TY - JOUR
AU1 - Maher, Dhahri
AU2 - Hana, Aouinet
AU3 - Arjmand, Jamal Tabe
AU4 - Issakhov, Alibek
AU5 - Sammouda, Habib
AU6 - Sheremet, Mikhail
AU7 - Sharma, Shubham
AB - Abstract Ventilation is a way of improving the air quality of rooms by circulation. The position of the inlet and outlet greatly influences the thermal comfort. This attempt proposes to analyse the effect of the position of window openings for a room building with natural ventilation and the air flow and temperature distribution numerically using a commercial computational fluid dynamics (CFD) code. This proposed study consists of (i) approving the numerical model against experimental data gathered in an environment similar to the one used in simulations and (ii) applying the CFD model to explore the results of four varying configurations of ventilator on the natural ventilation system and thermal comfort. For the varying arrangements, the wind speed is 0.2 m⋅s−1 perpendicular to the openings for a wind, (iii) evaluating the comfort level utilizing the Air Diffusion Performance Index (ADPI) on the basis of ASHRAE 55-210 criteria. The obtained results show that the positions of outlet and inlet openings highly affect the performance in the thermal comfort while they have a trivial effect on the occupied zone mean velocity. The computational results showed that the two cases (a) and (b) present results very close to each other with a slight difference at the center of the chamber. Most of the calculated values (effective draft temperature, EDT) are between (−1.7 and 1.1). Then ADPI is over 70% for case (a) and over 75% for case (b), so all points they are located in the comfort zone. The results affirmed also that configuration with inlet openings set at 1.022 m above ground and an outlet opening set at 0.52 m brings about the most applicable solution ventilation efficiency and give the best EDT that fulfills the criteria of ASHRAE 55-210 with an ADPI of ~90%. 1. INTRODUCTION The information on the velocity and temperature of air, relative humidity, turbulent intensity and concentration of contaminant are required to have healthy and desirable indoor environment, which can be numerically resolute [1–7]. According to the studies, computational fluid dynamic (CFD) is a precious method to examine the fundamental studies that analyse the distribution of airflow and temperature in a building [5–9]. Many factors affect the precision of CFD modeling. Some of them are the discretization method, boundary conditions and turbulence model [10–13]. For example, Zhang et al. [14] had a systematic evaluation of height turbulence models used in the simulation of indoor airflow. The authors studied the indoor airflow under diverse approaches, specifically an indoor zero-equation model (0-eq) [15], a low Reynolds number (LRN) k-ε model [16, 17], an Re-Normalisation Group (RNG) k-ε model [18] and finally a large-eddy-simulation model [19]. There are many searches in the literature that achieved the numerical study of thermal comfort in residential complexes and also evaluated the effect of natural and stratified ventilations on the thermal comfort status [20–25]. With the development of numerical approaches, numerical method has been used by CFD, modeling the indoor airflow and other related applications. Widespread research has been conducted in current years, to improve general fluid flow and heat transfer programs in order to solve the flow of air in a room. The natural ventilation flow in a generic isolated building was the case of Peren et al. [26]. The study concerned many vertical installation of the outlet opening resulting in asymmetric opening positions and five dissimilar roof inclination angles using the CFD method. They found that the inclination angle of roofs has a dramatic influence on the aeration current; the volumetric flow rate increases to higher than 22%. By increasing the inclination angle, the maximum local indoor air velocity gets higher to a significant amount. However, the variety engaged zone mean velocity illustrates to be around 7%. The effect of vertical position of the outlet opening on the rate of volume flow is slightly low (below 4%), and the occupied zone mean velocity is under 5%. Montazeri and Montazeri [27] examined the outlet opening effect on the ventilation act in a single-zone secluded building having a wind catcher. The estimation is according to three ventilation functional indices. The results obtained that induced airflow will not be increased in a case that outlet openings are near the wind catcher. Nevertheless, it significantly reduced the indoor air quality. Khoshab and Dehghan [28] numerically studied mixed airflow convection beneath a ventilated dome-shaped roof via LRN k-ω turbulence model. The results demonstrate that most of the airflow is intent under the hot ground as the Grashof number is increased in the natural convection range. Zhai et al. [29] used indoor airflow modeling to study the utility of eight turbulence models. The