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Physical and Numerical Modeling Evaluations for Air-

Conditioned Multipurpose Hall

Dr.Ahmed A.Medhat 1 and Prof.Dr.Essam E.Khalil 2 1 Senior Research Scientist at Housing, Buildings Research Centre (HBRC), Cairo- Egypt

2 Professor of Mechanical Engineering, Cairo University, Cairo-Egypt

ABSTRACT

This paper focuses on both physical and numerical modeling of full-scale modeled air-conditioned multipurpose hall fully operable. To evaluate and optimize the thermal parameters affecting the zone comfort conditions. This is accomplished through the application of two different modeling approaches. First approach is to carry out experimental full-scale modeling utilizing a developed experimental technique depending on artificial intelligence rig, which is constructed to be fully automated .wireless mobile test rig remotely controlled by pre-programmed computer and using high precision state-of-the-art measuring instruments. While the Second approach is to carry out a numerical modeling using a well developed [CFD] 3DHVAC code and computer simulation program. Physical and Numerical investigations enable the analyses and investigations of the influence of Reynolds, Archimedes and Prandtl numbers for the air as well as the effects of shape, location, inlet air velocity of supply outlet on the flowing air parameters. These parameters include throw, drop, air induction, room local velocities, humidity ratio and temperatures distributions. Collected, information and data obtained from physical modeling compared with corresponded numerical modeling results, while gained data from both techniques were compared with statistical data collected from occupancies of this multipurpose hall to evaluate the validation of these modeling techniques. Such data and information will have a great impact on air distribution modeling assessments and contribute for a detailed knowledge of spatial and temporal distributions of local velocity and temperature, Thus, better understanding of fluid flow interaction in air-conditioning spaces also showed and identified the velocity fluctuations components modelling, which play a vital role in the validation of the numerical modeling. One of the main conclusions is that good agreement between both of full-scale physical modeling and numerical modeling were reported .While the reported comparisons concluded that qualitative agreements were shown, some discrepancies were also observed in the thermal parameters for comfort conditions required by different occupants.

PROBLEM FORMULATION

The proper tactical airflow distribution is required in all applications in the multipurpose halls to ensure comfort of occupants. The airflow distribution in its final steady pattern is a result of different interactions such as, the airside design, objects distribution, thermal effects, occupancy movements, etc, see references [1 to 14]. The airside design and internal obstacles are the focus of the present work. The forced air supply of cooled air streams out of high wall mounted, 150 downward inclined jets is investigated with mechanically extracted air from the top of the split units as shown in figure 1. This configuration played an important role in the main flow pattern and the creation of main recirculation zones. The internal obstacles would naturally obstruct the airflow pattern in different ways and means, by for example increasing the recirculation zones size, relocating these and or deflecting the main airflow pattern. The present work followed both experimental and numerical approaches to properly understand and analyze room air flow patterns. A ready available commercial ANSYS 3D Computational code, [15] was used to predict the air flow patterns and thermal behavior. On the other hand an experimental traversing mechanism, computer-based and operated by PLC was developed and used to map the velocity and temperature contours. The room was typically used as the chairman office, meeting room and seminar room. MODELED EQUATIONS The program solves the differential equations governing the transport of mass, three momentum components, and energy in 3D configurations under steady conditions [1-7]. The different governing partial differential equations are typically expressed in a general form as:

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AIAA 2005-566

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ΦΦΦΦ +���

����

�

∂Φ∂Γ

∂∂+��

�

����

�

∂Φ∂Γ

∂∂+��

�

����

�

∂Φ∂Γ

∂∂=Φ

∂∂+Φ

∂∂+Φ

∂∂

Szzyyxx

Wz

Vy

Ux effeffeff ,,,ρρρ ............ (1)

Where: ρ = Air density, kg/m3 Φ = Dependent variable. SΦ = Source term of Φ. U, V, W = Velocity vectors. ΓΦ, eff = Effective diffusion coefficient. The effective diffusion coefficients and source terms for the various differential equations are listed in the following table1. Turbulence model of Launder et al [9] was incorporated in the present work. Details of the modeling technique and assumptions can be found in references [9] to [13].

