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Influence of displacement ventilation on the distribution of pollutant concentrations in livestock housing

Publié en ligne: 31 May 2022
Volume & Edition: AHEAD OF PRINT
Pages: -
Reçu: 29 Dec 2021
Accepté: 26 Mar 2022
Détails du magazine
License
Format
Magazine
eISSN
2444-8656
Première parution
01 Jan 2016
Périodicité
2 fois par an
Langues
Anglais
Abstract

A physical model of a tall space livestock house was established using Prosim software and the relevant boundary conditions were set under the replacement of ventilation conditions. The exhaust air volume calculated by different ventilation times is simulated to the effort of the indoor pollutant concentration distribution and the measuring points are evenly arranged in the space. The study found that the replacement ventilation effect is optimal and the indoor pollutant concentration is the lowest when the indoor air supply and exhaust air volume are increased to 45 times/h.

Keywords

Introduction

Since people are increasingly demanding better indoor air quality, the need for control over and research into indoor environment characteristics such as temperature, humidity, and pollutant concentration is becoming more and more extensive. Generally speaking, people often discharge pollutants through natural ventilation outlets such as open windows [1] to improve the quality of indoor air. However, the concentration of indoor pollutants is relatively high when the natural ventilation effect is not ideal, or when the concentration of indoor pollutants is often controlled by mechanical ventilation [2,3,4].

Till date, many scholars have conducted research into the distribution of indoor pollutant concentrations. He Bo [5] and others analysed the effect of air supply speed on the distribution of velocity field and pollutant concentration field in space by numerical simulation; the height of pollutant concentration distribution increases with air supply speed, but the mixing will also be enhanced, and the air supply speed should be 0.25 m/s. Zhiping and Liang [6] analysed the effect of airflow in student dormitories under different ventilation methods using numerical simulation. By conducting numerical simulation of the velocity field in student dormitories under different ventilation methods, the authors of the study concluded that when the window-to-ground ratio was above 0.114, the ventilation effect increased very slowly if the window area continued to be increased, and when the window-to-ground ratio was below 0.114, the ventilation effect increased significantly resultant to increasing the window area.

Guo Fei [7] analysed the effects of various barn spacing and pollutant release locations on the air flow patterns and pollutant distribution of natural ventilation in barns, and concluded that the pollutants released from the downwind barn might reach the upwind barn. However, while it was found that the pollutants released from the downwind barn might reach the upwind barn, the amount was very small and could be reasonably ignored; it was effective and economical to choose two times the ridge height as the barn isolation distance for epidemic prevention when pollutants were released from the upwind barn. As the amount of ventilation has been scarcely studied in the literature, the effect of various air supply and exhaust air volumes on the distribution of indoor pollutants is obtained through multiple air exchange numbers, and with the help of FLUENT numerical simulation software, a combination of theoretical analysis and numerical simulation is used, various solution methods are applied, and the air supply and exhaust air volumes under the optimal air exchange numbers are modelled [8,9,10].

Physical and mathematical models
Physical modelling overview

The object of this study is the large space room model; the room is 20 m long, 7 m wide and 3.5 m high, with supply and exhaust air outlets on the east and west sides; the size of the air outlets is 3 m × 2 m, the pollutant CO is distributed in the centre of the room, the mass flow rate of the pollutant is set to 0.72 Kg/(m2/s), the surface size of the pollutant is 1 m×2 m, seven measurement points are set inside the room, and the measurement points are 1 m, 2 m and 3 m in the height direction, one at each of the supply and exhaust air outlets. The height direction is 1 m, 2 m and 3 m, respectively, where one measurement point is set at each of the air supply and exhaust outlets.