measured flows resulted from the mixture of many parameters. As an example, their required convection was along with separation and jet flow. When variances between the numerical results and measured data were singled out, it was that simple to observe the parameter that led to the fall of the turbulence model. As a result, the standard cases should be used to facilitate the analysis of the features of the flow. Other parameters added to those complex flow properties should be examined as well. An additional, numerical analysis by Tang et al. [30] exposed a model that shows a thermal performance assessment of non-ventilated or without any opening vaulted roof buildings. It is an unsteady two-dimensional conduction heat transfer with a solar absorption radiation system considering the motion of the sun. Dhahri et al. [31] employed a commercial fluid dynamics calculation software package (ANSYS CFX 15). The authors analysed the air flow, the thermal comfort and the temperature distribution in the chamber, and all the CFD simulations were carried out in a vacant chamber. The numerical results are validated with measurement points from the literature. In this paper, the authors evaluated the performance of the comfort using the Air Diffusion Performance Index (ADPI). The results showed that the simulations could accurately predict the temperature and airflow distribution in the chamber space. They also proved that the condition of a speed of 0.15 ms-1 gives the best effective draft temperature (EDT). Asfour and Gadi [32] studied numerically the influence of vaulted roofs using wind induced naturally and demonstrated that the existence of some openings at the bases of the vaulted roofs can be of complete effectiveness in case of ventilation by suction. Furthermore, the performance of natural ventilation between a domed and vaulted roof was discussed and compared. Another work of Lin [33] determined the range of ‘satisfactory’ and ‘good’ for the effective draft temperature for stratum ventilation (EDTS). Based on their study, the satisfactory ETDS ranges from −1.2 to 1.2 and the good ETDS varies between −0.6 and 0.6. Hawendi and Gao [34] essentially inspected the influence of effective parameters on patterns of flow and cross-ventilation inside a secluded house by using a CFD model. More recently, Navid et al. [35] analysed numerically the thermal comfort and the indoor flow patterns in a room equipped with a two-sided wind catcher based on five different room outlets and four different outlet areas. The authors used a Reynolds-averaged Navier–Stokes (RANS) CFD simulation with three turbulence model. The authors accomplished that the room outlet mass flow rate increases up to 26% in the case of decreasing the room outlet, and they concluded also that for a higher room outlet opening, the ratio of the area of the room outlet increases and the wall increases the mass flow. Nikhil et al. [36] proposed a new design for double-loaded affordable apartments with the goal of improving the indoor ventilation performance of the buildings. The new plan is about three keys building components: a closed-vertical void, an open pilotis and a wind fin. A wind tunnel experiment, accompanied by CFD simulations, was employed to analyse the effects of the new design on the performance of indoor ventilation compared to an ordinary building with an open vertical vacuum. The results illustrate that the closed vertical vacuum of the proposed design distributed wind pressures better than those of the ordinary apartment vacuum and better interior ventilation. In another recent work, Yan et al. [37] integrated a wind tower with a natural ventilated house on one side. The authors compared this ventilation combination with a common underground application and investigated the effect of this combination with different window configurations. The results illustrate that the local wind environment must be fine reproduced to accurately predict indoor airflow. In the same order of velocity, the ventilation efficiency of the new combination is 15% to 40% lower than the underground application, which is normally due to the effect of the separation flow above the roof. The indoor temperature is higher also than the outdoors, the exhaust wind tower will work better due to the chimney effect. Chen et al. [38] used both the experimental and numerical simulation approaches and studied the influence aspect ratios of the wind inlets and their locations on indoor air quality. The results demonstrate that the ration between length and width equal 4 and the location of inlet in the middle of the sidewall can advance the efficiency of natural ventilation. Based on the literature review, numerical studies excavating the effect of the opening location on natural ventilation and thermal comfort in building have not been until that time examined and considered in an inclusive method. The major aim of this study is to offer an extensively validated study about indoor airflows in a three-dimensional vacant room with a natural convection. The experimental data will be evaluated to the CFD predictions using the variables of velocity and temperature distributions at the same flow and boundary conditions. This paper covers six sections. Mathematical model is presented in section 2. The computational settings and the parameters applied in the CFD simulations are described in section 3, the CFD results are presented in section 4 and the validation studies are briefly outlined. Finally, discussion and conclusion are provided respectively in section 5 and section 6. 