The 26th Annual International Conference of Iranian Society of Mechanical Engineers-ISME2018 24-26 April, 2018, School of Mechanical Engineering, Semnan University, Semnan, Iran.
ISME2018-1205
Investigation in performance of a hybrid personalized ventilation (PV) with under-floor air distribution (UFAD) system Bahram Rahmati1, Ali Heidarian2, Amir Mohammad Jadidi 3 1
Semnan, Semnan University;
[email protected] Semnan, Semnan University;
[email protected] 3 Semnan, Semnan University;
[email protected]
2
Abstract In this article, combining the under-floor air distribution (UFAD) with personalized ventilation (PV) system, we tried to improve the performance of a UFAD system. The simulation of PV-UFAD system was investigated in a small office room with two office workers, in AirpakFluent software. Two Vertical desk grills (VDG) were considered on the desks of the office workers as the PV system. Computational fluid dynamics (CFD) was employed for assessment of the local thermal discomfort, indoor air quality (IAQ), Fanger’s thermal comfort index (PMV-PPD) and energy consumption. Then, the performance of combination compared with standalone UFAD system. As the results showed, the optimum performance was obtained by combining UFAD and PV. Improvements in IAQ, suitable value of temperature/velocity around the occupant’s head and improvements in thermal sensation were achieved by hybrid PV-UFAD systems. Also, by evaluation of energy saving of UFAD and PV-UFAD, 15.3% and 17.3% reduction in energy consumption was achieved compared to a traditional mixing ventilation (MV) system, respectively. Keywords: Under-floor air distribution (UFAD), Personalized ventilation (PV), Thermal comfort, Indoor air quality (IAQ), Energy saving Introduction UFAD systems are one of the most effective and economical ventilation methods in improvement of indoor air quality (IAQ), indoor thermal comfort (ITC), productivity and health compared to MV systems [1]. In UFAD system, fresh air enters the room by swirl diffusers placed on the floor. The fresh air is diffused across the room and transfers heat and particles from heat sources at the occupied zone (OZ) to the upper zone (UZ) where the warm and polluted air exits through the ceiling exhaust vent with minimal effect on occupant’s thermal comfort. By this phenomenon caused by buoyancy forces, qualified air circulates properly over the breathing zone. However, UFAD has a lot of barriers. For example, one of the famous barriers of UFAD is called “warm head and cold feet”. One of the good strategies for covering the barriers is usage of personalized ventilation (PV) as an assistance ventilation system. PV systems provide individually a control for occupants by entering the fresh air close to the occupants before its mixing with polluted environment air which causes significantly improvements in IAQ, ITC and energy saving [2]. A PV
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system includes vertical desk grills (VDG), computer monitor panel (CMP) and movable panel (MP) [3]. Gao et al. [4] analyzed the combination of PV systems with displacement ventilation (DV) and mixing ventilation (MV). The results showed improvements in IAQ and ITC. Also, they reported the combination between PV and DV were better strategies than combination of PV with MV. However, the advantage of PV depended highly on the proper interactions between PV and background ventilation system. He et al. [5] by a CFD study on a room equipped with PV investigated the exhaled droplet transmission between occupants with variable background systems like DV, MV and UFAD. In that study combination of PV and MV increased the IAQ in the breathing zone. However, improvement in IAQ with interaction of DV and UFAD depended on the particle size. Also, one of the famous integrations in the field of stratified air distribution (STRAD) systems is the combination of PV and desk displacement ventilation system (DDV). DDV systems introduced for better ventilation effectiveness by creating a hypothetical micro-climate area around the occupants. In a DDV system the displacement diffuser is placed under the worker’s desk which gives more flexibility features compared to a DV system. Loomans [6] by using of VDG improved the response time and step response of DDV system. The combination is known as the improved desk displacement ventilation (DDV+). Of course, all of the interactions between systems had not suitable results and may lead negative effects on the performance or errors in the transmission of pollutants [7]. The pervious researches in combination of UFAD and PV systems are insufficient. So, by comparison between UFAD and PV-UFAD in local thermal discomfort, IAQ, PMV-PPD and energy consumption in Airpak software, we tried to determine the advantage of hybrid PV-UFAD system in all of the mentioned indexes. Methods Simulation of the PV-UFAD system was performed in a typical office room with 5.16 m length, 3.65 m width and 2.5 m height. Internal head sources included 2 thermal mannequins, 2 PC-cases, 2 PC-monitors, 2 light simulators and 4 ceiling lamps. Two case studies were prepared. Case 1 was made to represent the UFAD standalone system and case 2 was designed to show the PV-UFAD system. Figure 1 and 2 shows the case 1 and case 2, respectively. The released heat from each internal heat sources is listed in Table 1.
