Skip to main content
SpringerLink
Log in

Research on optimization and design methods for air distribution system based on target values

  • Research Article
  • Published:
Building Simulation Aims and scope Submit manuscript

Abstract

To achieve sufficient air conditioning of large buildings, reasonable air distribution in indoor spaces is an effective method for creating stratified air conditioning. Therefore, optimizing the air distribution in large buildings is extremely significant. In this paper, we expound on a new method for air distribution design and optimization based on target value evaluation and summarize the relevant design processes based on an orthogonal test and by decoupling the effects of the size of the tuyère, airflow temperature, air-supply angle and velocity on air distribution. Then, we present a design case. To optimize the distribution of a lateral air supply in winter, the deflection angle, velocity and temperature of the air supply can be determined in turn. For the large and tall building types addressed in this paper, the optimal air-supply angle is 2°, the optimal air-supply velocity is 8 m/s, and the optimal air-supply temperature is 19 °C.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

a :

outlet dimensionless turbulence coefficient

Ar :

Archimedes number

Ar m :

Archimedes number of model situations

Ar p :

Archimedes number of actual situations

Cg:

free fall acceleration similarity scale

C 1 :

length similarity scale

\({C_{\Delta {T_0}}}\) :

temperature difference similarity scale

C q :

air-supply volume similarity scale

C q :

heat similarity scale

\({C_{{T_{\rm{u}}}}}\) :

temperature similarity scale

\({C_{{u_0}}}\) :

velocity similarity scale

d 0 :

air inlet diameter (m)

g :

free fall acceleration (m/s2)

G k :

generated turbulence kinetic energy due to the mean velocity gradients

k :

turbulent kinetic energy (m2/s2)

m j :

jth simulated value (m/s)

n 1 :

number larger than the number of test points for the target value

n 2 :

number smaller than the number of test points for the target value

S :

the modulus of the mean rate-of-strain tensor

T :

target value

T 0 :

jet outlet temperature (K)

T n :

ambient air temperature (K)

T x :

axial temperature of jet x at the outlet (K)

T u :

thermodynamic temperature (K)

t i :

jth experimental value (m/s)

u 0 :

air-supply velocity (m/s)

u x :

axial velocity starting from the pole to a distance of x from the calculated section (m/s)

x :

distance from the pole to the calculated section (m)

x i :

horizontal jet distance (m)

y i :

longitudinal deflection distance of the jet (m)

α :

air expansion coefficient

β :

angle between the jet and the horizontal plane (°)

δ :

deviation between the experimental value and the simulated value

α k :

turbulent Prandtl numbers for k

α ε :

turbulent Prandtl numbers for ε

ε :

turbulent dissipation rate (m2/s3)

ΔT 0 :

temperature difference (K)

μ :

molecular viscosity

μ t :

turbulent viscosity

ρ :

fluid density (kg/m3)

References

  • Awbi HB (2003). Ventilation of Buildings. London: Taylor & Francis.

    Google Scholar 

  • Chen Y, Gu L, Zhang J (2015). EnergyPlus and CHAMPS-Multizone co-simulation for energy and indoor air quality analysis. Building Simulation, 8: 371–380.

    Article  Google Scholar 

  • Cheng Y, Zhang S, Huan C, Oladokun MO, Lin Z (2019). Optimization on fresh outdoor air ratio of air conditioning system with stratum ventilation for both targeted indoor air quality and maximal energy saving. Building and Environment, 147: 11–22.

    Article  Google Scholar 

  • Gao R, Fang Z, Li A, Liu K, Yang Z, Cong B (2018a). A novel low-resistance tee of ventilation and air conditioning duct based on energy dissipation control. Applied Thermal Engineering, 132: 790–800.

    Article  Google Scholar 

  • Gao R, Liu K, Li A, Fang Z, Yang Z, Cong B (2018b). Biomimetic duct tee for reducing the local resistance of a ventilation and air-conditioning system. Building and Environment, 129: 130–141.

    Article  Google Scholar 

  • Gao R, Wang C, Li A, Yu S, Deng B (2018c). A novel targeted personalized ventilation system based on the shooting concept. Building and Environment, 135: 269–279.

    Article  Google Scholar 

  • Gao R, Zhang H, Li A, Wen S, Du W, Deng B (2020). A new evaluation indicator of air distribution in buildings. Sustainable Cities and Society, 53: 101836.

    Article  Google Scholar 

  • Guo ZY, Tao WQ, Shah R (2005). The field synergy (coordination) principle and its applications in enhancing single phase convective heat transfer. International Journal of Heat and Mass Transfer, 48: 1797–1807.

    Article  Google Scholar 

  • Guo F, Zhang J, Shan M, Yang X (2018). Analysis on the optimum matching of collector and storage size of solar water heating systems in building space heating applications. Building Simulation, 11: 549–560.

    Article  Google Scholar 

  • Han L, Zhang J, Guo J (2005). Numerical simulation on air distribution optimize of Pengshui underground hydropower station. Building Energy & Environment, 2005(3): 76–79. (in Chinese)

    Google Scholar 

  • Huang Y, Wang Y, Liu L, Nielsen PV, Jensen RL, Yan F (2015). Reduced-scale experimental investigation on ventilation performance of a local exhaust hood in an industrial plant. Building and Environment, 85: 94–103.

    Article  Google Scholar 

  • Lai T, Gao R, Li H, Li A, Yang B, Melikov AK (2020). Air distribution of oxygen supply through guardrail slot diffusers in high-altitude hypoxic areas. Building and Environment, 179: 106852.