2. MATHEMATICAL MODEL The following governing equations were used for numerical simulation. Continuity equations: $$\begin{align} \frac{\partial \rho }{\partial t}+\frac{\partial }{\partial{x}_i}\left(\rho{u}_j\right)=0 \end{align}$$(1) Momentum equation: $$\begin{align} \frac{\partial }{\partial t}\left(\rho{u}_i\right)+\frac{\partial }{\partial{x}_j}\left(\rho{u}_i{u}_j\right)=\frac{\partial }{\partial{x}_j}\left[-p{\delta}_{ij}+\mu \left(\frac{\partial{u}_i}{\partial{x}_j}+\frac{\partial{u}_j}{\partial{x}_i}\right)\right]+\rho{g}_i \end{align}$$(2) Energy equation: $$\begin{align} \frac{\partial }{\partial t}\left(\rho{c}_pT\right)\frac{\partial }{\partial{x}_j}\left(\rho{u}_j{c}_pT\right)-\frac{\partial }{\partial{x}_j}\left(\lambda \frac{\partial T}{\partial{x}_j}\right)={S}_T \end{align}$$(3) Here T and cp respectively stand for air temperature and specific heat, λ represents the thermal conductivity, ρ denotes the density, g is the gravity acceleration, μ denotes the dynamic viscosity and u represents the velocity. The k-ε model has historically been very popular for industrial applications because of its good convergence rate and relatively low memory requirements. The turbulence models listed below are used in this paper; the kinetic energy of turbulence, k, and its dissipation rate, ε, can be calculated from Eq. (4) and Eq. (5) as follows: $$\begin{align} & \frac{\partial }{\partial t}\left(\rho k\right)+\frac{\partial }{\partial{x}_i}\left(\rho k{u}_i\right)\nonumber\\&\quad=\frac{\partial }{\partial{x}_j}\left[\left(\mu +\frac{\mu_t}{\sigma_k}\right)\frac{\partial k}{\partial{x}_j}\right]+{G}_k+{G}_b-\rho \varepsilon -{Y}_M+{S}_k \end{align}$$(4) and $$\begin{align}& \frac{\partial }{\partial t}\left(\rho \varepsilon \right)+\frac{\partial }{\partial{x}_i}\left(\rho \varepsilon{u}_i\right)=\frac{\partial }{\partial{x}_j}\left[\left(\mu +\frac{\mu_t}{\sigma_{\varepsilon }}\right)\frac{\partial \varepsilon }{\partial{x}_j}\right]\nonumber\\&\quad+{C}_{1\varepsilon}\frac{\varepsilon }{k}\left({G}_k+{C}_{3\varepsilon }{G}_b\right)-{C}_{2\varepsilon}\rho \frac{\varepsilon^2}{k}+{S}_{\varepsilon } \end{align}$$(5) Here Gk is the generated kinetic energy as a result of mean velocity gradient, Gb represents the kinetic energy corresponding to buoyancy, YM is defined as the ratio of the fluctuating dilatation in compressible turbulence to the total dissipation rate, C1ε, C2ε and C3ε are constants, σk is the turbulent Prandtl number for k and σɛ is the turbulent Prandtl number for ε. The combination of k and ε helps to compute νt, the turbulent viscosity, as follows: $$\begin{align} {v}_t={C}_{\mu}\frac{k^2}{\varepsilon } \end{align}$$(6) Here Cμ is a constant value in Eq. (6). The constants of the including C1ε, C2ε, Cμ, σk and σε are as follows: $$ {C}_{1\varepsilon }=1.44,{C}_{2\varepsilon }=1.92,{C}_{\upmu}=0.09,{\sigma}_k=1.0,{\sigma}_{\varepsilon }=\mathrm{1.3.} $$ The default values were obtained through experimentations employing water and air for fundamental turbulent shear flows, which consist of homogeneous shear flows and decaying isotropic grid turbulence. Their fairly well work in the cases of a wide range of wall-bounded and free shear flow is found through these experimentations. The building of this paper has dimensions of height × length×width of 1.04 × 1.04 × 0.74 m3, as shown in Figure 1. Air enters the room from an opening at the top of the corner that is designed at the height of 1.8 cm of the room. There is an opening space at the height of 2.4 cm through which air exits. The results obtained from inlet conditions were 0.57 m/s for the velocity. The temperatures of wall and floor were 15°C and 35.5°C, respectively. On the basis of air inlet velocity, Re = 706. The considered Rayleigh number is equal to 2.62 × 109. The Rayleigh number is expressed as $$\begin{align} Ra=\frac{\beta \left({T}_1-{T}_2\right)g{H}^3}{v\alpha} \end{align}$$(7) The Reynolds number is expressed as $$\begin{align} \operatorname{Re}=\frac{U_{in}{h}_{in}}{v} \end{align}$$(8) where hin is the inlet height, Uin is the inlet air velocity and ν is the kinematic viscosity. Figure 1 Open in new tabDownload slide The computational domain. Figure 1 Open in new tabDownload slide The computational domain. Numerical values of the wall y+ had the span of 11. For the whole cases the second-order discretization scheme was employed. The solution was observed converged as