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Wind environment around the setback building models

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
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Abstract

The irregular shape of buildings always tenders an enormous challenge to the designers. The wind velocity at the pedestrian level has a specific approach from a comfortable point of view. This investigation highlighted the characteristic of the pedestrian level wind velocity for distinct types of asymmetrical setback buildings. The passed study explored the pedestrian level effect for the axisymmetric models, while this study is based on the models that have symmetry about a single axis. This study investigates the pedestrian level flow fluctuation of setback models with single and double side setbacks at multiple levels. The double-side double setback buildings are efficient to reduce 28%–30% velocity in front of the building and 68%–70% velocity behind the building. Finally it suggests that the double side double setback building is efficient to maintain the velocity at the pedestrian level, roof level, and backside of the building. The setback building can easily control the frequency of fluctuating velocity at downstream flow for both along and across wind conditions.

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Abbreviations

BAF:

building amplification factor

CFD:

computational fluid dynamics

PSD:

power spectral density

SST:

shear-stress transport

RANS:

Reynolds-average Navier-Stokes

RNG:

re-normalisation group

b :

breadth of the model

C f :

force coefficient

C m :

moment co-efficient

C p :

pressure coefficient

f :

frequency of the oscillating signal in Hz

h :

height of the model

I :

turbulence intensity

k :

turbulence kinetic energy

l :

length of the model

S u :

Strouhal number

t* :

non-dimensional sampling time

t :

initial time step

U :

mean velocity

u :

oscillating signal at the measuring point

U h :

horizontal wind speed at an elevation Z

U x,y :

mean velocity at the pedestrian level with the presence of building at point (x, y)

U x,y domain :

mean velocity at the same location of the pedestrian level with the absence of building at point (x, y).

σ :

standard deviation of energy variation

References

  • Ansys 15 (2013). ANSYS Fluent Theory Guide.

  • Arens EA, Williams PB (1977). The effect of wind on energy consumption in buildings. Energy and Buildings, 1: 77–84.

    Article  Google Scholar 

  • Azzi Z, Habte F, Elawady A, et al. (2020). Aerodynamic mitigation of wind uplift on low-rise building roof using large-scale testing. Frontiers in Built Environment, 5: 149. DOI:10.3389/fbuil.2019.00149.

    Article  Google Scholar 

  • Baghaei Daemei A, Khotbehsara EM, Nobarani EM, et al. (2019). Study on wind aerodynamic and flow characteristics of triangular-shaped tall buildings and CFD simulation in order to assess drag coefficient. Ain Shams Engineering Journal, 10: 541–548.

    Article  Google Scholar 

  • Bairagi AK, Dalui SK (2018a). Comparison of aerodynamic coefficients of setback tall buildings due to wind load. Asian Journal of Civil Engineering, 19: 205–221.

    Article  Google Scholar 

  • Bairagi AK, Dalui SK (2018b). Aerodynamic effects on setback tall building using CFD simulation. In: Proceedings of the 2nd International Conference on Advances in Dynamics, Vibration and Control (ICADVC 2018), Durgapur, India.

  • Bairagi AK, Dalui SK (2018c). Comparison of pressure coefficient between square and setback tall building due to wind load. In: Proceedings of the 11th Structural Engineering Convention, Kolkata, India.

  • Bairagi AK, Dalui SK (2020a). Spectral density at roof of setback tall building due to time variant wind load. In: Vinyas M, Loja A, Reddy K (eds), Advances in Structures, Systems and Materials. Lecture Notes on Multidisciplinary Industrial Engineering. Singapore: Springer.

    Google Scholar 

  • Bairagi AK, Dalui SK (2020b). Distribution of wind pressure around different shape tall building. In: Vinyas M, Loja A, Reddy K (eds), Advances in Structures, Systems and Materials. Lecture Notes on Multidisciplinary Industrial Engineering. Singapore: Springer.

    Google Scholar 

  • Bairagi AK, Dalui SK (2020c). Forecasting of wind induced pressure on setback building using artificial neural network. Periodica Polytechnica Civil Engineering, 64: 751–763.

    Google Scholar 

  • Bazdidi-Tehrani F, Kiamansouri M, Jadidi M (2016). Inflow turbulence generation techniques for large eddy simulation of flow and dispersion around a model building in a turbulent atmospheric boundary layer. Journal of Building Performance Simulation, 9: 680–698.