    Article  Google Scholar 

  • Li A, Zhang Y, Hu J, Gao R (2014). Reduced-scale experimental study of the temperature field and smoke development of the bus bar corridor fire in the underground hydraulic machinery plant. Tunnelling and Underground Space Technology, 41: 95–103.

    Article  Google Scholar 

  • Li Y, Li X (2015). Natural ventilation potential of high-rise residential buildings in Northern China using coupling thermal and airflow simulations. Building Simulation, 8: 51–64.

    Article  Google Scholar 

  • Liu S, Novoselac A (2015). Air Diffusion Performance Index (ADPI) of diffusers for heating mode. Building and Environment, 87: 215–223.

    Article  Google Scholar 

  • Li Y, O’Neill Z (2018). A critical review of fault modeling of HVAC systems in buildings. Building Simulation, 11: 953–975.

    Article  Google Scholar 

  • Luo N, Weng W, Xu X, Fu M (2018). Experimental and numerical investigation of the wake flow of a human-shaped manikin: Experiments by PIV and simulations by CFD. Building Simulation, 11: 1189–1205.

    Article  Google Scholar 

  • Margason RJ (1993). Fifty years of jet in cross flow research. In: Proceedings of AGARD, Computational and Experimental Assessment of Jets in Cross Flow Conference, Winchester, UK.

  • Nielsen PV (2004). Computational fluid dynamics and room air movement. Indoor Air, 14: 134–143.

    Article  Google Scholar 

  • Nielsen PV (2015). Fifty years of CFD for room air distribution. Building and Environment, 91: 78–90.

    Article  Google Scholar 

  • Saarinen P, Kalliomäki P, Koskela H, Tang JW (2018). Large-eddy simulation of the containment failure in isolation rooms with a sliding door—An experimental and modelling study. Building Simulation, 11: 585–596.

    Article  Google Scholar 

  • Sundell J (2004). On the history of indoor air quality and health. Indoor Air, 14: 51–58.

    Article  Google Scholar 

  • Takleh HR, Zare V (2019). Performance improvement of ejector expansion refrigeration cycles employing a booster compressor using different refrigerants: Thermodynamic analysis and optimization. International Journal of Refrigeration, 101: 56–70.

    Article  Google Scholar 

  • Teixeira JC, Lomba R, Teixeira SF, Lobarinhas P (2012). Application of CFD tools to optimize natural building ventilation design. In: Proceedings of the International Conference on Computational Science and Its Applications.

  • van Hooff T, Blocken B, Defraeye T, Carmeliet J, van Heijst GJF (2012). PIV measurements and analysis of transitional flow in a reduced-scale model: Ventilation by a free plane jet with Coanda effect. Building and Environment, 56: 301–313.

    Article  Google Scholar 

  • Vojkůvková P, Sikula O, Kral T (2016). Optimization of air distribution of social hall. Applied Mechanics and Materials, 824: 649–656.

    Article  Google Scholar 

  • Walker C, Tan G, Glicksman L (2011). Reduced-scale building model and numerical investigations to buoyancy-driven natural ventilation. Energy and Buildings, 43: 2404–2413.

    Article  Google Scholar 

  • Weng WG, Fan WC (2003). Mitigation of backdraft with water mist: A reduced-scale experimental study. Process Safety Progress, 22: 163–168.

    Article  Google Scholar 

  • Yang B, Melikov AK, Kabanshi A, Zhang C, Bauman FS, et al. (2019). A review of advanced air distribution methods — theory, practice, limitations and solutions. Energy and Buildings, 202: 109359.

    Article  Google Scholar 

  • Yuan F, You S (2007). CFD simulation and optimization of the ventilation for subway side-platform. Tunnelling and Underground Space Technology, 22: 474–482.

    Article  Google Scholar 

  • Zhai Z, Jin Q (2018). Identifying decaying contaminant source location in building HVAC system using the adjoint probability method. Building Simulation, 11: 1029–1038.

    Article  Google Scholar 

  • Zhang T, Chen QY (2007). Novel air distribution systems for commercial aircraft cabins. Building and Environment, 42: 1675–1684.

    Article  Google Scholar 

  • Zhou P, Huang G, Zhang L, Tsang KF (2015). Wireless sensor network based monitoring system for a large-scale indoor space: data process and supply air allocation optimization. Energy and Buildings, 103: 365–374.

    Article  Google Scholar 

Download references

Acknowledgements

This research project was sponsored by the National Key R&D Program of China (No. 2017YFC0702800), the National Natural Science Foundation of China (No. 51878533 and No. 51508442), the Natural Science Foundation of Shaanxi Province (No. 2019JM-233), and the Industrialization Fund of the Shaanxi Provincial Department of Education (No. 19JC023).

Author information

Authors and Affiliations

  1. School of Building Services Science and Engineering, Xi’an University of Architecture and Technology, Xi’an, 710055, China

    Ran Gao, Hengchun Zhang, Angui Li & Shihao Wen

  2. School of Thermal Engineering, Shandong Jianzhu University, Jinan, Shandong, 250101, China

    Ran Gao & Angui Li

  3. China Railway First Survey & Design Institute Group, Xi’an, 710043, China

    Wuyi Du & Baoshun Deng

Authors
  1. Ran Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hengchun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Angui Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shihao Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wuyi Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Baoshun Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ran Gao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, R., Zhang, H., Li, A. et al. Research on optimization and design methods for air distribution system based on target values. Build. Simul. 14, 721–735 (2021). https://doi.org/10.1007/s12273-020-0679-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12273-020-0679-1

Keywords

Search

Navigation