the normalized residuals of 10−5 for the energy and the other parameters. The gravitational acceleration direction and value are considered to express the buoyancy effect. Receiving a proper solution with a good mesh is highly important. There are some general guidelines to create a good mesh. The necessary factor about a good mesh is that they should be fine enough, having a high quality and a good distribution. They should not have more cells than the computer resources. The obtainable meshing tool in ANSYS is in use to generate the computational mesh. The domain made use of a structured mesh residing on a rectangular grid. To evaluate the impacts of grid size on the results, a grid independence test was done for the square cavity. Five considered sets of mesh are 249 648, 323 948, 353 668, 502 268 and 550 000 nodes at V = 0.57 m/s. An example of the mesh can be found in Figure 2. The comparison of the mesh configurations considering the temperature value is shown in Figure 3. It can be accomplished that the solution is independent on grid size and any increase in size of mesh more than the one cited in no. 4 does not have a remarkable impact on the results. As a result, to achieve a reliable accuracy, the mesh no. 4 (502 268 cells) will be employed in all calculations. Figure 2 Open in new tabDownload slide The generated grid for computational domain. Figure 2 Open in new tabDownload slide The generated grid for computational domain. Figure 3 Open in new tabDownload slide Independency test for model grid at Z = 0.502 m. Figure 3 Open in new tabDownload slide Independency test for model grid at Z = 0.502 m. Industrial CFX-15.0 software was used for the numerical calculations. Geometric modeling and meshing were applied by means of the meshing software workbench. Figure 2 presents a structured mesh at the entire transversal chamber section. The total of the absolute residual values required to be under 10−6 was applied for a good convergence. The following vent configuration as shown in Figure 1 is applied to observe the impact of vent scheme on windward ventilation of a room building. Consequently, four cases are considered, which differ in location of their outlet and inlet openings. Cross-section area of the window outlet is 0.018 × 0.018 (Ainlet = 3.24 × 104 m2). The window outlet opening with a surface area of 0.024 × 0.024 m2 is different from the wind inlet opening (Aoutlet = 5.76 × 104 m2). Configuration (a) The building is prepared with two sides opening an inlet opening located at 1.022 m above ground with one outlet opening located at the ground. This configuration produces an entire opening area of 36 m2 (Figure 4). Configuration (b) For this configuration the base of the outlet window is exactly at 1.022 m above ground with the window height of 0.024 m and the inlet window opening for the airflow situated at 1.022 m above ground (Figure 4). Configuration (c) In this case, the building is equipped with a double side opening: an inlet opening set at 1.022 m above ground and an outlet opening set at 0.52 m (Figure 4). Configuration (d): combined roof and side openings (roll-up type) The inlet and outlet openings are placed at the 0.52 m above ground. This type generates an inlet opening area of 0.018 × 0.018 m2 and outlet area of 0.024 × 0.024 m2 (Figure 4). 3. RESULTS AND DISCUSSION 3.1. Numerical model validation Among the most essential test cases to evaluate different turbulence models for buoyancy-driven flows is the mixed convection in a room. The researchers considered the experimental data of mixed convection in an enclosure. The different geometry cases are shown in Figure 4 and the temperature boundary conditions are listed in Table 1. The validation of the numerical results was based on the experimental results of Blay et al. [39]. Figure 4 Open in new tabDownload slide Different geometries of the four types selected configurations: (a) case 1, (b) case 2, (c) case 3 and (d) case 4. Figure 4 Open in new tabDownload slide Different geometries of the four types selected configurations: (a) case 1, (b) case 2, (c) case 3 and (d) case 4. Table 1 Inlet parameters used for validation. . Validation case . Wall temperature 15°C Ground temperature 35.5°C Inlet air velocity 0.57 m/s . Validation case . Wall temperature 15°C Ground temperature 35.5°C Inlet air velocity 0.57 m/s Open in new tab Table 1 Inlet parameters used for validation. . Validation case . Wall temperature 15°C Ground temperature 35.5°C Inlet air velocity 0.57 m/s . Validation case . Wall temperature 15°C Ground temperature 35.5°C Inlet air velocity 0.57 m/s Open in new tab Figures 5–7 compare the average air velocity and temperature with the experimental data at center sections of Y = 0.502 m and Z = 0.502 m. Figure 5 shows that the profiles of the velocity agree adequately with the experimental data. The velocity field is asymmetric, which is overall small in the center of the cavity. The percentage error is ~17%. The differences between the numerical