass concentration of snowdrift;
α
geomorphic parameter;
β
coefficient of thermal expansion;
ε
turbulence dissipation rate;
δij
Kronecker's delta;
κ
von Karman's constant;
μ
aerodynamic viscosity;
μt
flow dynamic viscosity;
vt
flow kinematic viscosity;
ρ
flow density;
ρs
snow density; and
φ
flux of snow erosion/deposition.

References

Alfonsi, G. 2009. “Reynolds-averaged Navier–Stokes equations for turbulence modeling.” Appl. Mech. Rev. 62 (4): 040802. https://doi.org/10.1115/1.3124648.
Anderson, R. S., and P. K. Haff. 1991. “Wind modification and bed response during saltation of sand in air.” Acta Mech. Suppl. 1: 21–51. https://doi.org/10.1007/978-3-7091-6706-9_2.
Boutanios, Z., and H. Jasak. 2017. “Two-way coupled Eulerian-Eulerian simulations of drifting snow with viscous treatment of the snow phase.” J. Wind Eng. Ind. Aerodyn. 169: 67–76. https://doi.org/10.1016/j.jweia.2017.07.006.
Cao, Z., M. Liu, and P. Wu. 2019. “Experiment investigation and numerical simulation of snowdrift on a typical large-span retractable roof.” Complexity 2019 (2): 1–14. https://doi.org/10.1155/2019/5984804.
Elghobashi, S. 1994. “On predicting particle-laden turbulent flows.” Appl. Sci. Res. 52 (4): 309–329. https://doi.org/10.1007/BF00936835.
Hinze, J. O. 1975. Turbulence. New York: McGraw-Hill Publishing Corporation.
Li, J., Y. B. Peng, and Q. Yan. 2013. “Modeling and simulation of fluctuating wind speeds using evolutionary phase spectrum.” Probab. Eng. Mech. 32: 48–55. https://doi.org/10.1016/j.probengmech.2013.01.001.
Iversen, J. D., R. Greeley, B. R. White, and J. B. Pollack. 1975. “Eolian erosion of the Martian surface, part 1: Erosion rate similitude.” Icarus 26 (3): 321–331. https://doi.org/10.1016/0019-1035(75)90175-X.
Kind, R. J. 1981. “Snow drifting.” In Handbook of snow, principles, processes, management, and use, edited by D. M. Gray and D. H. Male, 338–359. Oxford: Pergamon Press.
Krishnan, L., and N. D. Sandham. 2006. “Effect of Mach number on the structure of turbulent spots.” J. Fluid Mech. 566: 225–234. https://doi.org/ 10.1017/S0022112006002412.
Lee, S.-H., Y.-H. Kim, and S.-M. Choi. 2015. “Ultimate strength of long-span buildings with P.E.B (Pre-Engineered Building) system.” Steel Compos. Struct. 19 (6): 1483–1499. https://doi.org/10.12989/scs.2015.19.6.1483.
Mo, H. M., H. P. Hong, and F. Fan. 2017. “Using remote sensing information to estimate snow hazard and extreme snow load in China.” Nat. Hazard. 89 (1): 1–17. https://doi.org/10.1007/s11069-017-2939-7.
Naaim, M., F. Naaim-Bouvet, and H. Martinez. 1998. “Numerical simulation of drifting snow: Erosion and deposition models.” Ann. Glaciol. 26: 191–196. https://doi.org/10.3189/1998aog26-1-191-196.
Nishimura, K., and J. C. R. Hunt. 2000. “Saltation and incipient suspension above a flat particle bed below a turbulent boundary layer.” J. Fluid Mech. 417: 77–102. https://doi.org/10.1017/S0022112000001014.
Okaze, T., Y. Takano, A. Mochida, and Y. Tominaga. 2015. “Development of a new k–ε model to reproduce the aerodynamic effects of snow particles on a flow field.” J. Wind Eng. Ind. Aerodyn. 144: 118–124. https://doi.org/10.1016/j.jweia.2015.04.016.
Peng, Y. B., S. F. Wang, and J. Li. 2018. “Field measurement and investigation of spatial coherence for near-surface strong winds in Southeast China.” J. Wind Eng. Ind. Aerodyn. 172: 423–440. https://doi.org/10.1016/j.jweia.2017.11.012.
Pomeroy, J. W., and D. M. Gray. 1990. “Saltation of snow.” Water Resour. Res. 26 (7): 1583–1594. https://doi.org/10.1029/WR026i007p01583.
Shih, T.-H., W. W. Liou, A. Shabbir, Z. Yang, and J. Zhu. 1995. “A new kε eddy viscosity model for high Reynolds number turbulent flows.” Comput. Fluids 24 (3): 227–238. https://doi.org/10.1016/0045-7930(94)00032-T.
Sun, X., R. He, and Y. Wu. 2018. “Numerical simulation of snowdrift on a membrane roof and the mechanical performance under snow loads.” Cold Reg. Sci. Technol. 150: 15–24. https://doi.org/10.1016/j.coldregions.2017.09.007.
Tang, G. L., H. Shi, Y. X. Wu, J. Lu, Z. Li, Q. Liu, and H. Zhang. 2016. “A variable turbulent Prandtl number model for simulating supercritical pressure CO2 heat transfer.” Int. J. Heat Mass Transfer 102: 1082–1092. https://doi.org/10.1016/j.ijheatmasstransfer.2016.06.046.
Thiis, T. K., J. Potac, and J. F. Ramberg. 2009. “3D numerical simulations and full-scale measurements of snow depositions on a curved roof.” In Proc., 5th European and African Conf. on Wind Engineering, 371–374. Florence, Italy: Firenze University Press.
