A domain with classical dimension has been studied numerically by STARCCM+ based on recent research and innovation in the field of Energy and Buildings. Conceiving temperature range of summer ( May-July) in southern France, Mixed mode (M echanical ventilation through inlet, N atural ventilation in room) ventilation method has considered as a mean of air refreshment in a classical room . Moreover, n umerical analysis has performed at Reynolds Number (Re) 8.6 x 102, 1.7 x 103 to examine effect s of inlet angle (horizontal, inclined) and domain wall thickness in air refreshment . Finally, all the parameters have compared by bulk temperature on horizontal planes and heat transferred from domains to find out the optimum solution. Keywords: Air refreshment in Buildings, Mixed mode ventilation, 3D unsteady numerical analysis ii Nomenclature : Variables m Mass ̇ Heat transfer rate k Turbulent kinetic energy Fs Factor of safety p Order of accuracy r Grid refinement factor t Time ⃗ Fluid velocity vector ⃗=(𝑢, ,𝑤) x Horizontal coordinate y Vertical coordinate z Depth coordinate 𝐶𝑑 Coefficient of discharge Variables E Total energy G Production of turbulent kinetic energy Keff Effective conductivity N Number of cells P Pressure T Temperature ̇ Mass flow rate cp Specific heat ⃗ Velocity field correction Pressure correction Thermal conductivity Qcond Conductive heat transfer Greek Letters 𝛽 Thermal expansion coefficient ε Turbulent rate of dissipation 𝜌 Density of fluid μ Viscosity Fluid tensor Subscripts 1 Fine grid 2 Medium grid 3 Coarse grid in Into the room out Out of the room 1 I. INTRODUCTION Though the idea of innovative house flourished in 17th century, the actual application started in 20th century. Many researches have proved that world is heading to an energy crisis in near future. Utilization of natural resources could be a probable solution for a greener, better and economical world. As a conseq uence of energy crisis , Thermal Regulation (RT) has been embodied for building construction before few decades. The first thermal regulatio n dates back to 1974 (RT 1974) . Afterword, new thermal regulation goal ha d been set and fulfilled successively (i.e. RT 1988, RT 2000, RT 2005, RT 2012 and RT 2000) . The RT 2012 was aimed new homes to consume up to 50 kWhep par m2 par years. However, t his value changes notably depending on the region and the altitude at which the house is located. This maximum consumption defines the building low consumption. Finally , RT 2020 has also been regulated with a goal of positive energy production sy stem in buildings which means the energy production will be more than requirement. The imminent computational work of this scientific article was a part of an innovative air refreshm ent system for buildings with an endeavor to attain RT 2020 in near future . Meanwhile , many ingenious inventions such as Free or Natural cooling, solar heating, Mechanical or F orced ventilation, mixed mode ventilation have been introduced to the world as a consequence of regulation of building construction. As a part of study, literature review has been done to explore previous research on ventilation process. For instance , Jiang et al. [1] presented a n experimental and n umerical computational study (LES, large eddy simulation) of natural ventilation, driven only by wind forces for simple geometries representing cross -ventilation and single -sided ventilation configurations. In order to reduce the comput ational cost, Evola and Popov [2] applied Reynolds Averaged Navier -Stokes (RANS) models, the standard and the RNG models, for the experimental set up described in reference [1 ], and also obtained reasonable accuracy for the velocity distribution inside the building model and also for the ventilation flow rates . Another study has been done by Mingang Jin et al . [3] for solving natural convection problem. The study investigated Fast Fluid Dynamics (FFD) performance for simulating natural ventilation . FFD was applied to different types of natural ventilation, such as wind -driven, single -sided natural ventilation, wind -driven cross natural ventilation, and buoyancy -driven, single - sided natural ventilation. They also examined the impact of wind directio n and applied FFD to natural ventilation in a building complex. T. Catalina et al. [4] has studied a full -scale experimental campaign and a computational fluid dynamics (CFD) study of a radiant cooling ceiling installed in a test room, under controlled con ditions. Their research aims to use the results obtained from the two studies to analyze the indoor thermal comfort using the predicted mean vote (PMV). During the whole experimental tests the indoor humidity