Fig. 1

Physical model and distribution of measurement points

Basic control equations
(ρΦ)t+div(ρuΦ)=div(ΓgradΦ)+S {{\partial \left( {\rho \Phi } \right)} \over {\partial t}} + div\left( {\rho u\Phi } \right) = div\left( {\Gamma {\kern 1pt} grad{\kern 1pt} \Phi } \right) + S

In the equation, Φ denotes a generic variable that can represent fractional velocity, temperature, constants, etc., and Γ and S denote the generalised diffusion coefficient and the generalised source term, respectively. The conservation of mass equation Φ takes 1, Γ takes 0 and S takes 0. For the conservation of momentum equation, Φ takes ui, Γ takes u and S takes - D0 + ; and for the conservation of energy equation, Φ takes T, Γ takes k/c and S takes ST. (ρk)t+(ρkui)xi=xj[(μ+μiσk)kxj]+GK+Gbρε+Sk {{\partial (\rho k)} \over {\partial t}} + {{\partial (\rho k{u_i})} \over {\partial {x_i}}} = {\partial \over {\partial {x_j}}}\left[ {\left( {\mu + {{{\mu _i}} \over {{\sigma _k}}}} \right){{\partial k} \over {\partial {x_j}}}} \right] + {G_K} + {G_b} - \rho \varepsilon + {S_k} In the equation, GK is the kinetic energy of the turbulent flow generated by the laminar velocity gradient; and Gb is the turbulent kinetic energy generated by buoyancy. x(uxC)+y(uyC)+z(uzC)=Γ(2Cx2+2Cy2+2Cz2)+S(x,y,z) {\partial \over {\partial x}}\left( {{u_x}C} \right) + {\partial \over {\partial y}}\left( {{u_y}C} \right) + {\partial \over {\partial z}}\left( {{u_z}C} \right) = \Gamma \left( {{{{\partial ^2}C} \over {\partial {x^2}}} + {{{\partial ^2}C} \over {\partial {y^2}}} + {{{\partial ^2}C} \over {\partial {z^2}}}} \right) + S(x,y,z) In the equation, Γ is the diffusion coefficient at any point; s(x, y, z) is the diffusion intensity at any point; and C is the pollutant concentration.

Simulation of operating mode settings

As the room volume is calculated according to different ventilation times, different air supply and exhaust volumes are obtained. When the concentration of pollutants in the room is high, it follows that the ventilation times should be appropriately increased. This simulation assumes a general feeding farm, and thus the number of air changes is increased from 30 times/h to 50 times/h; the specific operating mode set parameters used are shown in Table 1.

Setting of operating mode parameters

Room volume (m3) Pollutant mass flow rate [kg/(m2·s)] Number of air changes (times/h) Ventilation volume (m3)

operating mode 1 490 0.72 30 4.08
operating mode 2 490 0.72 35 4.76
operating mode 3 490 0.72 40 5.44
operating mode 4 490 0.72 45 6.13
operating mode 5 490 0.72 50 6.81
Analysis of numerical simulation results
Variation pattern of CO concentration in the room under different ventilation amounts

From the simulated data, it can be known that the concentration of CO in the room does not decrease with the increase of ventilation quantity. When the frequency of ventilation in the room is 30 times/h, the concentration of pollutants in the room is relatively high. At the same time, it will keep the value of CO concentration around 0.3–0.4 kg/m3 for a period of time. With the increase of ventilation quantity, when the frequency of ventilation is 45 times/h, the lowest concentration of pollutants in the room is 0.2 kg/m3 on average. However, continuing to increase the number of air changes in the room, when the frequency of ventilation is 50 times/h, the concentration value of pollutants in the room increased, which is not conducive to the timely discharge of pollutants. The concentration of pollutants at the air supply outlet apparently reduces as the frequency of ventilation increases. When the frequency of ventilation is up to 45–50 times/h, the concentration value of pollutants near the air supply outlet changes very little, and the concentration value of pollutants is basically reduced to zero. The change rule of the pollutant concentration value at the exhaust outlet is similar to the one inside the room, and the pollutant concentration value at the exhaust outlet is the lowest when the number of air changes is 45 times/h. After 750 min, the pollutant concentration value decreases to different degrees under different operating conditions.

The specific numerical results of the simulation are shown in Figures 2–8.

