Seventh International IBPSA Conference Rio de Janeiro, Brazil August 13-15, 2001

ON THE NATURAL DISPLACEMENT VENTILATION FLOW THROUGH A FULL SCALE ENCLOSURE, DRIVEN BY A SOURCE OF BUOYANCY AT FLOOR LEVEL S. A. Howell and I. Potts University of Newcastle upon Tyne Newcastle upon Tyne, NE1 7RU, England

technique, which uses salt water to generate density ABSTRACT differences and motivate the displacement flow. This paper presents experimental data for the This paper reports independent validation work, temperature stratification established within a where a natural displacement ventilation flow, driven full-scale enclosure, for the natural displacement by a source of buoyancy at floor level, is established ventilation flow driven by a source of buoyancy at within a full-sized enclosure with air as the working floor level within the space with air as the working fluid. This is an extension of previously published fluid. work (Howell and Potts, 1998), where a smaller scale A range of predictive techniques is also enclosure was studied. The current investigation is, investigated for the flow, and for each technique a however, truly representative of the ventilation flows critical comparison with the experimental data is observed in real buildings. presented. It is found that there are differences between It is confirmed that the salt-bath modelling the ventilation flow through the full-scale test room technique and related mathematical model of Linden and that predicted by the simple mathematical et, al. (1990) is not appropriate for the prediction of models for the steady-state case. The causes of the this type of ventilation flow in full-scale buildings. differences are identified and discussed. Computational fluid dynamics is a powerful Computational fluid dynamics is a powerful technique that can yield realistic predictions for this predictive technique that can realistically describe type of ventilation flow. Even this approach, natural ventilation flows within buildings. Even this however, requires further investigation before it can approach, however, requires further investigation to be used routinely. In particular, this paper illustrates ensure that useful predictions are obtained. A major the effect of applying different models of turbulence, problem is the validity of the turbulence models that and highlights the requirement to employ a complete must be employed for ventilation simulations. A thermal radiation model when using the CFD wide variety of flow regimes are observed in many technique to predict this class of flow. buildings, and it is apparent that as yet, no single model of turbulence can accurately describe the INTRODUCTION range of features generally found in room turbulence. Almost half of the total energy consumption in In addition, a simulation should incorporate a model the UK is used in buildings, and this is dominated by to account for the effects of heat transfer due to electricity use for heating, ventilation, air- thermal radiation. conditioning and lighting systems (CIBSE, 1998). Numerical predictions of the ventilation flow Clearly, if more environmentally friendly strategies through the test room have been performed using a could by employed for the design of the building CFD computer code, and are compared with the flow services, such as the provision for ventilation by through the enclosure. A variety of turbulence natural means, then this energy consumption, models are employed for the computer simulations, together with the related emissions of carbon dioxide together with a model for thermal radiation, and the which account for three-quarters of all greenhouse predictions obtained are compared and discussed. gas emissions, could be significantly reduced. The experimental results obtained from the test One of the major barriers to the natural room form a useful set of benchmark data for the ventilation approach is the lack of a reliable design validation of CFD codes that are intended to be used tool for such flows. Linden and his co-workers for the investigation of buoyancy-driven ventilation (University of California, previously at the flows through full-scale enclosures. University of Cambridge) have developed some simple mathematical models for natural displacement EXPERIMENTAL SETUP ventilation of an enclosure over the past decade. This The experimental test-room was representative work has recently been reviewed (Linden, 1999). of a full-sized office space. This was a natural The models are validated using the salt-bath