was kept at a level where the condensation risk was minimized and no condensation was detected on the chilled surface of the ceiling N.C Markatos et al [5] have considered natural ventilation as solution of increasing energy consumption due to mechanical ventilation, atmospheric pollution and global wa rming. They have suggested that the proper design of natural ventilation must be based on detailed understanding of airflow within enclosed spaces, governed by pressure differences due to wind and buoyancy forces. Now, If we focus on wall thickness of the domain, an unsteady three -dimensional conjugate heat and mass transfer in an enclosure having finite thickness heat -conducting walls has been analyzed numerically by Sheremet et al [6 ]. They have solved the governi ng unsteady, three -dimensional flow, energy and contaminant transport equations for the gas cavity and unsteady heat conduction equation for solid walls by using an iterative imp licit finite -difference method. To take the previous study one step forward, C onjugate natural and forced convection heat transfers in a domestic model room of finite - thickness walls and a heat source have been numerically studied by Horikiri et al [7 ] From the analysis of previous literature relevant to natural and mechanical venti lation , it is easily apprehensible that only a few studies have been done before regarding inlet angle effect on heat removal from domain . Therefore, we will try to take old studies one step further by considering two differ ent inlet angles which will be tested numerically for same do main in this imminent study. 2 During the study, a classical empty room was assumed as domain with horizontal and inclined inlet for summer season and the temperature range had been considered for southern region of France. Then the effect of inlet angle for air refreshment has been observed by numerical simulation at Reynolds number 8.6 x 102 and 1.7 x 103 to acquire op timal solut ion for the system. Meanwhile, Mixed mode (M echanica l ventilation through inlet, N atural ventilation in room) ventilation method had considered as princip le of heat removal from room. As the N atural ventilation is a major part of M ixed-mode ventilation and optimally operate in small temperature difference, the system will function 30 minutes just in night when the outdoor temperature is lower than indoor. A mechanical fan was placed for forced ventilation at the inlet which located below the window and the outlet is placed just upper portion of window. The domains have been simulated with maximum critical conditions so that we can ensure about the system’s highest ability r egarding heat removal. Hence , window remained closed because sometime it’s might not possible to open window due to dust, noise or insects especially room located in ground floor. Moreover, the door was also considered closed and there was no air pass except outlet. II. GOVERNING EQUATION As interaction between Natura l and F orced convection has been investigated inside a three dimensional enclosure , the governing equation contains conservation of Momentum, M ass and Energy equations. The conservation of M omentum is commonly referred as the Navier -Stokes Equation . Additionally, conservation of Mass and E nergy are also used to solve velocity and temperature field in domain respectively . Conservation of M omentum : 𝑢 𝑢 𝑢 𝑢 𝑤 𝑢 𝛽( ) ( 𝑢 𝑢 𝑢 ) ( ) Conservation of M ass: 𝜌 𝜌( 𝑢 𝑢 𝑢 ) ( ) Conservation of E nergy: 𝑢 𝑤 ( ) ( ) Governing equations are made non -dimensional using following length and velocity scales 𝑢 𝑢 𝑢 Therefore, dimensionless form of governing equations can be stated as following : Conservation of Momentum : 𝑢 𝑢 𝑢 𝑢 𝑤 𝑢 𝛽( ) ( 𝑢 𝑢 𝑢 ) ( ) Conservation of M ass: 𝜌 𝜌( 𝑢 𝑢 𝑢 ) ( ) 3 Conservation of E nergy : 𝑢 𝑤 ( ) ( ) III. NUMERICAL MODELING A. Geometry and boundary conditions: The geometr y chosen in the study was a classical room. The computational domain associated to the geometry was made of entire room with extruded inlet and outlet for the tranquilization of the flow as illustrated in fig ure 1. As stated previously, horizontal and inclined inlet had considered as a purpose of evaluation. Figure 1(a): Classical d omain (Left: Room with Horizontal Inlet; Right: Room with Inclined Inlet) Inlet angle has been calculated by vector relation of velocity component for X and Z axis as following: ( ) Adiabatic wall condition was applied to the numerical simulation of all (without wall thickness ) domains . Domain with wall thickness was also considered to examine the effect of wall thickness on heat removal from the room. For simulation of domain with wall thickness , outside ambient temperature was