Fig. 2

Variation of CO concentration values under different operating mode at one measurement site

Fig. 3

Variation of CO concentration values under different operating modes at measurement point 2

Fig. 4

Variation of CO concentration values at the three measurement points under different operating modes

Fig. 5

Variation of CO concentration values at four measurement points under different operating modes

Fig. 6

Variation of CO concentration values at five measurement points under different operating modes

Fig. 7

Variation of CO concentration values at the six measurement points under different operating modes

Fig. 8

Variation of CO concentration values at seven measurement points under different operating modes

The increase in the amount of room ventilation makes the speed of air supply and exhaust speed to increase, and the vortex effect of airflow organisation is formed above the source of pollution, which enhances the mixing and diffusion of airflow and surrounding air and affects the effect of replacement ventilation.

Figures 2 to 8 show the measured values in different operating modes.

Airflow rate distribution in the room under different ventilation volumes

As it can be seen from Figures 9 to 13 of the simulation results, the airflow velocity field in the room increases significantly with the increase of ventilation. When the ventilation rate is 30 times/h and 35 times/h, the airflow rate is relatively small in the room, and the concentration of pollutants is comparatively high. When the ventilation rate is 40 times/h and 45 times/h, the concentration of pollutants is low and the wind speed is moderate, which is conducive to the discharge of pollutants. When the ventilation rate is increased to 50 times/h, the airflow in the room produces the vortex phenomenon and the air mixing degree is enhanced; with the increase of room ventilation, the speed of air supply and exhaust is increased and the vortex effect of airflow is formed above the pollution source. As a result, the airflow and the surrounding air mixing diffusion is enhanced, which affects the effect of replacement ventilation.

Fig. 9

Airflow rate distribution in the room for operating mode 1

Fig. 10

Airflow rate distribution in the room for operating mode 2

Fig. 11

Airflow rate distribution in the room for operating mode 3

Fig. 12

Airflow rate distribution in the room for operating mode 4

Fig. 13

Airflow rate distribution in the room for operating mode 5

The velocity vector of the airflow organisation inside the room is shown in Figures 14 to 18, and we see that it is constantly changing. When the number of air changes increases from 30 times/h to 45 times/h, the airflow organisation above the pollutant source gradually moves in the direction of the exhaust air outlet, and when the number of air changes increases to 50 times/h, the exhaust air velocity is relatively large, and a larger swirling airflow is generated above the pollutant source, which greatly reduces the effect of replacement ventilation. Following the changes of time, the airflow of pollutants near the source gradually and uniformly moved in the direction of the exhaust air outlet.

Fig. 14

Vector diagram of the airflow velocity in the room for operating mode 1

Fig. 15

Vector diagram of the airflow velocity in the room for operating mode 2

Fig. 16

Vector diagram of airflow velocities in the room for operating mode 3

Fig. 17

Vector diagram of airflow velocity in the room for operating mode 4

Fig. 18

Vector diagram of airflow velocities in the room for operating mode 5

Conclusion

When discharging pollutants from livestock and poultry houses having large spaces, the air volume of displacement ventilation needs to be reasonably controlled. The research carried out in this paper has enabled us to conclude that when the ventilation rate is calculated by the number of air changes, the pollutant concentration at the exhaust outlet is the lowest, the pollutant concentration in the room has the lowest value and the pollutants are easy to discharge when the ventilation rate is fixed at 45 times/h. Further, when the ventilation rate is less than 45 times/h, the pollutant emission rate is relatively slow. At this time, the pollutant concentration in the room is high and the air quality is poor. When the ventilation rates are between 45 times/h and 50 times/h, the vortex phenomenon of air flow is generated above the pollutants, which is not conducive to the emission of pollutants. Therefore, maintaining the ventilation rate of 45 times/h can minimise the concentration of pollutants in the room, and by using this rate, the pollutants are distributed more evenly; additionally, this rate is more conducive towards curtailing the emission of the pollutants.

