SBO project IWT Tweede jaarlijks rapport

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1 Faculteit Toegepaste Wetenschappen Departement Burgerlijke Bouwkunde Laboratorium Bouwfysica Kasteelpark Arenberg 40, 3001 Heverlee Universiteit Gent Vakgroep Mechanica van Stroming, Warmte en Verbranding Sint-Pietersnieuwstraat 41, 9000 Gent Universiteit Gent Vakgroep Architectuur en Stedenbouw Plateaustraat 22, 9000 Gent Technische Universiteit Eindhoven Unit Building Physics & Systems P.O. Box 513, 5600 Eindhoven Wetenschappelijk en Technisch Centrum voor het Bouwbedrijf Departement Geotechniek en Structuren Departement Bouwfysica en Uitrustingen Poincarélaan 79, 1060 Brussel Physibel Heirweg 21, 9990 Maldegem Daidalos Bouwfysisch Ingenieursbureau Oudebaan 391, 3000 Leuven Ingenieursbureau Stockman nv Muinklaan 6, 9000 Gent Heat, air and moisture performance engineering A whole building approach SBO project IWT Tweede jaarlijks rapport Staf ROELS, Erik DICK, Michel DE PAEPE, Arnold JANSSENS, Peter WOUTERS, Benoit PARMENTIER, Jan HENSEN, Bert BLOCKEN, Piet HOUTHUYS, Filip DESCAMPS, Piet DELAGAYE, Demir-Ali KÖSE, Kim GOETHALS, Marnix VAN BELLEGHEM, Mohammad MIRSADEGHI, Daniel COSTOLA, Tadiwos ZERIHUN DESTA, Thijs DEFRAEYE (verslag). September 2008

2 Inhoud Inhoud Wetenschappelijk- technisch verslag Overzicht van uitgevoerde activiteiten... 3 WP1.1 Wind pressure distribution... 4 WP1.2 Driving rain load distribution WP2.1 Development of HAM model WP2.2 Experimental analysis on building enclosures WP3.1 Convective heat exchange and summer comfort WP3.2 Development of CFD-HAM model WP4 Towards an integrated approach WP5.1 Strategic and integrated planning of research activities WP5.2 Strategic implementation of testing and simulation facilities References Bijsturingen in het project Beheer van het project Haalbaarheid van het project Te beschermen resultaten Utilisatieverslag Valorisatiepotentieel: geactualiseerde visie Overzicht van de uitgevoerde valorisatieacties Bescherming projectresultaten Financieel verslag Prestatietabel Prognose voor komende projectjaar Financiële verantwoording Overzicht Wetenschappelijk technisch Valorisatie... 87

3 1 Wetenschappelijk- technisch verslag 1.1 Overzicht van uitgevoerde activiteiten Het onderzoekswerk is georganiseerd in vijf werkpakketten, welke op hun beurt nog verder onderverdeeld zijn: WP1 Outside boundary conditions WP1.1 Wind pressure distribution WP1.2 Driving rain load distribution WP2 Building envelope WP2.1 Development of HAM model WP2.2 Experimental analysis on building enclosures WP3 Building interior WP3.1 Convective heat exchange and summer comfort WP3.2 Development of CFD-HAM model WP4 Towards an integrated approach WP4.1 Development of a prototype software environment WP4.2 Development of a coupling necessity decision procedure WP4.3 Experimental validation WP5 Establishment of a knowledge platform WP5.1 Strategic and integrated planning of research activities WP5.2 Strategic implementation of testing and simulation facilities Dit verslag beschrijft de onderzoeksactiviteiten van het tweede projectjaar lopende van 1 september 2007 tot 1 september Dit deel van het verslag is opgemaakt in het Engels omdat dit de voertaal is voor publicaties en wetenschappelijke rapporten en een aantal onderzoekers Nederlands niet als moedertaal hebben. Tweede jaarlijks rapport 3

4 WP1.1 Wind pressure distribution Objectives WP1.1 emphasises the distribution of pressure differences across the building envelope due to wind flow. This subtask is subdivided in two parts: WP1.1.1 Some sets of full-scale measurements will be recorded regarding the wind pressure distribution on the building envelope of the building WINDHouse of the Laboratory Structures of BBRI, located in Limelette. The data will be used to asses the numerical predictions with CFD (Computational Fluid Dynamics). WP1.1.2 Numerical simulations of the air flow around a building will be performed. Different hybrid RANS-LES models to describe the turbulence are tested. The calculations will provide, among other numerical results, the pressure distributions at various locations on the building surface. The obtained data will be compared with the experimental pressure data sets provided by WP Description of work WP1.1.1 Experimental analysis of wind pressure distribution over a building envelope The activities of BBRI-SC during this second year focused on: The setup of a new measuring system (masts, sonic anemometers, ) The complete filtering and adaptation of the existing database of pressure measurements on the WINDHouse building for the purpose of this research and in particular for possible comparisons with numerical models developed in WP The reference building used to define outside boundary conditions is a small house with the dimensions 5x10 m with a roof slope of 30 and a ridge height of 5.2 m. This building was described in a more detailed way in Parmentier (2002). A meteorological mast is installed 30 m upstream of the house in the direction of the prevailing winds. The initial database provided about 600 records of pressure measurements. After filtering of local problems and the check of the self-stationarity of the records (see further), the database consists now of 336 clean records ( runs ) of 15 minutes each. The data collected are: Pressures on the roof of the building (48 tap locations). Wind speed at 12 m height upstream of the building. Wind speed at 5 m height upstream of the building. Wind direction. The sampling rate of the 51 channels was 20 Hz. All the data were collected by using 5 synchronised data loggers connected to a PC. A dedicated programme was written in VB to pilot the recording phases, the automatic calibration of the pressure transducers and the automatic rotation of the building. The data (18000 for each channel during a complete run) were checked for self-stationarity of the wind speed and wind direction. By using the rotation of the building, the influence of almost all angles of attack (AOA) has been studied (Figure 2). Tweede jaarlijks rapport 4