Table 1. The summary conditions of heat sources in the office
Internal heat sources Occupants PC-case PC-monitor Light-Simulator Ceiling Lamps Total
Figure 1. schematic view of case 1
Cooling load (W) 76×2 50×2 65×2 25×2 68×4 704
To obtain temperature, velocity and mean age of air in the room, the computational fluid dynamics (CFD) was employed to simulate the governing equations numerically. The following mass, momentum and energy conservation equations were assumed to be in three dimensional turbulent, steady state and incompressible fluid flow. Reynolds average method (RANS) in Cartesian coordinates was applied to relate the Reynolds stresses to the mean velocity gradients by Boussinesq approximation. Calculations were performed for all structural cubic cells in three dimensions. Continuity equation: ∇ ∙ (𝜌𝑣⃗) = 0
Figure 2. schematic view of case 2
According to Figure 1 and 2, the return vent (0.4 m × 0.15 m) was located at the western wall. According to pervious researches on optimal height of return vent [8], to create a proper IAQ, ITC and acceptable energy saving, the return vent was placed at the height of 1.3 m from the floor. Also, this model used ceiling exhaust vent (0.45 m × 0.45 m) to maximize the energy saving [9]. According to Ahmad et al. [10], the air volume through the return vent was considered 65% of the total inlet airflow. The total air volume which was considered for ventilation in this office was 8 ACH (air change per hour). The supply temperature was considered 20 (ºC) for all of the inlet diffusers. In case 1 the total air volume divided into 2 swirl diffuser. But, in case 1 the VDG units were consist 0.86 ACH of total air volume. The rest of the fresh air enters through one swirl diffuser in the middle of the room. The position of VDG unit is revealed in Figure 3.
(1)
Where, ρ and 𝑣⃗ are the density and velocity vector of air, respectively. Momentum equation: 𝜕 (2) (𝜌𝑣⃗) + ∇ ∙ (𝜌𝑣⃗𝑣⃗) = −∇𝑃 + ∇ ∙ (𝜏̅̅) + 𝜌𝑔⃗ 𝜕𝑡 Where P is the static pressure of air, 𝜌𝑔⃗ is the gravitational body force and 𝜏̅̅ is the stress tensor. Energy conservation: 𝜕 (𝜌ℎ) + ∇ ∙ (𝜌ℎ𝑣⃗) = ∇ ∙ [(𝑘 + 𝑘𝑡 )∇𝑇] + 𝑆ℎ (3) 𝜕𝑡 Where h is the sensible enthalpy (ℎ = 𝑇 𝐶 𝑑𝑇 , 𝑇 = 298.15 𝐾), k is the molecular ∫𝑇 𝑝 𝑟𝑒𝑓 𝑟𝑒𝑓
conductivity, 𝑘𝑡 is the conductivity due to turbulent 𝐶 𝜇 transport (𝑘𝑡 = 𝑝 𝑡), and 𝑆ℎ is the source term which 𝑃𝑟𝑡
includes all defined volumetric heat sources. To calculate the turbulent viscosity, the indoor zero equation was employed for simulating airflow in the room. Selecting appropriate turbulent model leads to predicting accurate turbulent viscosity and this subject has an important effect on the precision of simulation. The following equation was obtained by Chen et al [11] and was successfully tested for simulating the indoor temperature gradient:
μt = 0.03874 ρvl
Figure 3. The position of VDG in the model ISME2018, 24-26 April, 2018
(4)
Where ρ is the fluid density, v is the local velocity and l is the distance from the nearest wall and 0.03874 is an empirical constant. This model is ideally suited for predicting indoor air flows that consider natural convection, forced convection, mixed convection and displacement ventilation. For simulating the radiation, the Discrete Ordinates (DO) radiation model was used to compute radiation between heat sources and objects in the room. The discrete ordinates (DO) radiation model solves the
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0 20 22 24 26 28 30
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T(˚C) T(˚C) V(m/s) V(m/s) Figure 4. Comparison between numerical and experiment data of temperature profile along; (a) x=-2.58m and z=0.61m, (b) x=-1.72m and z=1.825m; Comparison between numerical and experiment data of velocity profile along; (c) x=-2.58m and z=0.61m, (d) x=-1.72m and z=1.825m Table 2. The walls boundary condition (℃)
Wall North South East West Floor Ceiling
Figure 5. The schematic view of validation model