Fig. 1

Physical model and distribution of measurement points
Physical model and distribution of measurement points

Fig. 2

Variation of CO concentration values under different operating mode at one measurement site
Variation of CO concentration values under different operating mode at one measurement site

Fig. 3

Variation of CO concentration values under different operating modes at measurement point 2
Variation of CO concentration values under different operating modes at measurement point 2

Fig. 4

Variation of CO concentration values at the three measurement points under different operating modes
Variation of CO concentration values at the three measurement points under different operating modes

Fig. 5

Variation of CO concentration values at four measurement points under different operating modes
Variation of CO concentration values at four measurement points under different operating modes

Fig. 6

Variation of CO concentration values at five measurement points under different operating modes
Variation of CO concentration values at five measurement points under different operating modes

Fig. 7

Variation of CO concentration values at the six measurement points under different operating modes
Variation of CO concentration values at the six measurement points under different operating modes

Fig. 8

Variation of CO concentration values at seven measurement points under different operating modes
Variation of CO concentration values at seven measurement points under different operating modes

Fig. 9

Airflow rate distribution in the room for operating mode 1
Airflow rate distribution in the room for operating mode 1

Fig. 10

Airflow rate distribution in the room for operating mode 2
Airflow rate distribution in the room for operating mode 2

Fig. 11

Airflow rate distribution in the room for operating mode 3
Airflow rate distribution in the room for operating mode 3

Fig. 12

Airflow rate distribution in the room for operating mode 4
Airflow rate distribution in the room for operating mode 4

Fig. 13

Airflow rate distribution in the room for operating mode 5
Airflow rate distribution in the room for operating mode 5

Fig. 14

Vector diagram of the airflow velocity in the room for operating mode 1
Vector diagram of the airflow velocity in the room for operating mode 1

Fig. 15

Vector diagram of the airflow velocity in the room for operating mode 2
Vector diagram of the airflow velocity in the room for operating mode 2

Fig. 16

Vector diagram of airflow velocities in the room for operating mode 3
Vector diagram of airflow velocities in the room for operating mode 3

Fig. 17

Vector diagram of airflow velocity in the room for operating mode 4
Vector diagram of airflow velocity in the room for operating mode 4

Fig. 18

Vector diagram of airflow velocities in the room for operating mode 5
Vector diagram of airflow velocities in the room for operating mode 5

Setting of operating mode parameters

Room volume (m3) Pollutant mass flow rate [kg/(m2·s)] Number of air changes (times/h) Ventilation volume (m3)

operating mode 1 490 0.72 30 4.08
operating mode 2 490 0.72 35 4.76
operating mode 3 490 0.72 40 5.44
operating mode 4 490 0.72 45 6.13
operating mode 5 490 0.72 50 6.81

Lv Chao, 2007, Exploration of fresh air volume determination methods for typical pollutant control in office buildings [D]. Harbin Institute of Technology LvChao 2007 Exploration of fresh air volume determination methods for typical pollutant control in office buildings [D]. Harbin Institute of Technology Search in Google Scholar

Wang Haobin, 2016, Study on the determination of design parameters and pollutant control effect of replacement ventilation in industrial plants [D]. Tianjin University WangHaobin 2016 Study on the determination of design parameters and pollutant control effect of replacement ventilation in industrial plants [D]. Tianjin University Search in Google Scholar

Fang Xiaolong, 2014, Numerical simulation and experimental study on the emission and purification of gaseous pollutants in sports stadiums [D]. Donghua University FangXiaolong 2014 Numerical simulation and experimental study on the emission and purification of gaseous pollutants in sports stadiums [D]. Donghua University Search in Google Scholar

Chen Diankun, 2010, Research progress on the distribution and change pattern of pollutant concentration in hot pressurized naturally ventilated rooms [J]. Refrigeration Air Conditioning & Electrical Machinery, 31(03):6–9+5 ChenDiankun 2010 Research progress on the distribution and change pattern of pollutant concentration in hot pressurized naturally ventilated rooms [J] Refrigeration Air Conditioning & Electrical Machinery 31 03 6 9+5 Search in Google Scholar

He Bo. Liu Xiao, 2011, Numerical simulation of air supply speed on pollutant concentration distribution under displacement ventilation conditions [J]. Refrigeration and Air-conditioning, 25(04):362–364+373 HeBo LiuXiao 2011 Numerical simulation of air supply speed on pollutant concentration distribution under displacement ventilation conditions [J] Refrigeration and Air-conditioning 25 04 362 364+373 Search in Google Scholar