and the measured values can be explicated by the reducing hypothesis of the turbulence model and the uncertainty associated to the experiments. Figure 5 Open in new tabDownload slide Comparison of estimated and measured average velocity at Z = 0.502 m. Figure 5 Open in new tabDownload slide Comparison of estimated and measured average velocity at Z = 0.502 m. Figure 6 Open in new tabDownload slide Estimated vs. measured average temperature on the central parts at Z = 0.502 m. Figure 6 Open in new tabDownload slide Estimated vs. measured average temperature on the central parts at Z = 0.502 m. Figure 7 Open in new tabDownload slide Comparison of estimated and measured average velocity on the central parts(Y = 0.502 m). Figure 7 Open in new tabDownload slide Comparison of estimated and measured average velocity on the central parts(Y = 0.502 m). Figure 6 shows that the temperature is ~0.75 K lower than the one measured in the center, though the profile of the temperature is similar to the measured one. The models of estimation may exceed the actual amount of the heat transfer from the floor or underestimate the heat transfer to the other walls and the percentage error is <1%. Figure 7 represents the simulated and experimental air velocity distance profiles. This case revealed a logical harmony. The difference between simulated and measured velocity deviated by only 8%. Figure 8a and b shows the mean air velocity distribution obtained from the simulations. The numerical results of air flow patterns are almost in good agreement with the experimental data. Figure 8 Open in new tabDownload slide (a) Average velocity vectors computed, (b) average velocity vectors obtained from the experiment [ 35] at x = 0.35 m. Figure 8 Open in new tabDownload slide (a) Average velocity vectors computed, (b) average velocity vectors obtained from the experiment [ 35] at x = 0.35 m. Figure 9 presents the obtained results from the CFD model and the experimental temperature distribution distance profile. It can be seen that the CFD values were lower than the experimentally measured ones. This result can be interpreted as follows: Figure 9 Open in new tabDownload slide Estimated vs. measured average temperature on the central parts (Y = 0.502 m). Figure 9 Open in new tabDownload slide Estimated vs. measured average temperature on the central parts (Y = 0.502 m). (a) The wind velocity is experimentally measured to show the average value of the measurement period. For that reason, it ignores the turbulent part, while the predicted CFD model’s value comprises the turbulent part though the applied k-ε model is a rough estimate. (b) Though fans were made use of in the experiment, the homogenization of the tracer gases was not acceptable, despite the CFD model in which the homogenization is assumed. 3.2. Impact of different types of configurations in airflow patterns and temperature distribution Different configurations are proposed to observe the effect of temperature distribution and air flow. Subsequently, the ADPI and EDT are used to classify and determine the thermal comfort at plane P1 (YZ) at x = 0.35 cm. Configurations (A) and (B) The first configuration resembles the building room, which is used for validation of the model. The air enters at constant average velocity of 0.2 m/s and acknowledged temperature (Table 2). The outlet opening is considered to have a constant pressure (P = Patm). Flow and temperature fields determine the results. Table 2 Inlet parameters for different cases. . Case (a) . Case (b) . Case (c) . Case (d) . Wall temperature (°C) 15 15 15 15 Ground temperature (°C) 35.5 35.5 35.5 35.5 Inlet air velocity (m/s) 0.2 0.2 0.2 0.2 . Case (a) . Case (b) . Case (c) . Case (d) . Wall temperature (°C) 15 15 15 15 Ground temperature (°C) 35.5 35.5 35.5 35.5 Inlet air velocity (m/s) 0.2 0.2 0.2 0.2 Open in new tab Table 2 Inlet parameters for different cases. . Case (a) . Case (b) . Case (c) . Case (d) . Wall temperature (°C) 15 15 15 15 Ground temperature (°C) 35.5 35.5 35.5 35.5 Inlet air velocity (m/s) 0.2 0.2 0.2 0.2 . Case (a) . Case (b) . Case (c) . Case (d) . Wall temperature (°C) 15 15 15 15 Ground temperature (°C) 35.5 35.5 35.5 35.5 Inlet air velocity (m/s) 0.2 0.2 0.2 0.2 Open in new tab Figure 10 shows the vertical and horizontal velocity profile in the middle of the cavity. Figure 10a shows the convective strength of the air increased as it rises vertically next to the block surfaces towards the upper boundaries of the underhood. The air velocity arrived at 0.13 m/s at Y = 1.03 m for two configurations. In detail, the maximum value of the velocity (0.05 m/s) appears at Z = 0.11 m for configuration (a) while the maximum for configuration (b) appears at Z = 0.9 m (0.04 m/s). Figure 10 Open in new tabDownload slide Velocity components for configuration (a); vertical velocity W (left) on the central parts (Z = 0.502 m) and horizontal velocity V (right) at Y = 0.502 m. Figure 10 Open in new tabDownload slide Velocity components for