applied to all the outer wall surfaces and the walls were considered as non -adiabatic except the floor of the room. A contact type interface had been used for proper heat transfer between solid walls and fluid region inside the room. Over and above, velocity inlet and pressure outlet was selected to the inlet and outl et of the domain respectively. Temperature distribution within the solid region of thick wall is governed by 1-D heat conduction equation that could be expressed as ( ) At the interface between fluid region and solid region in the conjugate heat transfer model, the conductive heat transfer throughout the solid is coupled with the convective heat transfer in the fluid by ( ) ( ) Where is dimensionless temperature and is wall thermal conductivity Moreove r, for a large plane wall, one -dimensional (1 -D) heat conduction equation can be applied and using the Fourier’s law, the equation can be written as Figure 1(b): Window configuration 4 𝑑 𝑑 ( ) Where Qcond is conductive heat transfer, K is thermal conductivity of solid material, is the temperature gradient, and A is the heat conduction area (m2). Thus, the total and surface heat fluxes can be evaluated by ( ) Where, qtotal is total heat flux ( w/m2 ), Rtotal is total thermal resistance (i.e., R-value) ( m2k⁄ w), qsurface is surface heat flux, h is heat transfer coefficient ( w⁄ m2k) and indexes in and out are internal and external environments, subscript ∞ is ambient condition and inner surface and outer surface are internal and external surfaces of a finite -thickness wall. Conceiving above the oretical aspect, we have considered horizontal inlet (Re= 1.7 x 103 ) domain with wall thickness. Concrete wall around room was considered 13 cm. For two different regions, two different models i.e. solid for walls and fluid for inner room space were chose n during numerical model section. Moreover, contact type interface was selected for conjugate heat transfer between fluid and solid model. Pr. Outlet Vel. Inlet … … … (10) … … … (11) A Solid Region Fluid Region Interface Pr. Outlet Vel. Inlet Figure 2: Domain’s boundary c ondition without wall thickness ; A = Adiabatic ; Pr. = Pressure; Vel. = Velocity Figure 3: Domain’s boundary c ondition with wall thickness ; Pr. = Pressure; Vel. = Velocity 5 B. Grid independence analysis: After developing 3D room geometry in the StarCCM+ CFD software, trimmer hexa mesh was generated with prism layer and surface remesher. The optimal one was chosen by grid independent analy sis. The discretization error was studied using the grid convergence index (GCI). The GCI has proposed by Roache [8] for uniform reporting of grid convergence studies. The GCI is based on the Richardson extrapolation [9], where the discrete solutions are assumed to have a series represen tation o f the discretization error. GCI converts the Richardson extrapolation error estimate into an uncertainty by using absolute values to provide an uncertainty bounds and using a factor of safety (Fs). Solutions for fine, medium, and coarse grids are subscripted with n, n+1, and n+2 , respectively. The GCI can be represented as: 𝐶 | | where r is the grid refinement factor, p is the order of accuracy . The grid refinement factor r for three -dimensional study is: ( ) Where N is the number of cells or elements The order of accuracy is then estimated by using the following equation: ( ) ( ) Several domains with different grid number such as , , , was tested to find the optimal grid for numerical solution. Figure 4: Grid independence test by Pressure ( Pa) at the inlet. The error bar in the plot shows 1% error. As the exact error for grid and was 0.9 % and 0.6% , while the GCI was 0.33% and 0.25% respectively. We have chosen the grid to reduce computational cost especially in the unsteady simulation. … … … (12) 6 Figure 5: Mesh ( ) of room with inclined inlet (EM: Extruder Mesh) Moreover, Extruder mesh has been built in the inlet so that the velocity profile can develop up to the desired value at the domain inlet surface. Same procedure was followed to outlet for pressure according to StarCCM+ user guide. C. Numerical model selection: For solving the convection problem unsteady, incompressible, turbulent ( k-ε) model, due to Rayleigh number 7.3 x 1011, was chosen . Moreover, RANS and realizable two layer additional model had also considered according to literature review and Star CCM+ user guide. Firstly, Ideal gas with segregated flow, due to incompressible fluid, was selected according to user guide and then the same problem with coupled flow had also solved to identify accu racy of numerical solution. Moreover, Computation had been made with finite volume code. Second order