Feng Zhiping, Cai Liang, 2008, Numerical simulation of airflow velocity field in student dormitory under different ventilation methods [J]. Building Energy & Environment, 2008(03):53–56 FengZhiping CaiLiang 2008 Numerical simulation of airflow velocity field in student dormitory under different ventilation methods [J] Building Energy & Environment 2008 03 53 56 Search in Google Scholar

Guo Fei, Wang Meizhi, Ma Zonghu, et al, 2011, Numerical simulation study of pollutant dispersion between naturally ventilated animal barns[J]. Chinese Journal of Animal Science | Chin J Anim Sci, 47(15):67–72 GuoFei WangMeizhi MaZonghu 2011 Numerical simulation study of pollutant dispersion between naturally ventilated animal barns [J] Chinese Journal of Animal Science | Chin J Anim Sci 47 15 67 72 Search in Google Scholar

Peng Shanshan, 2018, Study on the distribution state of indoor gaseous pollutants in residential buildings under natural ventilation [D]. Xi’an University of Architecture and Technology PengShanshan 2018 Study on the distribution state of indoor gaseous pollutants in residential buildings under natural ventilation [D]. Xi’an University of Architecture and Technology Search in Google Scholar

Proceedings of the 2018 China Household Appliance Technology Conference [C]. China National Electrical Appliances Association: Electrical Appliance Magazine, 2018:10 Proceedings of the 2018 China Household Appliance Technology Conference [C] China National Electrical Appliances Association: Electrical Appliance Magazine 2018 10 Search in Google Scholar

Xu Xuan, 2016, Study on the effect of wind direction and building offset on airflow movement and pollutant dispersion in intersections [D]. University of Shanghai for Science and Technology XuXuan 2016 Study on the effect of wind direction and building offset on airflow movement and pollutant dispersion in intersections [D]. University of Shanghai for Science and Technology Search in Google Scholar

Yunus Emre Cetin, Mete Avci, Orhan Aydin, 2020, Particle dispersion and deposition in displacement ventilation systems combined with floor heating. 26(8):1019–1036 YunusEmre Cetin MeteAvci OrhanAydin 2020 Particle dispersion and deposition in displacement ventilation systems combined with floor heating 26 8 1019 1036 10.1080/23744731.2020.1760637 Search in Google Scholar

Xiaochen Liu, Xiaohua Liu, Tao Zhang, 2020, Influence of air-conditioning systems on buoyancy driven air infiltration in large space buildings: A case study of a railway station. 210 XiaochenLiu XiaohuaLiu TaoZhang 2020 Influence of air-conditioning systems on buoyancy driven air infiltration in large space buildings: A case study of a railway station 210 10.1016/j.enbuild.2020.109781 Search in Google Scholar

Xiao Ye, Yanming Kang, Xiufeng Yang, Ke Zhong, 2018, Temperature distribution and energy consumption in impinging jet and mixing ventilation heating rooms with intermittent cold outside air invasion[J]. Energy & Buildings XiaoYe YanmingKang XiufengYang KeZhong 2018 Temperature distribution and energy consumption in impinging jet and mixing ventilation heating rooms with intermittent cold outside air invasion [J]. Energy & Buildings Search in Google Scholar

Zhao Fuyun, Chen Pan, Zhang Dongdong, 2018, Numerical evaluation of multiple indicators of indoor air environment under displacement ventilation and mixed ventilation [J]. Engineering Journal of Wuhan University, 51(09):823–830 ZhaoFuyun ChenPan ZhangDongdong 2018 Numerical evaluation of multiple indicators of indoor air environment under displacement ventilation and mixed ventilation [J] Engineering Journal of Wuhan University 51 09 823 830 Search in Google Scholar

Liu Yanyang, Cui Liang, Zhang Ye, et al, 2018, Simulation and analysis of replacement ventilation system of potato raw material storage based on COMSOL [J]. Journal of Chinese Agricultural Mechanization, 39(10):65–70 LiuYanyang CuiLiang ZhangYe 2018 Simulation and analysis of replacement ventilation system of potato raw material storage based on COMSOL [J] Journal of Chinese Agricultural Mechanization 39 10 65 70 Search in Google Scholar

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