    Article  Google Scholar 

  • Beausoleil-Morrison I (2019). Learning the fundamentals of building performance simulation through an experiential teaching approach. Journal of Building Performance Simulation, 12: 308–325.

    Article  Google Scholar 

  • Blocken B, Stathopoulos T, Carmeliet J, et al. (2011). Application of computational fluid dynamics in building performance simulation for the outdoor environment: An overview. Journal of Building Performance Simulation, 4: 157–184.

    Article  Google Scholar 

  • Blocken B, Stathopoulos T, van Beeck JPAJ (2016). Pedestrian-level wind conditions around buildings: Review of wind-tunnel and CFD techniques and their accuracy for wind comfort assessment. Building and Environment, 100: 50–81.

    Article  Google Scholar 

  • Bre F, Gimenez JM, Fachinotti VD (2018). Prediction of wind pressure coefficients on building surfaces using artificial neural networks. Energy and Buildings, 158: 1429–1441.

    Article  Google Scholar 

  • Cable M (2009). An evaluation of turbulence models for the numerical study of forced and natural convective flow in atria. Master Thesis, Queen’s University, Canada.

    Google Scholar 

  • Chan TL, Dong G, Leung CW, et al. (2002). Validation of a two-dimensional pollutant dispersion model in an isolated street canyon. Atmospheric Environment, 36: 861–872.

    Article  Google Scholar 

  • Chen X, Li A, Zhang Z, et al. (2020). Improving the wind-induced human comfort of the Beijing Olympic Tower by a double-stage pendulum tuned mass damper. The Structural Design of Tall and Special Buildings, 29(4): e1704.

    Article  Google Scholar 

  • Daemei AB (2019). Wind tunnel simulation on the pedestrian level and investigation of flow characteristics around buildings. Journal of Energy Management and Technology (JEMT), 3(1): 58–68.

    Google Scholar 

  • Djekic J, Djukic A, Vukmirovic M, et al. (2018). Thermal comfort of pedestrian spaces and the influence of pavement materials on warming up during summer. Energy and Buildings, 159: 474–485.

    Article  Google Scholar 

  • Du Y, Mak CM (2017). Effect of lift-up design on pedestrian level wind comfort around isolated building under different wind directions. Procedia Engineering, 205: 296–301.

    Article  Google Scholar 

  • Durgin FH (1997). Pedestrian level wind criteria using the equivalent average. Journal of Wind Engineering and Industrial Aerodynamics, 66: 215–226.

    Article  Google Scholar 

  • Fernando S, Fernando S, Mendis P (2020). Pedestrian wind comfort study using computational fluid dynamic (CFD) simulation. In: Dissanayake R, Mendis P (eds), ICSBE 2018. Lecture Notes in Civil Engineering, vol 44. Singapore: Springer.

    Chapter  Google Scholar 

  • Franke J (2006). Recommendations of the COST action C14 on the use of CFD in predicting pedestrian wind environment. In: Proceedings of the 4th International Symposium on Computational Wind Engineering, Yokohama, Japan.

  • Fu CL, Lee SM, Cheng CM (2006). Validation of CFD simulations on the wind loads for tall buildings’ preliminary design. In: Proceedings of the 4th International Symposium on Computational Wind Engineering, Yokohama, Japan.

  • Fu JY, Li QS, Wu JR, et al. (2008). Spectral characteristics and correlation of dynamic wind forces on a super-tall building. The Structural Design of Tall and Special Buildings, 17: 471–489.

    Article  Google Scholar 

  • Gousseau P, Blocken B, van Heijst GJF (2013). Quality assessment of Large-Eddy Simulation of wind flow around a high-rise building: Validation and solution verification. Computers & Fluids, 79: 120–133.

    Article  MATH  Google Scholar 

  • Haller G (2005). An objective definition of a vortex. Journal of Fluid Mechanics, 525: 1–26.

    Article  MathSciNet  MATH  Google Scholar 

  • Hart GC, Jain A (2011). Nonlinear response of tall buildings subjected to wind loads. The Structural Design of Tall and Special Buildings, 20: 63–65.