Radiative transfer equation. The SIMPLE algorithm with finite-volume was used with a second order upwind scheme for the convective terms. The calculation was considered as converge when the residuals reaches as low as 10-4. Validation of CFD results Checking the accuracy and correctness of CFD results, the comparison between numerical temperature and velocity profiles with experimental profiles is necessary. Because there were no experimental results for the target model, the experimental study which was performed by Kobayashi et al. [12] on the UFAD system was selected to validate the numerical model. The dimension of room was 5.16 m length, 3.65 m width and 2.27 m height. The internal heat sources included 2 simplified thermal mannequin into 2 hollow blocks with 75 W heat load for each block, 68 W for each ceiling lamp. The released heat by PC-1 and PC-2 were 108.5 W and 173.4 W, respectively. The total inlet air volume was ISME2018, 24-26 April, 2018
Temperature (℃) 26.8 26.8 28.6 25.8 25.0 27.4
4.4 ACH with 19℃ of air temperature. The results of temperature/velocity validation are shown in Figure 4. Figure 5 shows the schematic view of experimental geometry. The boundary conditions which was used for the external walls were dirichlet boundary conditions as listed in Table 2. The boundary conditions of external walls were the same for both target model and validation case. The accuracy of a numerical simulation is an important issue that must be checked. One of the base checkings is grid independency. The geometry of cells and the number of cells play a critical role for precise simulation of the physical model. Three dimensions structured hexahedral grid was considered for meshing both geometries (target model and validation case) which gives the highest accuracy of solution compared to other mesh geometries. To achieve better results, the number of cells were risen near the heat sources, occupant and higher or lower points of the wall. The number of cells which were tested as grid independent solution, were 715230, 1412426 and 2105061. There was no significant change in temperature by increase from 1412426 cells to 2105061 cells. Results and Discussion One of the most important indexes in evaluation of people’s satisfaction in indoor environment is the local thermal discomfort. The temperature profile in STRAD systems is not homogenous like MV systems and it
Table 3. Local thermal discomfort results
Temperature 𝑇𝑓𝑒𝑒𝑡 (℃) 𝑇ℎ𝑒𝑎𝑑 (℃) ∆𝑇(℃)
Occupant 1 Case 1 Case 2 22.6 22.9 26.2 24.0 3.6 1.1
Occupant 2 Case 1 Case 2 22.5 22.7 25.6 24.0 3.1 1.3
Increases from floor to ceiling [12]. According to the ISO7730 [13] if the difference between head and feet temperature exceeds more than 3ºC, occupants experience the local thermal discomfort. Table 3, shows the result of numerical temperature of occupant’s head, feet and the difference between them. According to Tham [14] the suitable temperature range for the office workers in tropics is between 20-24 ºC. So, in case 1, the head temperatures of both occupants were more than allowable value. Also, the local thermal discomfort risk was high in case 1. That’s because of the considerable difference between occupants’ feet and head temperature. However, in case 2, by the aim of VDG, the head temperatures of occupants were in the suitable value. Also, the difference between feet and head temperature of the occupants were low. Figure 6 and Figure 7 shows the temperature contours in the room at the central plane z = 1.825 m for case 1 and 2, respectively. Another key index is the air velocities around the breathing zone. Gong et al. [15] reported the acceptable air velocity at occupant’s head is between 0.3 to 0.45 m/s at 23℃ and 0.3 to 0.9 m/s at 26℃. Table 4 shows the value of airspeed in inhaled zone for both occupants. In case 1, the facial air velocities of occupants were not sufficient and were under desirable range. But, in case 2, the facial air velocity was suitable for both occupants. Figure 8 and Figure 9, shows the velocity contours for occupant 1 in case 1 and 2, respectively.