configuration (a); vertical velocity W (left) on the central parts (Z = 0.502 m) and horizontal velocity V (right) at Y = 0.502 m. The efficiency distribution of temperature inside the room is calculated in two central parts (Y = 0.502 m and Z = 0.502 m) in order to define an ideal configuration between four proposed configurations and to obtain a comfort and homogeneous temperature inside the room. As observed, the temperature distribution along Z direction varies for the two configurations. Figure 11 shows that the temperature sheer occurs near the walls at the outlet, while the temperature in the core of the room is quite small. The peak near the wall reaches 21°C for configuration (a). The natural convection causes an increase of the temperature in the large central part of cavities. These profiles showed that all temperature gradients are located near the walls. It should be noted that configuration (a) provides the highest temperatures at Z = 0 than configuration (b) due to the low contribution of the natural convection and a better air mixing with the (b) configuration, caused by the air circulation cell developed at the interior. Figure 11 Open in new tabDownload slide Temperature profiles for configuration (A and B); vertical temperature (left) on the central parts (Z = 0.502 m) and horizontal temperature (right) at Y = 0.502 m. Figure 11 Open in new tabDownload slide Temperature profiles for configuration (A and B); vertical temperature (left) on the central parts (Z = 0.502 m) and horizontal temperature (right) at Y = 0.502 m. The temperature distribution along Y direction varies between 35°C and 24°C in comparison to an outside temperature of 15°C for the two configurations. It can be seen that the temperature distribution is more homogenous along the length of the room between Y = 0.16 m and Y = 0.8 m. In this region, the air temperature is the same as the outside (16°C–17°C), while on the upper part along Z direction, the temperature decreases until reaching a value of 15°C. For the case of the vertical center plane, the air velocity is calculated, and it is represented in Figure 12a. The fluid is pushed into the wall on the right, where it flows downward before moving back up the left side of the cavity. This motion creates a large vortex in the center of the cavity. We can see that the velocities in the center of the cavity are lower due to the dissipation of the energy through the large viscous term. The plot velocity was characterized by a powerful airflow near the recirculation loop and the inlet opening with a slower speed around the center of the room. Below the height of the ventilator (1.022 m), the air velocities were decreased. Figure 12 Open in new tabDownload slide Computed vectors of the air velocities (a) and temperature distribution (b) for configuration (a). Figure 12 Open in new tabDownload slide Computed vectors of the air velocities (a) and temperature distribution (b) for configuration (a). In configuration (b), the air temperature rose inside the building around the corner in consequence of the small air velocities intensity. However, it was 6°C greater than the outside temperature. According to this configuration, better air mixing was done by the cell located inside of the building caused the air temperature to displace constantly almost all over the building with 2°C higher than the outside as seen in Figure 13b. Additionally, there is proportionally a higher temperature at the lower left corner of the room. The heat is uploaded from the floor and pulled by the air current, where low air mixed and velocity existed. In the simulated situations, this is due to concentrated internal load from the room. In a real situation, it would be shown by dwellers and the tools settled inside of the area. During the entrance of cold air to the room, a colder place will neither be formed nor found, which means it is uniform as a result of proper mixing and a good circulation between the air in the room and the cold air supply. Noticeably, the jet area around the ceiling would be much cooler than the specified range in the above; however, the existing situation has no impact on comfort. Figure 13 Open in new tabDownload slide Computed vectors of the air velocities (a) and temperature distribution (b) for configuration (b). Figure 13 Open in new tabDownload slide Computed vectors of the air velocities (a) and temperature distribution (b) for configuration (b). The prediction of velocity vectors in the room is shown in Figure 13a. It is important to notice that the the air coming from the inlet reaches the floor upward flow reached the downstream wall. There is a core region in the center where the velocities are relatively small, and a strong vortex is shown at the ceiling of the room. Additionally, secondary vortices at cavity corners are very small. Configurations (C) and (D) The temperature profile along Y line is shown in Figure 15. It can be seen that a uniform distribution is produced between Y = 0.04 