Tominaga, Y. 2018. “Computational fluid dynamics simulation of snowdrift around buildings: Past achievements and future perspectives.” Cold Reg. Sci. Technol. 150: 2–14. https://doi.org/10.1016/j.coldregions.2017.05.004.
Tominaga, Y., A. Mochida, R. Yoshie, H. Kataoka, T. Nozu, M. Yoshikawa, and T. Shirasawa. 2008. “AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings.” J. Wind Eng. Ind. Aerodyn. 96 (10–11): 1749–1761. https://doi.org/10.1016/j.jweia.2008.02.058.
Tominaga, Y., T. Okaze, and A. Mochida. 2011. “CFD modeling of snowdrift around a building: An overview of models and evaluation of a new approach.” Build. Environ. 46 (4): 899–910. https://doi.org/10.1016/j.buildenv.2010.10.020.
Tominaga, Y., and T. Stathopoulos. 2007. “Turbulent Schmidt numbers for CFD analysis with various types of flow field.” Atmos. Environ. 41 (37): 8091–8099. https://doi.org/10.1016/j.atmosenv.2007.06.054.
Uematsu, T., Y. Kaneda, K. Takeuchi, T. Nakata, and M. Yukumi. 1989. “Numerical simulation of snowdrift development.” Ann. Glaciol. 13: 265–268. https://doi.org/10.3189/S0260305500008028.
Uematsu, T., T. Nakata, K. Takeuchi, Y. Arisawa, and Y. Kaneda. 1991. “Three-dimensional numerical simulation of snowdrift.” Cold Reg. Sci. Technol. 20 (1): 65–73. https://doi.org/10.1016/0165-232X(91)90057-N.
Vionnet, V., C. B. Marsh, B. Menounos, S. Gascoin, N. E. Wayand, J. Shea, K. Mukherjee, and J. W. Pomeroy. 2021. “Multi-scale snowdrift-permitting modelling of mountain snowpack.” Cryosphere 15 (2): 743–769. https://doi.org/10.5194/tc-2020-187.
Yu, X., M. Liu, J. Wang, Q. Liu, and J. Bu. 2022. “Statistical characteristics of the spatial distribution of wind and snow in the Xinjiang Uygur Autonomous Region.” Nat. Hazard. 111 (2): 1977–2009. https://doi.org/10.1007/s11069-021-05127-4.
Yu, Z., F. Zhu, R. Cao, X. Chen, L. Zhao, and S. Zhao. 2019. “Wind tunnel tests and CFD simulations for snow redistribution on 3D stepped flat roofs.” Wind Struct. 28 (1): 31–47. https://doi.org/10.12989/was.2019.28.1.031.
Zhang, G. L., Q. W. Zhang, F. Fan, and S. Z. Shen. 2021. “Numerical simulations of development of snowdrifts on long-span spherical roofs.” Cold Reg. Sci. Technol. 182: 103211. https://doi.org/10.1016/j.coldregions.2020.103211.
Zhou, X., L. Kang, M. Gu, L. Qiu, and J. Hu. 2016. “Numerical simulation and wind tunnel test for redistribution of snow on a flat roof.” J. Wind Eng. Ind. Aerodyn. 153: 92–105. https://doi.org/10.1016/j.jweia.2016.03.008.
Zhou, X., and X. Li. 2010. “Simulation of snow drifting on roof surface of terminal building of an airport.” Disaster Adv. 3 (1): 42–50.
Zhou, X., Y. Zhang, and M. Gu. 2018. “Coupling a snowmelt model with a snowdrift model for the study of snow distribution on roofs.” J. Wind Eng. Ind. Aerodyn. 182: 235–251. https://doi.org/10.1016/j.jweia.2018.09.014.
Zhou, X., Y. Zhang, L. Kang, and M. Gu. 2019. “CFD simulation of snow redistribution on gable roofs: Impact of roof slope.” J. Wind Eng. Ind. Aerodyn. 185: 16–32. https://doi.org/10.1016/j.jweia.2018.12.008.
Zhu, F., Z. Yu, L. Zhao, M. Xue, and S. Zhao. 2017. “Adaptive-mesh method using RBF interpolation: A time-marching analysis of steady snow drifting on stepped flat roofs.” J. Wind Eng. Ind. Aerodyn. 171: 1–11. https://doi.org/10.1016/j.jweia.2017.09.008.

Information & Authors

Information

Published In

Go to Journal of Cold Regions Engineering
Journal of Cold Regions Engineering
Volume 38Issue 4December 2024

History

Received: Aug 16, 2023
Accepted: Jun 11, 2024
Published online: Sep 12, 2024
Published in print: Dec 1, 2024
Discussion open until: Feb 12, 2025

Permissions

Request permissions for this article.

Authors

Affiliations

Professor, State Key Laboratory of Disaster Reduction in Civil Engineering and Shanghai Institute of Disaster Prevention and Relief, Tongji Univ., Shanghai 200092, China (corresponding author). ORCID: https://orcid.org/0000-0002-8110-8536. Email: [email protected]
Weijie Zhao
Graduate Student, College of Civil Engineering, Tongji Univ., Shanghai 200092, China.
Song Li
Graduate Student, College of Civil Engineering, Tongji Univ., Shanghai 200092, China.
Jian Zhou
Professor of Engineering, Shanghai Headquarters, East China Architectural Design & Res Inst, Shanghai 200002, China.

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share