Figure 6. The temperature contour (℃) for case 1
Figure 7. The temperature contour (℃) for case 1 ISME2018, 24-26 April, 2018
Table 4. The velocity value at inhaled zone (m/s)
Case studies 1 2
Occupant 1 0.02 0.29
Occupant 2 0.02 0.30
In the case of indoor thermal comfort for numerical solutions the approach of the classic steady-state model by Fanger was used. This is the first model for predicting the thermal comfort in 1970 and still is the most common way for calculating the indoor thermal comfort. Fanger’s model has the following four environmental variables: air temperature, air velocity, mean radiant of the surrounding surface and relative humidity, and two personal variables of clothing insulation and activity level. The result is known as the predicted mean vote (PMV). Predicated percentage of dissatisfaction (PPD) developed by Fanger only examines the individual vote of occupants, not a large group of people. ISO7730 introduced three categorize for PMV: 1 (PMV±0.2), 2 (PMV±0.5) and 3 (PMV±0.7) which class 1 with PPD < 10 percent provides 90% acceptability for residents [16-17]. Cloth isolation for summer was considered 0.5 in this model. The inside and outside relative humidity in this office was considered 40% and 70%, respectively [18]. The area which was considered for evaluations of PMV-PPD criteria was around the whole body of each occupant. According to the results of PMV and PPD in Table 5, both scenarios were located in class 1 of PMV. The closest thermal sensation to neutral condition was in case 2. But, UFAD standalone system in case 1 had the maximum thermal discomfort risk than case 1 because of the out of range PPD value. However, hybrid performance passed the PPD criteria.
Figure 8. The velocity contour (m/s) for case 1
Figure 9. The velocity contour (m/s) for case 2
Table 5. PMV-PPD indexes results for case studies
Case studies 1 2
Occupant 1 PMV PPD 0.08 10.0 0.03 9.75
Occupant 2 PMV PPD 0.08 10.2 0.03 9.80
The local mean age of air (MAA) indicator was used to calculate the indoor air quality (IAQ) and the air freshness in this study. MAA is defined as the average age of the air in a certain position in space, when the air is sent into space for the first time. The MAA is obtained from the following equation [19]. 𝜕 𝜕 𝜕 𝜕𝜏 (𝜌𝜏) + (𝜌𝑢𝑗 𝜏) = (𝛤 )+𝜌 (5) 𝜕𝑡 𝜕𝑥𝑗 𝜕𝑥𝑗 𝜕𝑥𝑗 𝜏 = 0 and
𝜕𝜏 𝜕𝑥𝑗
= 0 represents as the boundary condition
of air inlet and the boundary condition of walls and exhaust vent, respectively. For calculating the MAA in breathing zone a cubature was assumed in front of each occupants with 1 until 1.1 m height from the floor. The results are presented in Table 6. The lower value of local MAA shows more air freshness in the breathing zone. By comparing the performance of cases 1 and 2, we can conclude the hybrid PV-UFAD reduced the MAA for occupant 1 and 2 approx. 93 and 63 seconds, respectively. That’s because of VDG units which were close to the office workers. Figure 10 and Figure 11, shows the MAA contours in the room at the central plane z = 1.825 m for case 1 and 2, respectively. In STRAD ventilation systems, the achieved energy saving is highly depended on temperature stratification and the performance of each scenario to remove the heat loads. The ventilation area in STRAD system is not the whole room. By ventilating just the occupied zone the required temperature is higher than MV systems and the low velocity speed is sufficient.