m and Y = 0.84 m and the air temperature is greater than outside within 2°C for configuration (c). In fact, for configuration (d) (Figure 4), the temperature distribution is uniform from Y = 0.04 m to Y = 0.4 m then it increases linearly by ~1°C until Y = 0.5 m and then the distribution becomes uniform at Y = 1.03 m. The distribution of the temperature along Z direction is demonstrated in Figure 15 for configuration (c). There is no difference with other configurations. In Figure 14, the two components of vertical and horizontal velocity profile in the middle of the cavity are presented for the two cases (c) and (d). Within the room, in this case (c), we notice that the location of the inlet and outlet on the same plane has influenced the distribution of the vertical velocity compared to the other cases. Figure 14 Open in new tabDownload slide Velocity components: vertical velocity W (a) on the central parts (Z = 0.502 m) and horizontal velocity V (b) on the central parts (Y = 0.502 m). Figure 14 Open in new tabDownload slide Velocity components: vertical velocity W (a) on the central parts (Z = 0.502 m) and horizontal velocity V (b) on the central parts (Y = 0.502 m). Figure 15 Open in new tabDownload slide Temperature at Z = 0.502 m (a) and temperature at Y = 0.502 m (b). Figure 15 Open in new tabDownload slide Temperature at Z = 0.502 m (a) and temperature at Y = 0.502 m (b). Figure 16 Open in new tabDownload slide Computed contours of the air velocities (a), temperature distribution (b) at X = 0.305 m for configuration (c). Figure 16 Open in new tabDownload slide Computed contours of the air velocities (a), temperature distribution (b) at X = 0.305 m for configuration (c). Figure 17 Open in new tabDownload slide Computed contours of the air velocities (a), temperature distribution (b) at X = 0.305 m for configuration (d). Figure 17 Open in new tabDownload slide Computed contours of the air velocities (a), temperature distribution (b) at X = 0.305 m for configuration (d). Figure 18 Open in new tabDownload slide EDT contours clipped case (a) and case (b). Figure 18 Open in new tabDownload slide EDT contours clipped case (a) and case (b). Figure 19 Open in new tabDownload slide EDT contours clipped case (c) and case (b). Figure 19 Open in new tabDownload slide EDT contours clipped case (c) and case (b). Figure 20 Open in new tabDownload slide Air Diffusion Performance Index (ADPI) for the four configurations. Figure 20 Open in new tabDownload slide Air Diffusion Performance Index (ADPI) for the four configurations. Based on the results taken from the styles of the flow, the space inside of the room comprises a vortex that is big and occupies nearly all the existing space in the room and a smaller counter clockwise vortex at the corners of the room. The detailed specification of this type of configuration is expressed in Figure 16a. As shown in Figure 16b, the patterns of the temperature related to these cases present an acceptable uniformity and also the space of the room is within the limits of comfort. Proportionally, the lower left corner of the room possesses high temperature. The heat uploaded from the floor and pulled by the air current, where low air mix and velocity exist. Concentrated internal load from the room leads to this. By looking at the velocity forms that are shown in Figure 17a, some important similarities in the values of velocity at the lower and higher levels can be observed. By decreasing the supplied air temperature, a negligible drop is noticed in the air velocity. This is because of the lower volume of the air supplied and circulated in the room. As shown in Figure 17b, the room temperature is held between 16°C and 20°C. The existence of high air temperature in this area is because of a low air near the room. In the corners of the room and in the central part elevation, the temperature was 20.38°C and 16.35°C higher than the outside, respectively. At air inlet and outlet zones, air velocity represents higher values. Opposed to this, velocity is reduced in the lower parts from the center to the top of the structure. 4. DISCUSSION Generally, thermal comfort is felt when the loss of heat from the body is equivalent to the amount of produced heat, while the person is unconscious of the changes in his temperature-regulating mechanisms. The thermal comfort according to the ASHRAE Standard 55-2010 [40] is defined as a state of mind that makes one feel satisfied with the thermal environment. This satisfaction is affected by several elements, namely temperature, humidity, air speed, radiation, clothing and activity level. A selection of parameters is considered to evaluate comfort. In a given case, cold drifts should be considered during the distribution of cold air in an area. Draft is an unwanted local cooling of the body, resulting from air movement. The draft feeling is calculated by means of the EDT based on the ASHRAE Handbook [41]: $$\begin{align} EDT=\left({T}_i-{T}_r\right)-7.66\left({u}_i-0.15\right) \end{align}$$(9) Based