Table 1: Terms of Partial Differential Equations (PDE) Φ ΓΦ,eff SΦ Continuity 1 0 0 X-momentum U µeff -∂P/∂x +ρgx Y-momentum V µeff -∂P/∂y +ρgy(1+β∆t) Z-momentum W µeff -∂P/∂z +ρgz H-equation H µeff/σH SH k-equation k µeff/σk G - ρ ε ε-equation ε µeff/σε C1 ε G/k – C2 ρ ε2/k

µeff = µlam + µ t µ t = ρ Cµ k2 / ε

G = µt [2{(∂U/∂x)2 +(∂V/∂y)2 +(∂W/∂z)2}+(∂U/∂y + ∂V/∂x)2 +(∂V/∂z + ∂W/∂y)2 +(∂U/∂z + ∂W/∂x)2] C1 = 1.44, C2 = 1.92, Cµ = 0.09 σH = 0.9, σRH = 0.9, στ = 0.9, σk = 0.9, σε = 1.225

Model Validation

Previous comparisons between measured and predicted flow pattern, turbulence characteristics, and heat transfer were reported earlier in the open literature, reference should be made to these for further details and assessments. The predictions of flow and turbulence characteristics were reported to be in general qualitative agreement with the corresponding experiments and numerical simulations published by others, Kameel, [12], Neilsen, [13] as reported in the work of Khalil [14]. The obtained trends are in adequate agreement for engineering purposes. Nevertheless discrepancies exist and particularly in the vicinity of recirculation zone boundaries. More discrepancies were also observed in situation with heating flows than those of ventilation or cooling.

EXPERIMENTAL SIMULATION The present experimental program describes the test facility setup and the procedure followed in present measurements.

Experimental Facility The room under investigation, at HBRC, was provided by three commercially available high wall split units each of 7.05 kW cooling at supply airflow rate of 0.3-m3/s .These were installed at 2.85 m height. The supplied airflow to the room was inclined downward at 15 o to the horizontal .The return air was taken back through a top horizontal return grille. Whose dimensions were 0.10 x 0.9 m .The supply swiveled diffusers were at a fixed position during measurements. The present experiments were performed with the presence of the room furniture, such as the desk, tables, cupboard and all additional accessories, as shown in figures 1-a and 1-b. The room dimensions are 12 m in length (L), 5.4 m in width (w), and 3.05 m in height (H). Measurements were obtained at two vertical planes at the middle of the first two split air conditioners and also at a horizontal plane at the supply level of 2.85 m above room finished floor. The local values of velocities, temperatures, and humidities were individually measured inside the room. The exterior walls were made of 0.4 m thick concrete brick wall and equipped with three high wall cooling systems (in operation during this work). The air-cooled condensing units were located outside the room. Heated thermocouple anemometer was used .its probe has a semi-sphere shape with a diameter of 1.0 mm, and was supported in separate

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telescopic support of a cylindrical shape with a diameter equals to 12.0 mm at its base position. Test rig concept was designed and manufactured by Medhat [6]. The test rig was developed several times to improve and refine its accuracy. This system is capable of measuring in different spaces with different flooring types. This specific size limit of the effective used part of test rig when cubed should never exceed 1: 2000 of volume of the room under test. Test rig consists of chained-wheel mobile carriage powered by two high torque independent 12- volts, DC, 1.80-deg, stepper motors remotely controlled by wireless serial port connected to personal computer. Each stepper motor can be driven separately allowing the carriage to move in X-Y plane. Mounted on this carriage a plastic cross acting tower carrying all probes and sensors are allowed to rotate around its vertical axes. Mounted probes can be moved longitudinally in the Z-direction and also able to rotate along its axes, this permits the probes to rotate around X-axes or Y-axes depending on the position of the carriage. Measurements at different locations in room are conducted by pre-programmed computer software, designed and adopted by Medhat [6] with the use of a control program licensed by National Instruments U.S.A. This program was Lab VIEW program. Probes when located at desired positions measure data that is transferred instantaneously in batches to the computer for analysis; this is followed by set of measured data to test rig again in a hand-shaking connection protocol. Data collected are instantaneously fed to the computer, recorded and saved. Measurements of local velocities, humidity and temperatures at any point in three-dimensional coordinates are based on controlled volume of dimensions (0.4 meter length, 0.5 meter width and 0.1 meter height). During room test procedure part of the measured control volumes were overlapped by fifty percent of its volume to assure accurate values (if required at critical expected zones). The distribution of the local velocity distribution have been obtained with the aid of heated-thermocouple anemometer air velocity sensors, the distribution of the local mean temperature have been obtained with the aid of thermal positive coefficient thermistor sensor and resistant-temperature device (RTD) and the local mean humidity distribution have been obtained by capacitive sensing elements see Medhat [6].

Figure 1A: Test Room Configuration

NUMERICAL RESULTS Figures 2,3,4, 5,6 and 7 showed the numerical prediction of the air velocity vectors and temperature contours in the X-Y vertical elevation section of the room at Z= 1.2 and 6 m (middle plane of the first two air conditioners ),figures 2,3 and 4. The obtained contours of are different in shape and indicated the influence of the airside design on the velocity & temperature distributions. On the other hand figures 5, 6 and 7 indicated the predicted velocities and temperature at a horizontal Z-X plane at height Y=2.85 m from finished floor.