    Article  Google Scholar 

  • Holmes MH (2009). Introduction to the Foundations of Applied Mathematics, 2nd edn. New York: Springer.

    Book  MATH  Google Scholar 

  • Huang S, Li QS, Xu S (2007). Numerical evaluation of wind effects on a tall steel building by CFD. Journal of Constructional Steel Research, 63: 612–627.

    Article  Google Scholar 

  • Ikegaya N, Okaze T, Kikumoto H, et al. (2019). Effect of the numerical viscosity on reproduction of mean and turbulent flow fields in the case of a 1: 1: 2 single block model. Journal of Wind Engineering and Industrial Aerodynamics, 191: 279–296.

    Article  Google Scholar 

  • Itoh M (1992). Wind resistant design of a tall building with an ellipsoidal cross section. The Structural Design of Tall Buildings, 1: 119–132.

    Article  Google Scholar 

  • Jazar RN (2020). Approximation Methods in Science and Engineering. New York: Springer.

    Book  Google Scholar 

  • Jiao J, Yoshie R (2012). Large-eddy simulation of flow around obstacle arrays using drag force method of gas-solid two-phase flow. In: Proceedings of the 7th International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7).

  • Kang G, Kim JJ, Choi W (2020). Computational fluid dynamics simulation of tree effects on pedestrian wind comfort in an urban area. Sustainable Cities and Society, 56: 102086.

    Article  Google Scholar 

  • Kataoka H, Mizuno M (2002). Numerical flow computation around aeroelastic 3D square cylinder using inflow turbulence. Wind and Structures, 5: 379–392.

    Article  Google Scholar 

  • Kikumoto H, Ooka R, Han M, et al. (2018). Consistency of mean wind speed in pedestrian wind environment analyses: Mathematical consideration and a case study using large-eddy simulation. Journal of Wind Engineering and Industrial Aerodynamics, 173: 91–99.

    Article  Google Scholar 

  • Kim M, Song J, Lee H, et al. (2007). Effect of the changes in neighboring building layout onto natural ventilation scheme in buildings. In: Proceedings of the 100th Annual Conference and Exhibition of the Air and Waste Management Association 2007, Pittsburgh, PA, USA.

  • Kim Y, Kanda J (2010). Characteristics of aerodynamic forces and pressures on square plan buildings with height variations. Journal of Wind Engineering and Industrial Aerodynamics, 98: 449–465.

    Article  Google Scholar 

  • Kim YC, Kanda J (2013). Wind pressures on tapered and set-back tall buildings. Journal of Fluids and Structures, 39: 306–321.

    Article  Google Scholar 

  • Kim YC, Xu X, Yang Q, et al. (2019) Shape effects on aerodynamic and pedestrian-level wind characteristics and optimization for tall and super-tall building design. International Journal of High-Rise Buildings, 8: 235–253.

    Google Scholar 

  • Kuo CY, Tzeng CT, Ho MC, et al. (2015). Wind tunnel studies of a pedestrian-level wind environment in a street canyon between a high-rise building with a podium and low-level attached houses. Energies, 8: 10942–10957.

    Article  Google Scholar 

  • Li XX, Liu CH, Leung DYC (2005). Development of a model for the determination of air exchange rates for street canyons. Atmospheric Environment, 39: 7285–7296.

    Article  Google Scholar 

  • Liu J, Niu J (2016). CFD simulation of the wind environment around an isolated high-rise building: An evaluation of SRANS, LES and DES models. Building and Environment, 96: 91–106.

    Article  Google Scholar 

  • Liu J, Zhang X, Niu J, et al. (2019a). Pedestrian-level wind and gust around buildings with a ‘lift-up’ design: Assessment of influence from surrounding buildings by adopting LES. Building Simulation, 12: 1107–1118.

    Article  Google Scholar 

  • Liu S, Pan W, Cao Q, et al. (2019b). CFD simulations of natural cross ventilation through an apartment with modified hourly wind information from a meteorological station. Energy and Buildings, 195: 16–25.

    Article  Google Scholar 

  • Lou W, Huang M, Jin H, et al. (2010). Three-dimensional wind load effects and wind-induced dynamic responses of a tall building with X-shape. The Structural Design of Tall and Special Buildings, 19: 885–900.

