Keywords

10.1 Introduction

A ventilation system incorporated in a building is responsible for human comfort. An effective ventilation system improves the state of wellbeing, on the other hand, an ineffective ventilation system can be detrimental to human health. The location of the inlet, outlet, amount of air supplied, air-velocity, temperature, humidity, number of occupants in the room, furniture, etc., influences the thermal comfort. The most common type of ventilation systems used in indoor spaces is “mixing ventilation system” and “displacement ventilation system.” Both of these ventilation systems have their own merits and demerits. The mixing ventilation system supplies air at high velocity into the room from the inlet situated close to the ceiling. The fresh air mixes with the air present in the room and exits from the outlet located near the floor [1]. The displacement ventilation system supplies fresh air from the inlet located near the floor. This fresh air displaces the existing room air, encounters heat sources, and rises upward in the room [2, 3]. Numerous studies (experimental and numerical) reported the comparison of the mixing and displacement ventilation system. The studies investigated the thermal comfort, indoor air quality in offices, classroom, retail shops, industrial workshop, space capsules, tutorial rooms [4,5,6,7], effects of the cooling ceiling in a ventilated room [8], air quality in single-person patient ward [9], air-quality and air conditioning performance in a partitioned room [10], and removal effectiveness during vacuuming session [11]. To the author’s best knowledge, previous studies demonstrated the two ventilation systems (mixing and displacement) airflow characteristics with fixed boundary conditions in larger room sizes. The present study numerically investigates the airflow characteristics in a scaled-office room equipped with the two most commonly used air-diffusion systems (mixing and displacement) functioning at different ACH (air change hour). A validated CFD code will be employed to analyze the airflow pattern in the room, evaluate air velocity and temperature at different levels of the room.

10.2 Geometry Description

The model of the office room used for the investigation is illustrated in Fig. 10.1. A four seat-table is placed in the center region of the room. According to Topp et al. [12], a box-shaped mannequin representing an occupant is sufficient for studying the global air flow of the room. Therefore, four box-shaped mannequins are placed near the table. Seats are not created in the model, the box-shaped mannequin represented an occupant seated at their respective desk. To replicate an office scenario, a personal computer (PC) is placed on the desk for the occupant to perform the office job. Three lamps are mounted on the ceiling to illuminate the room.

Fig. 10.1
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Room model with mixing and displacement ventilation system

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Two CAD models of the office room are created using Creo Parametric software. The first model is incorporated with the mixing ventilation system, and the second model is incorporated with the displacement ventilation system. Figure 10.1a illustrates the dimensions used for modeling the office room. The length, breadth, and height of the room are based on Chen et al.’s experimental study [13]. In the experimental study, the authors used an empty room for their investigation. For the present research, the room is created with “furniture” and “occupants” to depict an office environment. Figure 10.1a represents the office room with a “mixing ventilation system,” and Fig. 10.1b represents the office room with a “displacement ventilation system”. The difference between the two models is the placement of the inlet and outlet, and the rest of the dimensions is identical.

10.3 Numerical Scheme

The CFD solver ANSYS Fluent is employed to investigate the flow characteristics. This solver works on the principle of the “Finite Volume Method,” a discretization technique well-suited for numerical experiments in several engineering fields [14]. The presence of low-speed incompressible flow in the computational domain required the utilization of a pressure-based coupled algorithm [15] to solve the governing equations. The coupled algorithm solves the momentum and pressure-based continuity equations simultaneously. The airflow in the indoor environment is driven by two major factors, one is the air-diffusion system, and the second is the buoyancy. In buoyancy-driven flow, the heat sources in the room vary the density of air (lighter air moving upward and heavier air moving down); therefore, the flow is induced due to the gravity force acting on these density variations. To model the buoyancy characteristics, a gravity force of 9.81 m/s is included in the numerical scheme. Incompressible ideal gas law is adapted to compute the density of air in the domain using the following equation:

$$\rho = \frac{{P_{{{\text{op}}}} }}{{\frac{R}{{M_{w} }}T}}$$
(10.1)

where R is the universal gas constant, Mw is the molecular weight of the gas, Pop is the operating pressure and T is the temperature. The pressure at the middle height of the domain is considered to be the operating pressure [16]. The energy and species transport equations are used to quantify the temperature and humidity in the room. For spatial discretization, the second-order upwind scheme was adapted for the momentum, turbulence, and energy equations. The pressure values were interpolated using the Pressure Staggering Option scheme (PRESTO!). The convergence was satisfied when the residuals reached below 10–4 and the average velocity in the breathing zone was constant with the iterations.