- 627 - extension to the previous experimental investigation Each resistance thermometer formed one leg of of Howell and Potts (1998). a bridge circuit, and had a resistance of 100Ω. The The test-room was constructed within a large supply voltage to the bridge was maintained at chamber at the University of Newcastle. The 100mV, so that resistive heating of the element was chamber provided two essential features for the insignificant. experimental work. Firstly, the envelope of the The imbalance voltage across the bridge chamber was well sealed, so that any interference due provided a measure of the change in resistance of the to external wind effects was minimised. resistive thermometer element and therefore of Secondly, the physical dimensions of the temperature. The imbalance voltage was monitored chamber were large compared with those of the by a programmable amplifier, with a gain of 1000, test-room, so that the walls of the chamber did not and was then converted to a digital signal, which was affect the ventilation flow through the test-room. subsequently transferred to a PC for further analysis. Indeed, the height of the chamber was about two and The thermometers were calibrated using a a half times that of the test-room, and there was water-bath and a mercury-in-glass thermometer, sufficient room at the end walls of the test-room so which was accurate to within 0.1K. Although the that the flow through the openings was unaffected by platinum temperature-resistance relationship for the the presence of the boundaries of the chamber. thermometer elements was quadratic in nature, for The test-room was assembled from standard the small changes in temperature which occurred 2440x1220mm sheet materials attached to an within the test-room, it was acceptable to assume a aluminium frame. The frame was constructed from linear relationship without introducing significant ‘Dexion’ slotted angle, and sheets of chipboard error. Calibration was performed at two bolted to the frame form the walls, ceiling and floor temperatures, one at each end of the range of of the enclosure. Any gaps at joints between the temperatures expected during the experiments. panels were sealed, so that the test-room was airtight. Assuming a linear variation of temperature with The internal surfaces of the test-room were painted resistance, a third temperature in the middle of the matt white. The floor of the test-room was raised expected range was measured. The range of 100mm above the existing concrete floor of the wind temperatures measured by the thermometers was less tunnel chamber in order to prevent the thermally than one-tenth of a degree Kelvin. massive floor from significantly affecting the airflow within the test-room. SIMULATIONS The end walls were manufactured from Computer simulations of the flow through the polycarbonate sheet, so that the inside of the test-room were performed using the Computational enclosure was visible from outside. It is these walls Fluid Dynamics package Fluent, version 5.4. This is which incorporated the openings to the enclosure. an unstructured code, which allows the engineer The size of each opening could be adjusted by sliding much more freedom in terms of grid density. a polycarbonate panel to the required position, the Fluent 5 employs a collocated grid panel being secured in place by a channel machined arrangement, together with Rhie-Chow interpolation into the structural batten used to keep the (Rhie and Chow, 1983) to prevent non-realistic polycarbonate sheet rigid. oscillations developing in the pressure field as the A 225W plate heater measuring 0.4×0.2m was simulation proceeds. Pressure-velocity coupling was positioned in the centre of the floor to provide the achieved using the SIMPLEC algorithm heat source. (van Doormaal and Raithby, 1984). Measurements of air temperature were The third-order QUICK differencing scheme performed extensively throughout the test-room (Leonard, 1979) was used to evaluate the convection using twelve Platinum resistance thermometers. One terms for the Navier-Stokes equations, the energy of the thermometers was positioned in the inlet equation and the turbulent transport equation, in region to record the temperature of the air entering order to reduce numerical diffusion which is the test-room. The remaining thermometers were generally more significant on an unstructured grid. mounted on a vertical mast, in order to obtain the Linear interpolation was used to determine the face instantaneous vertical temperature profile at any pressures required for the source terms in the particular position. The mast was supported by a discretised Navier-Stokes equations. frame, which itself was supported by rollers engaged The effects of turbulence were modelled in this on guide rails, so that it could be accurately traversed paper using a variety of two-equation turbulence along the x-axis of the test-room. The frame was models. Each model is based upon the eddy viscosity positioned from outside the enclosure by means of a concept and requires additional transport equations to pulley and rope system, and the guide rails had be solved for two new flow variables; the turbulence periodic notches machined into the upper edge for kinetic energy k and the rate of dissipation of accurate and repeatable location of the frame. turbulence kinetic energy ε. The models of