on the EDT, another parameter that can also evaluate the performance of space air diffusion is called the ADPI and is defined by Wang [42] as follows: $$\begin{align} ADPI=\frac{N_c}{N}\times 100 \end{align}$$(10) Here Nc is number of points measured in the occupied space that falls within (−1.7 ≤ EDT ≤ 1.1 and V ≤ 0.35 m/s) and N is the total number of point in the occupied zone. There is an index to assess the system of distribution applied in a room called ADPI. It is expressed as the number of points satisfying the criteria (−1.7 ≤ EDT ≤ 1.1 and V ≤ 0.35 m/s −1) to the total number of points in the occupied surface. This draft-assessment index is suggested by ASHRAE Handbook [41] for assessing the comfort in a region that is introduced to cold air drafts. The most favorable ADPI value is higher than 80%. The computed ADPI in the environmental chamber at the four different cases is shown in Figures 18 and 19. In case (a), most of the EDTS values are positive. The EDTS values distribute more evenly on the center of the room while they increase near the left wall where the inlet exists. The discomfort zones are near the top wall and above ground. On the other hand, the outlet near the ground increases the value of the EDT to exceed the threshold value of 1.7, hindering the values of the ADPI of 75% (Figure 20) in this case from reaching 80%. For the second case (b), the most negative EDT values are located near the top wall and right wall where the outlet exists. However, above ground, the EDTS values are higher than 1.7 and it is outside the accepted limits. The ADPI shows a small improvement but remains lower than the accepted limit defined as 80%. It is suggested that EDTS is considered to be satisfactory if −1.2 < EDTS<1.2 and to be good if −0.6 < EDTS<0.6. In this case, most of the values of EDTS are ranging between −0.6 and 0.6 (Figure 19). The values of ADPI 89.74% (Figure 20) are the closest value to the allowed indices of comfort. Overall, all the tips mentioned in configuration (c) meet ASHRAE 55-2010 [40], the air velocity in all points is smaller than 0.2 m/s but for most of them it is between 0.2 and 0.04 m/s. In this last case (d), the EDTS contours is clipped in two parts, in which the most negative value is located in top parts while all the positive values exist in lower parts. Consequently, the ADPI is around 50% (Figure 20), which reflects a lower comfort level; it clarifies the fact that configuration (d) represents the worst outcomes and affirms that the lowest ventilation efficiency as well as the most determined EDTS values are not within the range of −1.7 to 1.1 K. On the whole, all the tips mentioned in this configuration do not meet ASHRAE 55-2004 [43] as they are not placed inside of the comfort zone (Figure 19). The air velocity in all points is smaller than 0.1 m/s but for most of them, it is between 0.05 and 0.1 m/s. The temperature of the aforesaid points is between 16°C and 20°C (Figure 17). 5. CONCLUSIONS The effectiveness of opening position in windward ventilation of a building room was researched numerically modeled by applying the CFD simulation approach and validated by experimental results. Four types of configurations of opening location were investigated, which resulted in various rates of ventilation, airflow and temperatures patterns. The main conclusions of the present article are listed as follows: I) These findings confirm that the opening location can always be the best standard to assess the function of diverse ventilation systems and thermal comfort in buildings. II) The aforesaid criteria revealed that the most favorable solution for evaluating thermal comfort is to put the inlet and outlet opening in the middle of the side wall. III) In the best way, the numerical model reasonably simulates the performance of building ventilation. IV) The maximum value of the velocity along the direction z appears at Z = 0.11 for configuration A where the velocity value is 0.05 m/s while the maximum for configuration B appears at Z = 0.9 m for the velocity value of 0.04 m/s. V) In the room, the upward flow reached the celing and the air coming in from the inlet fan reaches the floor. VI) For configuration (d), the temperature distribution is uniform from y = 0.04 m to Y = 0.4 m then it increases linearly by ~1°C until y = 0.5 then the distribution becomes uniform at = 1.03 m. VII) The computed ADPI in the room at the four different cases showed that configuration (d) represents the worst outcomes and configuration (c) is the best and meets ASHRAE 55-2010. 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TI - Effect of inlet/outlet on thermal performance of naturally ventilated building
JF - International Journal of Low-Carbon Technologies
DO - 10.1093/ijlct/ctab055
DA - 2021-12-29
UR - https://www.deepdyve.com/lp/oxford-university-press/effect-of-inlet-outlet-on-thermal-performance-of-naturally-ventilated-lkdkE8NEPg
SP - 1348
EP - 1362
VL - 16
IS - 4
DP - DeepDyve
ER -