The realizable k-ϵ model proposed by Shih et al. [17] is used for turbulence modeling [18]. The transport equations for k and ϵ in the steady-state form are:

$$\frac{\partial }{{\partial x_{j} }}\left( {\rho ku_{j} } \right) = \frac{\partial }{{\partial x_{j} }} \left[ {\left( {\mu + \frac{{\mu_{t} }}{{\sigma_{k} }}} \right)\frac{\partial k}{{\partial x_{j} }}} \right] + G_{k} + G_{b} - \rho \epsilon - Y_{M} + S_{k}$$
(10.2)

And

$$\begin{aligned} \frac{\partial }{{\partial x_{j} }}\left( {\partial \epsilon u_{j} } \right) = & \frac{\partial }{{\partial x_{j} }}\left[ { \left( { \mu + \frac{{\mu_{t} }}{{\sigma_{\epsilon } }}} \right)\frac{\partial \epsilon }{{\partial x_{j} }}} \right] + \rho C_{1} S\epsilon - \rho C_{2} \frac{{\epsilon^{2} }}{{k + \sqrt { v \epsilon } }} \\ & \quad + C_{1\epsilon } \frac{\epsilon }{k} C_{3\epsilon } G_{b} + S_{\epsilon } \\ \end{aligned}$$
(10.3)

where

$$C_{1} = \max \left[ {0.43,\frac{\eta }{\eta + 5}} \right] , \;\eta = S\frac{k}{\epsilon } ,\;S = \sqrt {2S_{ij} S_{ij} }$$

In the above equations, \(G_{k}\) represents the generation of turbulent kinetic energy due to mean velocity gradients, \(G_{b}\) represents the generation of turbulent kinetic energy due to buoyancy, \(Y_{m}\) represents fluctuating dilatation in compressible turbulence to the overall dissipation rate. C2 and \(C_{1\epsilon }\) are constants. \(\sigma_{k}\) and \(\sigma_{\epsilon }\) are the Prandtl numbers for k and ϵ, respectively. Sk and Sϵ are user-defined source terms.

10.4 CFD Validation

The experimental study performed by Chen et al. [13] was considered to demonstrate the accuracy of the numerical scheme. Air at a velocity of 0.225 m/s (corresponding to 10 ACH) was supplied in the room. The supplied air exited from the outlet located on the wall near the floor. During this journey, the x-velocity of air was measured at three locations along with the height of the room. Detailed dimensions of the room and the location of the poles used to measure the velocity can be found in [13]. Figure 10.2 illustrates that CFD obtained results are consistent with the reported experimental results. Therefore, the numerical scheme has demonstrated accuracy and is valid to be used for the consequent simulations.

Fig. 10.2
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Comparison of present-CFD and experimental x-velocity

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10.5 Boundary Conditions and Grid Independence Study

The boundary conditions are presented in Table 10.1. The supply velocity (m/s) varied with the amount of air supplied in the room. The supplied temperature is constant for both the ventilation systems.

Table 10.1 Boundary condition
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A three-dimensional unstructured grid discretized the fluid domain into tetrahedral elements. The advanced size functions; Proximity and Curvature, were used to capture refined grid near the wall boundaries, curved regions, and small features of the geometry. The tetrahedral cells were converted into polyhedral cells in the ANSYS Fluent. The polyhedral cells are less sensitive with improved grid quality and offer numerical stability with a reduction in the computational time required for convergence [19]. The generated grid corresponds to a Y+ value of less than 5 at all the wall boundaries of the domain. Therefore, enhanced wall treatment is utilized to resolve the boundary layer.

Three grid sizes of 0.7, 0.8, and 1 million cells are tested to evaluate the variation of velocity and temperature in the room with a mixing ventilation system supplying air at 6ACH. The velocity and temperature are measured at two lines along with the height of the room. Figure 10.1b shows the position of Line-1 and Line-2. Figure 10.3 illustrates the effect of grid-refinement on the velocity and temperature distribution, for the three grid sizes. The flow variables differ minutely with grid refinement. Due to this insignificant difference in the flow parameters, Grid-2 is considered for the subsequent simulations.

Fig. 10.3
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Effect of grid-refinement on the temperature and velocity

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10.6 Results and Discussion

Figures in this section depict the global airflow movement in the office environment with the help of CFD obtained velocity vectors on the cut-section planes illustrated in Fig. 10.1b. The black-colored arrows on the vector graphic illustrate the direction of the air velocity vectors. The airflow movement in all three cases (ACH 6, 9, 12) is identical, the major difference is in the distance of the throw of supplied air. The supply air jet in ACH-12 (due to high velocity) travels further in comparison with ACH-6 and 9. Therefore, the velocity vectors of ACH-12 are used to illustrate the airflow movement in the office room.

Figure 10.4 illustrates the airflow pattern on the cut-section plane Z = 0 m. The mixing ventilation system (Fig. 10.4a) supplies air from the inlet near the ceiling. Due to buoyancy, the jet flow (cool-air) moves in a downward direction to impact the table. In this process, occupant-1 and occupant-3 face a high risk of the draft. The thermal plume of occupant-1 and 3 moves up to reattach with the oncoming supply jet. The thermal plume of occupant-2 and 4 moves to the ceiling, impinges the wall to travel downwards, and exits from the outlet. In the displacement ventilation system (Fig. 10.4b), the supplied air travel along the floor surface, to impinge occupant 1 and 3, followed by occupant 2 and 4. The temperature of the air gets reduced due to its interaction with the occupant body (ankle). Therefore, the air after crossing occupant-2 and 4 rises upward with the occupant’s thermal plumes, reaches the ceiling, and exits from the outlet. The thermal plume of occupant-1 and 3 impinges the ceiling and directs to the right-side walls, and latter moves down to reattach the inlet air.