upwind scheme was used in the discretization of governing equation. SIMPLE algorithm is used to link the pressure and velocity field. First order time implicit scheme has been used to resolve the unsteady term. The time step used in the computations is 1.0 s. D. Time step independence analysis: An optimal time step was chosen by comparing the three different, such as 0.5, 1.0, 2.0, solver time steps. For each time step the result was same except the simulation time needed to compute 30 minutes operation of system by Intel Xenon processor . Finally we have decided to consider the solv er time step 1.0 to save time. Time step has been calculated by following formul a 𝐶 𝑢 𝐶 𝑢 𝐶 Where, is the spacing of the grid; is the time step and u is the velocity. The value of Cmax is dependent on the method used to solve the system of algebraic equation (Explicit/Implicit). For explicit solver, Cmax = 1; for Implicit on the other hand, Cmax may be a little bigger numbe r, but it wouldn’t go beyond 2. ……… (13) EM Figure 6: Time step comparison by Temperature (k) at 1.5m from the floor Figure 7: CPU time comparison 7 IV. RESULTS ANALYSIS Numerical simulations were performed with domain (room) to verify the effect of inlet angle. The comparison between two different configurations was made by heat transfer and bulk temperature considered on different horizontal plan e between floor and ceiling. By definition Bulk temperature is the mass weighted average temperature at a given axial location/plane. Bulk temperature can be defined as: ∫𝑢 𝑑 Where the mean velocity can be expressed as: ∫𝑢 𝑑 We have chosen bulk temperature as a function of ‘z’ axis only in order to evaluate the mixing and therefore the average thermal comfort along the height of the room to evaluate the effect of geometrical and dynamic parameters on the characteristic time and uniformity of heat removal in the room. A. Flow structure with temperature distribution : Streamlines has been determined inside domain to realize flow structure and temperature distribution . Initially lower Reynolds number (Re=8.6 x 102 ) represents heat removal just at the lower portion of domain after successful termination of air refreshment system (30 min utes). Though the lower portion of the room temperature was decreased to outside ambient temperature, remaining part of the domain possess maximum temperature. Hence , we have increased velocity of the inlet by remaining other parameter s as earlier that theoretically also increased the Reynolds number (Re=1.7 x 103). Finally , the new results were one step more close to the desired goal than earlier. So, It conveyed exceeding heat removal. Case 1 : Re=8.6 x 102: Case 2 : Re=1.7 x 103: … … … (14) Figure 9: Inclined inlet Figure 8: Horizontal i nlet Figure 10: Horizontal i nlet Figure 11: Inclined inlet 8 B. Inlet angle comparison: Horizontal and I nclined inlet has compared by bulk temperature at different horizontal planes to find out the optimal selection of inlet for maximum heat removal from domain. For lower Reynolds number ( Re =8.6 x 102), inclined inlet (dotted Line) represents lower temperature than horizontal inlet (solid line) up to 1.5 m from the floor. However, temperature pattern has inverted from above 1.5 m to rest of the domain. Similar tendency has been observed in Reynolds number, Re = 1.7 x 103. Moreover, increment of Reynolds number helped to remove additional heat from domain that was also prominent in flow structure and temperature distribution graph. Figure 12: Horizontal i nlet, Re =8.6 x 102 Figure 13: Inclined i nlet, Re =1.7 x 103 Therefore, from the comparison of inlet angle effect it can be conclude that bulk temperature of different planes indicates, inclined inlet could be suitable from floor to 1.50 m for lower temperature while horizontal inlet for rest of the part (above 1.50 m). C. Total heat transfer: Heat transferred or removed from the domain was also considered to identify more reliable results because the more heat is transferred or removed from the domains then the thermal comfort wil l increase. We have calculated all the domains for segregated flow solver with ideal gas and heat transfer has been calculated throughout the simulation duration (1800 seconds). Then summation of heat transfer at every second mathematically leads to total heat transfer from domains. Furthermore, those two parameters have been compared not only graphically but also numerically to verify the accuracy by absolute and relative error. Heat flux removed from the insulated room between the inlet and the outlet by the air flow can be defined as follow: ̇ ̇ 𝐶 Then total heat removed from the room during an operation period of time is