- 628 - turbulence investigated were the standard k-ε model grid. A wall boundary condition with a specified (Launder and Spalding, 1974), the k-ε RNG model constant heat flux was used to model the 225W heat (Yakhot and Orzsag, 1986), and the realisable k-ε source. model (Shih et. al., 1995). Thermal radiation transfer was modelled in this EXPERIMENTAL RESULTS paper using the discrete-ordinates (DO) radiation The experimental results obtained thus far are model (Raithby and Chui, 1990, Chui and Raithby, presented in Figure 3 and Figure 4. The figures show 1993). This particular model solves the governing the average difference in temperature between the radiative transfer equation for a finite number of reference thermometer located in inlet B and each of discrete solid angles, each of which has an associated the thermometers located on the mast for the two fixed vector direction. The radiative transfer equation halves of the room, either side of the plume, is transformed into a transport equation for radiation henceforth designated section A and section B intensity in a particular vector direction, which is (Figure 1). An example of the temperature difference solved using the same solution method that is used along the entire x-axis of the test-room is given in for solving the Navier-Stokes and energy equations. Figure 5. The DO model, however, must solve for as many It is observed that the flow in the test-room is transport equations as there are directions, so that this not precisely symmetrical about the z-axis. This is model can quickly become computationally due to the fact that air entering the room at inlet A is intensive. In addition, the radiation intensity in each consistently about quarter of a degree cooler than air vector direction must be stored at each iteration, so entering at inlet B, due to the imperfect construction that memory and storage requirements are of the surrounding chamber. As a consequence of significantly increased. For the simulations presented this, the plume leans slightly towards the B-end of in this paper, the DO model was solved for 32 vector the test-room. directions. The lack of symmetry can be assessed by Pure gases such as nitrogen and oxygen are comparing the temperature profiles presented in essentially transparent to thermal radiation. The Figure 3 and Figure 4. It is observed that the lack of water vapour in air, however, can absorb and emit symmetry manifests itself mainly at the lowest level radiation, and this should be taken into account when of the test-room, within 0.3m of the floor, and to a modelling radiation transfer. The absorption lesser extent at the highest level, within say 0.4m of coefficient for water vapour in air is taken to be 0.17 the ceiling. For the remainder of the space, however, (ASHRAE, 1977). the temperature field is indeed approximately In the previous study (Howell and Potts, 1998) symmetrical. it was established that the k-ε RNG model of turbulence provided the best predictions of ANALYSIS OF RESULTS temperature stratification for the smaller test-rig. It is Despite the lack of symmetry within the also the view of others (Chen, 1995) that this model test-room, it is observed that the temperature profile of turbulence should be employed for the simulation along sections A and B exhibit the same features. It is of building ventilation flows. The k-ε RNG model is observed that for each combination of opening size, therefore used for the CFD simulations incorporating the temperature profile features a steep temperature the effects of thermal radiation. gradient from floor level up to a height of about 1m. The grid used for the simulations, which Above this height, the temperature gradient is less consisted of approximately 150,000 computational steep. cells, is illustrated in Figure 2. The test-room is The shape of the temperature profile appears to modelled as an enclosure within the larger chamber, be independent of the effective area of the openings obviating the need to apply specific boundary to the test-room. The effective area does, however, conditions in the region of the openings to the room. influence the actual values of temperature difference. Only a quarter of the domain was modelled, with It is observed that as the effective area is reduced, the planes of symmetry defined along the x- and z-axes values of temperature difference increase. This is to of the test-room. In the simulations that employed a be expected, since if the area of the openings is turbulence model, the standard wall-function reduced, the volume flow rate through the test-room approach (Launder and Spalding, 1974) was used to will also reduce. From the first law of model the region adjacent to the walls of the thermodynamics, therefore, the air temperatures test-room and the floor of the chamber. Also, in the within the test-room must increase. simulations including the DO radiation model, the surfaces of the walls of the room were assumed to COMPARISON OF RESULTS WITH have an absorption coefficient of 0.85 (ASHRAE, PREVIOUS WORK 1977). Constant static-pressure boundary conditions From a comparison of Figure 3, Figure 4 and were used to model the remaining boundaries of the Figure 7 it is observed that the nature of the