Fig. 10.4
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Velocity vector on cut-section plane Z = 0 m

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Plane X = −0.1 m (Fig. 10.5) shows that the thermal plumes of the occupant impinge the ceiling and travel downward along the surface of the wall behind the occupants. Therefore, the air behind the occupants forms a circulation zone. The air in the circulation region becomes older and may have a high concentration of contaminants. Both the ventilation systems (mixing—Fig. 10.5a and displacement—Fig. 10.5b), showcased an identical airflow pattern; however, in the displacement ventilation system, there exists a circulation zone below the table. This is because the supplied air rises upwards with the occupant thermal plume and impacts the surface of the table to circulate.

Fig. 10.5
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Velocity vector on cut-section plane X = −0.1 m

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The airflow pattern in the occupant breathing zone is illustrated in Fig. 10.6. In the mixing ventilation system (Fig. 10.6a), the desk of occupant 1 and 3 have fresh air supplied from the inlet. A certain quantity of fresh air impacts the table and divides it into two identical paths. The first path is behind occupant 1 and 2. The second path is behind occupant 3 and 4. The air surpasses occupant-1 and 3 to enter the desk region of occupant 2 and 4, respectively. The thermal plumes from the floor raise upward and reach the desk of occupant-2 and 4. Therefore, the air near occupant-2 and 4 is mixed with the incoming fresh air (from the right) and the thermal plumes (from the left). Due to this, the air in this region loses its freshness. This indicates that the occupants seated farther from the inlet location are prone to unfresh and contaminated air. In the displacement ventilation system (Fig. 10.6b), the air is supplied at the occupant ankle level (Y = 0.01 m). Therefore, the cut-section (Y = 0.16 m) represents the air that traveled upward either due to its interaction with the obstacles (table) or due to buoyancy (with the thermal plume). The vector plot reveals that the air impacts the table and redirects to enter the zone of occupant 1 and 2. Because of its lesser travel time, this air (near occupant 1 and 2) is free from contaminants and may be considered as fresh air. Plane Z = 0 m (Fig. 10.4b) revealed that the supplied air travels along the floor surface, crosses the occupant 2 and 4, and rises upward to enter into the occupant-2 and 4 desks regions. In addition to this, the plane Y = 0.16 (Fig. 10.6b) reveals that the rising air flows in the space behind the occupant 2 and 4. This flow pattern indicates that the air in the vicinity of occupant-2 and 4 is unfresh and may possess a high-contaminant concentration.

Fig. 10.6
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Velocity vector on the cut-section plane Y = 0.16 m

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Figure 10.7 illustrates the average velocity at different levels of the occupant body (Ankle-0.01 m, Knee-0.05 m, Stomach-0.1 m, Breathing-0.16 m, and Occupant standing position-0.21 m). For ACH-6, the mixing ventilation system showcases a high air velocity from the ankle to the occupant standing position. For ACH-9 and 12, the mixing ventilation system showcases high-air velocity from the knee to the occupant standing position. The displacement ventilation system showcases, a high-air velocity at the ankle level (for ACH-9 and 12), and at the rest of the levels, the displacement ventilation system possesses lower air velocity in comparison with the mixing ventilation system. Figure 10.8 illustrates the average temperature on the different occupant body levels. At ACH-6, 9, and 12, the displacement ventilation system demonstrates low temperature in all the occupant levels. However, at the standing position, the temperature of the mixing ventilation (at ACH 9 and 12) is slightly lower than that of the displacement ventilation system. Furthermore, the occupants in the displacement ventilation system will show dissatisfaction in the ankle and knee levels.

Fig. 10.7
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Average velocity—occupant body levels

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Fig. 10.8
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Average temperature—occupant body levels

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10.7 Limitations and Future Work

The present work demonstrated the airflow pattern in a scaled room model used by Chen et al. [13] for their experimental investigation. The Future work will focus on full-sized room geometry (with a similar office setting used in this research) to evaluate and compare the airflow pattern with that of a scaled room. Although the computational cost to evaluate the airflow pattern in the realistic room will be extremely high, an identical flow pattern will illustrate the possibility to allow the researchers to use scaled rooms for their investigations (provided the objective of their study is to identify the airflow movement).

10.8 Conclusion

The vector plots revealed that the airflow pattern in the office room is a function of the ventilation system being employed. The path of the supplied air in the office room varied according to its interaction with the obstacles (table), and occupants. As mentioned in the literature, the occupant thermal plumes (buoyancy effects) contributed to the airflow movement in the room. For a ventilation system, the change in supply rate has showcased a variation in the throw of air near the inlet, whereas the air further away from the inlet possessed an identical flow pattern. The study revealed that the occupants seated closer to the inlet have fresh air surrounding them, whereas the occupants seated further are surrounded with unfresh air. The average velocity and temperature in the occupant activity zone determined the draft and thermal sensation. The mixing ventilation system showcased a higher average air velocity, therefore, a high-draft sensation, and the displacement ventilation system showcased a lower air temperature in comparison with the mixing ventilation system.