    Article  Google Scholar 

  • Meng Y, Hibi K (1998). Turbulent measurments of the flow field around a high-rise building. Wind Engineers, JAWE, 1998: 55–64. (in Japanese)

    Article  Google Scholar 

  • Meng XW, Setoguchi T (2010). Development of urban design guidelines with wind tunnel simulations for downtown districts in winter cities—New urban design approaches for cold region cities. Journal of Asian Architecture and Building Engineering, 9: 355–362.

    Article  Google Scholar 

  • Moonen P, Defraeye T, Dorer V, et al. (2012). Urban Physics: Effect of the micro-climate on comfort, health and energy demand. Frontiers of Architectural Research, 1: 197–228.

    Article  Google Scholar 

  • Muehleisen RT, Patrizi S (2013). A new parametric equation for the wind pressure coefficient for low-rise buildings. Energy and Buildings, 57: 245–249.

    Article  Google Scholar 

  • Mukherjee S, Bairagi AK (2020). Power spectral density on principal building due to setback interfering building. In: Vinyas M, Loja A, Reddy K (eds), Advances in Structures, Systems and Materials. Lecture Notes on Multidisciplinary Industrial Engineering. Singapore: Springer.

    Google Scholar 

  • Nguyen VT, Nguyen TC, Nguyen J (2019). Numerical simulation of turbulent flow and pollutant dispersion in urban street canyons. Atmosphere, 10: 683.

    Article  Google Scholar 

  • Park JC, Kim IH, Jung HJ (2019). Feasibility study of fluctuating wind pressure around high-rise buildings as a potential energy-harvesting source. Energies, 12: 4032.

    Article  Google Scholar 

  • Rajasekarababu KB, Vinayagamurthy G, Selvi Rajan S (2019). Experimental and computational investigation of outdoor wind flow around a setback building. Building Simulation, 12: 891–904.

    Article  Google Scholar 

  • Rej A, Bairagi AK (2020). Wind load analysis of a tall structure with sharp and corner cut edges. In: Vinyas M, Loja A, Reddy K (eds), Advances in Structures, Systems and Materials. Lecture Notes on Multidisciplinary Industrial Engineering. Singapore: Springer.

    Google Scholar 

  • Roy K, Bairagi A (2016). Wind pressure and velocity around stepped unsymmetrical plan shape tall building using CFD simulation—A case study. Asian Journal of Civil Engineering, 17:1055–1075

    Google Scholar 

  • RWDI (2018). Pedestrian Level Wind Microclimate Assessment—Canada Water. London, UK

  • Sadrehaghighi I (2019). Turbulence Modeling—A review. CFD Open Series.

  • Šarkić Glumac A, Hemida H, Höffer R (2018). Wind energy potential above a high-rise building influenced by neighboring buildings: An experimental investigation. Journal of Wind Engineering and Industrial Aerodynamics, 175: 32–42.

    Article  Google Scholar 

  • Shimada K, Hibi K (1995). Estimation of wind loads for a super-tall building (SSH). The Structural Design of Tall Buildings, 4: 47–60.

    Article  Google Scholar 

  • Shirzadi M, Mirzaei PA, Naghashzadegan M (2017). Improvement of k-epsilon turbulence model for CFD simulation of atmospheric boundary layer around a high-rise building using stochastic optimization and Monte Carlo Sampling technique. Journal of Wind Engineering and Industrial Aerodynamics, 171: 366–379.

    Article  Google Scholar 

  • Soligo MJ, Irwin PA, Williams CJ, et al. (1998). A comprehensive assessment of pedestrian comfort including thermal effects. Journal of Wind Engineering and Industrial Aerodynamics, 77–78: 753–766.

    Article  Google Scholar 

  • Stathopoulos T (2006). Pedestrian level winds and outdoor human comfort. Journal of Wind Engineering and Industrial Aerodynamics, 94: 769–780.

    Article  Google Scholar 

  • Tamura Y, Yoshie R (2016). Advanced Environmental Wind Engineering. Tokyo: Springer.

    Book  Google Scholar 

  • Tamura Y, Xu X, Tanaka H, et al. (2017). Aerodynamic and pedestrian-level wind characteristics of super-tall buildings with various configurations. Procedia Engineering, 199: 28–37.