then ∫ ̇ 𝑑 Graphical representation of heat transferred from domain throughout the air refreshment process has illustrated below … … … (15) … … … (16) 9 Table 1: Inlet angle effect comparison by total heat transfer Hence, a bove comparison of total heat transfer shows that horizontal inlet removes comparatively more heat than inclined inlet. D. Wall thickness effect: The effect of wall around domain has been observed by drawing disparity of bulk temperature and total heat removal with a domain without wall thickness. As we have seen from the previous result analysis that horizontal inlet with Re=1.7 x103 was close enou gh to the desired goal of air refreshment system, we have considered those parameters to analyze wall thickness effect. Now if we focus on quantitative results by comparing bulk temperature at different horizontal planes for both configurations, we have se en that there was a significant temperature variation after 30 minute of heat removal. Furthermore, the temperature decreases negligibly even after one hour of heat removal for wall thickness effect. Figure 16 : Wall thickness effect comparison by bulk temp Figure 17 : Wall thickness effect comparison by heat transfer Therefore, we can easily conclude that we need more time for desired heat removal with wall thickness. The time for heat removal would be a function of wall materials, thickness, insulation type and some other parameters corresponding to different phenomenon. Figure 14: Heat transfer (KJ), Re=8.6 x 102 Figure 15: Heat transfer (KJ), Re=1.7 x 103 10 V. CONCLUSION A classical empty room was assumed as domain with horizontal and inclined inlet for summer season and the temperature range had been considered for southern region of France. Then the effect of inlet angle for air refreshment has been observed by numerical simulation to acquire op timal solution for the system. Meanwhile, M ixed mode (M echanica l ventilation through inlet, N atural ventilation in room) ventilation method had considered as principle of heat removal from room. As the N atural ventilation is a major part of M ixed-mode ventilation and optimal ly operate in small temperature difference, the system will function 30 minutes just in night when the outdoor temperature is lower than indoor A mechanical fan was placed for forced ventilation at the inlet which located below the window and the outlet is placed just upper portion of window. We have simulated domains with maximum critical conditions so that we can ensure about the system’s highest ability regarding heat removal. Therefore, window remained closed because sometime it’s might not possible to open window due to dust, noise or insects especially room located in ground floor. Moreover, the door was also considered closed and there was no air pass except outlet. Numerical analysis has been performed with Reynold s Number 8.6 x 102, 1.7 x 103 by considering effect of inlet angle (horizontal, inclined) and wall thickness. Finally, all the parameters have compared by bulk temperature on horizontal planes and heat transferred from domains to find the optimum solution. For inlet angle effect , Inclined inlet represents lower temperature than horizontal inlet up to 1.5 m from the floor in lower Reynolds number . However, temperature pattern has inverted above 1.5 m from the floor up to rest of the domain. Similar tendency has been observed in Reynolds number 1.7 x 103. Moreover, increment of Reynolds number helped to remove additional heat from domain that was also prominent in flow structure and temperature distribution graph. From the comparison for inlet angle effect it can be conclude that bulk tem perature of different planes indicates, inclined inlet could be suitable from floor to 1.50 m for lower temperature while horizontal inlet for rest of the part (above 1.50 m). In case of wall thickness consideration, we can easily conclude that we need mo re time for desired heat removal with wall thickness. The time for heat removal would be a function of wall materials, thickness, insulation type and some other parameters corresponding to different phenomenon. 11 VI. ACKNOWLEDGEMENT First of all, I would lik e to be grateful to the Almighty for bestowing me the strength and patience to co mplete the project successfully . I would also like to thank Mr. Yannick HOARAU (Professor, Computational Engineering Dept., Université de Strasbourg , France ) for his encouragement , guidance and beneficial criticize on this project. Fin ally, I solemnly acknowledge that this project wouldn’t be successful without financial and technical support provided by Ener gy, Electricity and Automation D epartment, Hautes Etudes d’Ingénieur –Lille. VII.