Figure 10. The MAA contour (s) for case 1
Figure 11. The MAA contour (s) for case 2
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Table 6. The local Mean age of air (s) results
Case Studies 1 2
Occupant 1 317 251
Occupant 2 336 243
By these two factors the required cooling load from the coil is much lower than MV systems. For mixing ventilation, the cooling coil load can be written as: 𝑄𝑐𝑜𝑖𝑙 = 𝑄𝑠𝑝𝑎𝑐𝑒 + 𝑄𝑣𝑒𝑛𝑡
(6)
Where 𝑄𝑠𝑝𝑎𝑐𝑒 (W) and 𝑄𝑣𝑒𝑛𝑡 (W) are the space cooling load and the ventilation load, respectively. The space cooling load in STRAD systems is calculated by the following method which is suggested by Cheng et al [20]. Q space = Cp ∙ ṁr ∙ (Tr − Ts ) + Cp ∙ ṁe ∙ (Te − Ts )
(7)
Where, ṁr and ṁe (kg/s) are the return and exhaust flow rates, respectively. Tr (℃) is the outlet air temperature of return vent, Te (℃) is the exhaust air temperature, Ts (℃) is the supply air temperature. The coil-cooling load is calculated as the following equation: Q coil = Q vent + Q space − Cp × ṁe × (Te − Tset )
(8)
Where, Tset is the set-point temperature which is equal to the height of 0.8 m or 1.2m from the floor. By Comparing Eq. (6) with Eq. (8) the term of Cp × ṁe × (Te − Tset ) is the saving energy in coil capacity of displacement ventilation compared to mixing ventilation. According to the results of Table 7 the maximum energy saving was achieved by hybrid PV-UFAD systems in case 2 approx. 17.3% in this office. That’s because of the lower Tset and Tr compared to UFAD standalone system in case 1. So, the system performance in removing the heat loads from occupied zone to upper zone in case 1 was more effective than case 2. Therefore, Hybrid performance increased the energy saving of the system approx. 2% with better IAQ and ITC, zero possibility of local thermal discomfort and suitable air velocity in breathing zone. Conclusions The results are listed below: The UFAD system couldn’t prepare the suitable facial temperature. Also, the local thermal discomfort possibility was considerable in this system. But, the PV-UFAD system was acceptable in local thermal discomfort criteria and facial temperature of occupants. The UFAD performance was unacceptable in facial desirable velocity range. Hybrid performance created a desirable velocity field in front of the office workers. By comparison of IAQ between PV-UFAD and UFAD, we can conclude that the IAQ significantly improved by using the PV-UFAD systems because of VDG units.
Table 7. The local Mean age of air (s) results
Energy saving variables 𝑇𝑠𝑒𝑡 (℃) 𝑇𝑟 (℃) 𝑇𝑒 (℃) ∆𝑄𝑐𝑜𝑖𝑙 (W) ∆𝑄𝑐𝑜𝑖𝑙 (%) 𝑄𝑠𝑝𝑎𝑐𝑒
Case 1 24.6 26.6 28.1 124.5
Case 2 24.3 26.2 28.1 134.1
15.5
17.3
The PPD value was out of the standard ISO7730 range in the UFAD system and occupants experienced thermal discomfort. By hybrid system the occupants’ thermal sensation improved and it guaranteed the occupants’ thermal comfort. The heat removal performance in PV-UFAD system was better than the UFAD system. Therefore, the energy consumption of PVUFAD was low. According to the results, the energy saving of a well-designed PV-UFAD was 17.3% lower than MV system.