    Article  Google Scholar 

  • Thompson RS (1993). Building amplification factors for sources near buildings: A wind-tunnel study. Atmospheric Environment Part A General Topics, 27: 2313–2325.

    Article  Google Scholar 

  • Tominaga Y, Mochida A, Murakami S, et al. (2008a). Comparison of various revised k-ε models and LES applied to flow around a high-rise building model with 1: 1: 2 shape placed within the surface boundary layer. Journal of Wind Engineering and Industrial Aerodynamics, 96: 389–411.

    Article  Google Scholar 

  • Tominaga Y, Mochida A, Yoshie R, et al. (2008b). AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96: 1749–1761.

    Article  Google Scholar 

  • Tominaga Y, Stathopoulos T (2010). Numerical simulation of dispersion around an isolated cubic building: Model evaluation of RANS and LES. Building and Environment, 45: 2231–2239.

    Article  Google Scholar 

  • van Druenen T, van Hooff T, Montazeri H, et al. (2019). CFD evaluation of building geometry modifications to reduce pedestrian-level wind speed. Building and Environment, 163: 106293.

    Article  Google Scholar 

  • Wang H, Chen Q (2012). A new empirical model for predicting single-sided, wind-driven natural ventilation in buildings. Energy and Buildings, 54: 386–394.

    Article  Google Scholar 

  • Wang D, Yu XJ, Zhou Y, et al. (2015). A combination method to generate fluctuating boundary conditions for large eddy simulation. Wind and Structures, 20: 579–607.

    Article  Google Scholar 

  • Wang DY, Zhang YS, Zhou Y (2017). Study on occupant comfort evaluation mode of tall buildings in wind excitation based on fuzzy probability method. The Structural Design of Tall and Special Buildings, 26: e1365. DOI:https://doi.org/10.1002/tal.1365.

    Article  Google Scholar 

  • Xu X, Yang Q, Yoshida A, et al. (2017). Characteristics of pedestrian-level wind around super-tall buildings with various configurations. Journal of Wind Engineering and Industrial Aerodynamics, 166: 61–73.

    Article  Google Scholar 

  • Yakhot V, Orszag SA, Thangam S, et al. (1992). Development of turbulence models for shear flows by a double expansion technique. Physics of Fluids A: Fluid Dynamics, 4: 1510–1520.

    Article  MathSciNet  MATH  Google Scholar 

  • Yan BW, Li QS (2015). Inflow turbulence generation methods with large eddy simulation for wind effects on tall buildings. Computers & Fluids, 116: 158–175.

    Article  MATH  Google Scholar 

  • Yoshie R, Jiang G, Shirasawa T, et al. (2011). CFD simulations of gas dispersion around high-rise building in non-isothermal boundary layer. Journal of Wind Engineering and Industrial Aerodynamics, 99: 279–288.

    Article  Google Scholar 

  • Zhan J-M, Li Y-T, Wai W-HO, et al. (2019). Comparison between the Q criterion and Rortex in the application of an in-stream structure. Physics of Fluids, 31: 121701.

    Article  Google Scholar 

  • Zhang X, Weerasuriya AU, Lu B, et al. (2020). Pedestrian-level wind environment near a super-tall building with unconventional configurations in a regular urban area. Building Simulation, 13: 439–456.

    Article  Google Scholar 

  • Zhong H, Jing Y, Liu Y, et al. (2019). CFD simulation of “pumping” flow mechanism of an urban building affected by an upstream building in high Reynolds flows. Energy and Buildings, 202: 109330.

    Article  Google Scholar 

  • Zu G, Lam KM (2018). LES and wind tunnel test of flow around two tall buildings in staggered arrangement. Computation, 6: 28.

    Article  Google Scholar 

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  1. Department of Civil Engineering, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India

    Amlan Kumar Bairagi & Sujit Kumar Dalui

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  1. Amlan Kumar Bairagi
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  2. Sujit Kumar Dalui
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Correspondence to Amlan Kumar Bairagi.

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Bairagi, A.K., Dalui, S.K. Wind environment around the setback building models. Build. Simul. 14, 1525–1541 (2021). https://doi.org/10.1007/s12273-020-0758-3

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