- 629 - temperature profile in the full-scale test-room is augmented by turbulent diffusion within the space. In different to that in the smaller scale test-rig addition, the differences in the experimental data for previously studied (Howell and Potts, 1998). It is the full-scale test-room and the smaller test-rig thought that this difference is due to the non- suggest that thermal radiation is also a significant reflection of thermal radiation in the experiments mechanism for heat transfer. within the smaller scale test-rig, since all of the walls The salt-bath technique is, therefore, not of the small rig were manufactured from transparent appropriate for modelling the ventilation flow polycarbonate sheet. through the full-scale test-room, or indeed for ventilation flows in buildings in general, where all COMPARISON OF RESULTS WITH THE three mechanisms of thermal transport coexist. MATHEMATICAL MODEL From a comparison of Figure 3, Figure 4 and COMPARISON OF RESULTS WITH CFD Figure 6 it is clear that the mathematical model of SIMULATIONS Linden et. al. (1990) does not realistically describe The CFD predictions for two example the distribution of temperature within the full-scale simulations, with effective area of opening test-room. Whereas the model predicts a sharp A* = 0.18m2 and A* = 0.48m2, are presented in interface between two layers of air of differing Figure 8 and Figure 9 respectively. For each temperature, the experimental results show that no simulation, the effects of thermal radiation have been such interface occurs. neglected. Each prediction illustrates the effect of This difference in temperature profile is due to different turbulence models upon the prediction of the mechanisms for the transport of heat present the temperature stratification within the enclosure. within the test-room. The mathematical model A comparison of the experimental data (Figure neglects both diffusion of heat and thermal radiation, 3 and Figure 4) with the CFD predictions show that so that the only remaining mechanism for heat the CFD technique is an improvement upon the transfer is convection. This is the basis for the mathematical model and salt-bath techniques for the assumption that two layers of air of differing prediction of full-scale ventilation flows. temperatures can co-exist in the same confined space The CFD result for the smaller opening without any diffusion over the sharp interface. (A* = 0.18m2) exhibits a steep temperature gradient Good agreement has been reported between the in the lower portion of the room, with a region where mathematical model and validation studies using the the temperature gradient is less steep above. This is salt-bath technique (Linden et. al., 1990). This is in qualitative agreement with the experimental because the salt-bath technique also neglects the results. The height at which the temperature gradient mechanisms of thermal radiation and diffusion. change, and the overall change in temperature Whilst the kinematic viscosity of water is only between floor level and ceiling level is not in about one-tenth that of air, the diffusivity of salt in agreement with the experimental data. water is less than one ten-thousandth that of heat in The CFD result for the larger opening air (Lane-Serff, 1989). The salt-bath technique is, (A* = 0.48m2) shows a region of constant therefore, only suitable for modelling flows where temperature at low level within the room, with a diffusion of heat is insignificant, since salt diffuses steep temperature gradient above, and a region where too slowly in water to represent the diffusion of heat the temperature gradient is less steep at high level. in air. This is not a particularly good agreement with the Furthermore, a review of experimental work on experimental results. The overall change in differentially heated cavities, it has been reported temperature between floor level and ceiling level is, (Olson et. al., 1990) that significant differences in however, in reasonable agreement with the temperature profile and flow pattern occur, experimental data. depending upon whether the experimental fluid is From Figure 10 and Figure 11 it is clear that the water or a gas. It is suggested that the absence of incorporation of the thermal radiation model can thermal radiation in the water experiments may dramatically improve the CFD predictions with contribute to the differing results. If this is true, then respect to the experimental data. In addition, it is the absence of thermal radiation with the salt-bath apparent that the absorption coefficient of the gas, technique will also affect the predictions to some which effectively depends upon the relative humidity extent. within the space, is crucial to the success of a CFD It is perhaps not surprising, therefore, that the prediction. validation studies using the salt-bath technique and The profile of temperature difference for the the mathematical model are in good agreement. smaller opening (A* = 0.18, Figure 10) with the In the full-scale enclosure, however, diffusion application of the DO-radiation model, and the of heat is a significant mechanisms of heat transfer. absorption coefficient of air set to 0.17 is in excellent Molecular diffusion is important, and this is agreement, both qualitatively and quantitatively, with