Nomenclature Variable information 𝜌 P 𝑔⃗ 𝜏̿ ℎ 𝑐𝑝 𝜏 𝑄Vent 𝑄space 𝑄Coil 𝑚̇𝑟 𝑚̇𝑒 𝑇𝑟 𝑇𝑒 𝑇𝑠 𝑇set Abbreviations DDV DDV+ STRAD UFAD MV PV VDG PMV PPD
Density of air (Kg⁄m3 ) Static pressure of air (Pa) Gravitational acceleration (m⁄s 2 ) Stress tensor (Pa) Sensible enthalpy (J) Specific heat capacity at constant pressure (J⁄K) Mean age of air (s) Ventilation load (W) Space cooling load (W) Cooling coil load (W) Exhaust mass flow rate (Kg⁄s) Return mass flow rate (Kg⁄s) The return temperature (℃) The exhaust temperature (℃) The supply flow temperature (℃) Set point temperature (℃)
Desk Displacement Ventilation Improved Desk Displacement Ventilation Stratified Air Distribution Under-floor air distribution Mixing ventilation Personalized ventialtion Vertical desk grills predicted mean vote predicted percentage of dissatisfied
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[2] W. Sun, K. W. Tham, W. Zhou, N. Gong, Thermal performance of a personalized ventilation air terminal device at two different turbulence intensities, Building and Environment, Vol. 42, No. 12, pp. 3974-3983, 2007. [3] A. K. Melikov, R. Cermak, M. Majer, Personalized ventilation: evaluation of different air terminal devices, Energy and Buildings, Vol. 34, No. 8, pp. 829-836, 2002. [4] N. P. Gao, H. Zhang, J. L. Niu, Investigating Indoor Air Quality and Thermal Comfort Using a Numerical Thermal Manikin, Indoor and Built Environment, Vol. 16, No. 1, pp. 7-17, 2007. [5] Q. He, J. Niu, N. Gao, T. Zhu, J. Wu, CFD study of exhaled droplet transmission between occupants under different ventilation strategies in a typical office room, Building and Environment, Vol. 46, No. 2, pp. 397-408, 2011. [6] M. Loomans, the Measurement and Simulation of Indoor Air Flow, PhD Thesis, Eindhoven University, Netherlands, 1998. [7] P. V. Nielsen, Control of airborne infectious diseases in ventilated spaces, Journal of The Royal Society Interface, Vol. 6, pp. S747-S755, 2009. [8] Y. Cheng, J. Niu, X. Liu, N. Gao, Experimental and numerical investigations on stratified air distribution systems with special configuration: Thermal comfort and energy saving, Energy and Buildings, Vol. 64, pp. 154-161, 2013. [9] A. Q. Ahmed, S. Gao, A. K. Kareem, A numerical study on the effects of exhaust locations on energy consumption and thermal environment in an office room served by displacement ventilation, Energy Conversion and Management, Vol. 117, pp. 74-85, 2016. [10] A. Q. Ahmed, S. Gao, A. K. Kareem, Energy saving and indoor thermal comfort evaluation using a novel local exhaust ventilation system for office rooms, Applied Thermal Engineering, Vol. 110, pp. 821834, 2017. [11] Q. Chen, W. Xu, A zero-equation turbulence model for indoor airflow simulation, Energy and Buildings, 28 (2) (1998) 137-144. [12] N. Kobayashi, Q. Chen, Floor-Supply Displacement Ventilation in a Small Office, Indoor and Built Environment, Vol. 12, No. 4, pp. 281-291, 2017/11/04, 2003. [13] R. a. A.-C. E. American Society of Heating, 2009 ASHRAE Handbook: Fundamentals: American Society of Heating, Refrigeration and AirConditioning Engineers, 2009. [14] K. W. Tham, Effects of temperature and outdoor air supply rate on the performance of call center operators in the tropics, Indoor Air, Vol. 14, pp. 119-125, 2004. [15] N. Gong, K.W. Tham, A. Melikov, D.P. Wyong, S.C. Sekhar, K. W. Cheong, The acceptable air velocity range for local air movement in the tropics, HVAC&R Research, Vol. 12, No. 4, pp. 1065-1076, 2006. [16] S. International Organization for, ISO 7730: Moderate Thermal Environments - Determination of
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