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Figure 1B: Robotic Telescopic traverse mechanism for velocity and temperature measurements

Figure 2: Predicted Velocity Contours at two vertical planes, m/s, Z = 1.2 and 6 m

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Figure3: Predicted Air Temperature Contours, deg. K, at two vertical planes, Z = 1.2 and 6 m

The relative magnitude of flow pattern and jet spread indicated higher velocities in the jet with strong corner recirculation zones in the side wall vicinity. The architectural design restrictions may enforce such design on most of HVAC designers particularly for low ceiling height rooms.

Figure 4: Predicted Velocity Vectors at two vertical planes, m/s, Z = 1.2 and 6 m

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Figure 5: Predicted Velocity counters at a horizontal plane at the supply grilles level, m/s ,Y=2.85m

Figure 6: Predicted Air temperature, deg.K, at a horizontal plane at the supply grilles level, Y=2.85m

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Figure 7: Predicted Velocity Vectors/s, at a horizontal plane at the supply grilles level, Y=2.85m

EXPERIMENTAL RESULTS Samples of the experimental results of temperature and velocities relative humidity measurements over in the room will be presented here in graphical three-dimensional plots. The measured transverse U velocity profiles are shown here in Figure 8. The figures demonstrated good trend wise agreement between measured and predicted flow behavior of figures 2,4 and 5; some discrepancies were also observed. These comparisons gave a good indication of the present numerical model capability to predict the airflow characteristics in the vicinity of the internal objects.

DISCUSSIONS AND CONCLUSIONS From the previous results, one can conclude that the airside designs have a strong influence on the velocity and temperature distribution and consequently on the IAQ. The location of the supply outlets plays the major role in his distribution. The extraction ports should be located in the right location to correct the errors of the bad selection of the supply outlet positions. Due to the architectural design restrictions designers may be forced to incorporate a certain design that is seen to yield better air flow, temperature, relative humidity behavior .The restrictions of the architectural and civil engineer to use a large supply area hinders attainment of good indoor air quality and comfort.

ACKNOWLEDGMENT Thanks and gratitude are respectfully due to HBRC and Cairo University technical assistants for the technical support throughout the work.

REFERENCES [1].Olesen, B. W., 2000, Guidelines for comfort, ASHRAE Journal, page 41 - 46, August 1998. [2].ISO EN 7730, 1994, Moderate thermal environments – Determination of the PMV and PPD indices and specification of the conditions for thermal comfort, International Standards Organization, Geneva. [3].Berglund, L. G., 1998, Comfort and humidity, ASHRAE Journal, page 35 - 40, August 1998.

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[4].Fang, L., Clausen, G., and Fanger, P. O., 1996, The impact of temperature and humidity on perception and emission of indoor air pollutants, Indoor Air’ 96, Tokyo, Institute of Public health. [5].Tanabe, S., Kimura, K., and Hara, T., 1987, Thermal comfort requirement during the summer season in Japan, ASHRAE Transactions, 93(1): 564-577 [6].Medhat, A.A. 1999, Optimizing room comfort using experimental and numerical modeling, Ph.D. Thesis, Cairo University. [7].Kameel, R. 2002. Computer aided design of flow regimes in air-conditioned operating theatres, Ph.D. Thesis work, Cairo University. [8].Spalding, D.B., and Patankar, S.V. 1974. A calculation procedure for heat, mass and momentum transfer in three dimensional parabolic flows, Int. J. Heat & Mass Transfer, 15, pp. 1787. [9].Launder, B.E., and Spalding, D.B. 1974, The numerical computation of turbulent flows, Computer Methods App. Mech., pp. 269-275. [10].Khalil, E. E., 1978, Numerical Procedures as a tool to Engineering Design, Proc. Informatica 78, Yugoslavia. [11].Khalil, E. E., 1999, Fluid Flow Regimes Interactions in Air Conditioned Spaces, Proc. 3 rd Jordanian Mech. Engineering Conference, pp. 79, Amman, May 1999. [12].Kameel, R., and Khalil, E.E. 2002. Generation of the grid node distribution using modified hyperbolic equations, 40th Aerospace Sciences Meeting & Exhibit, Reno, Nevada, AIAA-2002-656, January 2002. [13].Nielsen, P.V. 1989. Numerical prediction of air distribution in rooms, ASHRAE, Building systems: room air and air contaminant distribution, 1989. [14].Khalil, E. E., 2004, Fluid Flow Regimes Interactions in Air Conditioned Spaces, Proc. JIMEC, Amman, 2004. [15].ANSYS, 2003, CFD CODE Manual, 2003.

Figure 8: Measured velocity Profiles at Z = 1.2 m, Uo = � .� 5 m/s