- 630 - the experimental data from the full-scale test-room. ACKNOWLEDGEMENTS The prediction manifests a steep temperature gradient This work was sponsored by consulting from floor level up to a height of about 1m, and the engineers Cundall Johnston and Partners, temperature gradient is less steep above this height. Regent Centre, Gosforth, Newcastle upon Tyne, The temperature difference between ceiling level and NE3 3LU, England. floor level is predicted to be about two and a quarter degrees Kelvin, which corresponds to the REFERENCES experimental results. ASHRAE, 1977, "Fundamentals ASHRAE The profile of temperature difference for the Handbook", (Atlanta, GA: American Society of larger opening (A* = 0.48, Figure 11) with the Heating, Refrigeration and Air Conditioning DO-radiation model, and the absorption coefficient Engineers) of air set to 0.17 is also in good agreement with the Chen, Q., 1995, "Comparison of different k-ε experimental data. It shows a steep temperature models for indoor air flow computations", Numer. gradient in the lower region of the room, with a less Heat Transfer, B28:353-369 steep temperature gradient in the higher region. The Chui, E. H., and Raithby, G. D., 1993, temperature difference between ceiling and floor "Computation of radiant heat transfer on a non- levels is predicted to be about two degrees Kelvin, orthogonal mesh using the finite-volume method", which again corresponds to the experimental results. Numer. Heat Transfer, B23:269-288 CIBSE, 1998, "Energy efficiency in buildings CONCLUSIONS CIBSE Guide", (London: Chartered Institution of In this paper extensive measurements providing Building Services Engineers) information regarding temperature profile within a Howell, S. A., and Potts, I., 1998, "A full-scale test-room are presented for the case of a comparison of predictive techniques for natural natural displacement ventilation flow driven by a displacement ventilation of buildings", Proc. CIBSE source of buoyancy at floor level within the room. Nat. Conf.:156-164 The nature of the temperature stratification within the Lane Serff, G. F., 1989, "Heat flow and air full-scale room differs from that measured in a movement in buildings", Ph.D. thesis, Cambridge smaller-scale test-rig. The cause of the difference is Univ., UK thought to be the non-reflection of thermal radiation Launder, B. E., and Spalding, D. B., 1974, "The at the wall boundaries in the small-scale experiment. numerical computation of turbulent flows", Comput. The experimental data presented has been used Methods Appl. Mech. Eng. 3:269-289 to assess a range of alternative prediction techniques Leonard, B. P., 1979, "A stable and accurate for this type of flow. It is apparent that the salt-bath convective modelling procedure based on quadratic technique and the associated mathematical model of upstream interpolation", Comput. Methods Appl. Linden et. al. (1990) are not appropriate for the Mech. Eng. 19:59-98 prediction of this class of flow. The predictions Linden, P. F., 1999, "The fluid mechanics of obtained from these techniques do not realistically natural ventilation", Annu. Rev. Fluid Mech. describe the distribution of temperature within the 31:201-238 full-scale test-room. This is because both predictive Linden, P. F., Lane Serff, G. F., and Smeed, D. techniques neglect thermal radiation and diffusion as A., 1990, "Emptying filling boxes: the fluid mechanisms for thermal transport. For the flow mechanics of natural ventilation", J. Fluid Mech. through the test-room, however, thermal radiation 212:309-335 and diffusion are thought to significantly affect the Olson, D.A., Glicksman, L. R., and Ferm, H. temperature stratification within the space. M., 1990, "Steady-state natural convection in empty Computational fluid dynamics remains as a and partitioned enclosures at high Rayleigh powerful technique for the prediction of the class of numbers", ASME J. Heat Transfer 112:640-647 flow considered in this paper - natural displacement Raithby, G. D., and Chui, E. H., 1990, " A ventilation flows through enclosures. The CFD finite-volume method for predicting a radiant heat predictions must be performed, however, with the transfer in enclosures with participating media", application of suitable models for both turbulence ASME J. Heat Transfer 112:415-423 and thermal radiation effects. In addition, the Rhie, C. M., and Chow, W. L., 1983, absorption characteristics of air, due to concentration "Numerical study of the turbulent flow past an airfoil of water vapour in the atmosphere, must be properly with trailing edge separation", AIAA Journal assessed and included as part of the simulation if a 21(11):1525-1532 realistic prediction is to be generated. Shih, T. H., Liou, W. W., Shabbir, A., and Zhu, J., 1995, "A new k-ε eddy-viscosity model for high Reynolds number turbulent flows - model

- 631 - development and validation", Comput. Fluids NOMENCLATURE 24(3):227-238 A* = effective area of the openings to the Van Doormaal, J. P., and Raithby, G. D., 1984 enclosure. From Linden et. al. (1990) "Enhancements of the SIMPLE method for   predicting incompressible fluid flows", Numer. Heat  A A  A* = i o 2 , Transfer, 7:147-163    A2 + A2  Yakhot, V., and Orzsag, S. A., 1986, "  i o 

Renormalization group analysis of turbulence: I. where Ai and Ao are the areas of the low-level basic theory", J. Sci. Comp. 1:1-51 opening and high-level opening respectively.

FIGURES

B

y z x

Section B

A Section A

Figure 1 - Experimental test-room and associated co-ordinate system

Figure 2 - Computational grid used for CFD simulations

Figure 3 - Temperature profiles within the test-room for section A

- 632 - Figure 4 - Temperature profiles within the test-room for section B

Figure 5 - Plot of temperature difference along the x-axis of the test-room for an effective area A* = 0.18

Figure 6 - Temperature profiles predicted by the mathematical model of Linden et. al. (1990)

Figure 7 - Temperature profiles within the small scale test-rig (Howell and Potts, 1998)

- 633 - Figure 8 - Temperature profiles predicted by CFD simulation, using a variety of turbulence models, for an effective area of opening A* = 0.18

Figure 9 - Temperature profiles predicted by CFD simulation, using a variety of turbulence models, for an effective area of opening A* = 0.48

Figure 10 - Temperature profiles predicted by CFD simulation, using the k-e RNG turbulence model together with the discrete-ordinates radiation model, for an effective area of opening A* = 0.18

Figure 11 - Temperature profiles predicted by CFD simulation, using the k-e RNG turbulence model together with the discrete-ordinates radiation model, for an effective area of opening A* = 0.48

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