5 Figure 1: The WINDHouse building in Limelette. 20 Angle of Attack vs. Wind speed Wind speed [m/s] AOA [ ] Figure 2: AOA vs. Average wind speed (15 ) on the WINDHouse. The output format of the records was binary to save computer memory. Different Matlab routines have been developed in order to read the data and analyse it by different ways with a user-friendly interface (see Figure 3 and Figure 4). Tweede jaarlijks rapport 5

6 Time-history domain Frequency domain Spatial domain (external pressure coefficients, roof) Figure 3: Analysis of the full-scale measurements on the WINDHouse. Tweede jaarlijks rapport 6

7 Figure 4: Matlab routines developed for visualisation/analysis of the data sets. For each run, pressure results can be expressed as pressure coefficients (differential pressure divided by the dynamic pressure): Pe P CPe = 0,5. ρ. V 0 2 where P e is the external pressure [Pa], P 0 is the reference static pressure (in a ground box near the meteorological mast) [Pa], ρ is the air density (1.226) [kg/m³] and V is the wind speed at the ridge of the roof [m/s]. As already reported, there is a clear dependence of the wind direction on the longitudinal turbulence intensity (Iu). This is illustrated in Figure 5. While the roughness category of the Limelette site can be estimated in the range of 30% (category II according to the NBN EN ), the local influence of a group of trees in the North [180 ] is evident. These trees were simulated during some tests in a wind tunnel but some blockage effects occurred Iu [%] Wind direction [ ] Figure 5: Wind direction vs. longitudinal turbulence intensity (I u ) - U>5m/s. Tweede jaarlijks rapport 7

8 Figure 6: North view from the WINDHouse building. As reported in the first annual report, some discrepancies have been noticed between fullscale (F-S) and model-scale (M-S) measurements. Having this considered, it has been decided to install three additional meteorological masts around the building with specific anemometers in order to get a detailed evaluation of the turbulence intensities of the incoming wind flow around the building. The location of these new masts was determined according to the precision needed by the numerical simulation and to be able to identify the influence of the flow pattern on the windward and leeward pressures. The masts are lattice structures having 10 m height. These masts are now equipped with sonic and 3-cups anemometers. The locations of the masts are illustrated on Figure 7. As it can been seen on this figure, 2 masts are located just near the first existing (original) mast to obtain a spatial grid analysis of the wind flow upstream of the building. A last mast is located downstream, at around 20 m of the WINDHouse building. Figure 7: Location of the new meteorological masts around the WINDHouse building in Limelette at BBRI. Tweede jaarlijks rapport 8

9 The sensibility to the vibrations of the masts on the measurements has been studied and could be neglected. Hence, in order to evaluate the wind flow with more accuracy, sonic anemometers (SAT) were considered besides 3-cup anemometers (that were used in the past). The main characteristics of SAT s, cups and propellers are given in Figure 8. Figure 8: Main characteristics of SAT s, cups and propellers (Cuerva, Sanz-Andres et al. 2006). Importance of Sonic anemometry in Wind Engineering The calculation of the atmospheric parameters affecting the performance of structures in the atmospheric flow requires knowledge on the wind speed vector with large time resolution. SAT (see different models in Figure 9) is the most extensively used sensor for this purpose, mainly in places where the turbulent flow is highly 3D, as it occurs in natural complex terrain or in the built environment. SAT s measure the wind speed in a small volume approaching a single point by detecting the influence of the wind speed field in the transmission of ultrasound pulses along one or more acoustic paths configured by at least one pair of transmitter-receiver transducers (Cuerva and Sanz-Andres 2000). SAT s present different advantages compared to other types of anemometers (cup, propellers and hot wire). Dynamic effects can be neglected because they do not have any mobile parts. On the other hand, they can measure the 3D wind structure, whereas cups can not and their time resolution is much higher. Although hot wire anemometers can be sampled at high rates (in the order of 10 khz), their fragility and their need to keep the wire free of deposit and dust prevents its utilisation in outdoor conditions. But what is important for the activities of WP1.1.1 is the fact that the starting threshold and response time of sonic anemometers, for both wind speed and direction, are close to zero (Sturgeon 2005). It means that these SAT s are very accurate even at very low wind speeds. Hence, applications related to the ventilation and building envelope can be analysed with a high degree of confidence based on the outside boundary conditions measured by the SAT s. Finally, maintenance of SAT s is much simpler compared to other anemometers. In general, all SAT s are calibrated in a wind tunnel. Sonic anemometers are in principle independent of the atmospheric conditions. A misalignment of the anemometer (inclination) can provide a drift of the measurements and some errors in the measurements are also caused by turbulence along the arms (wake) of the transducer for high wind speeds (>60m/s). These different parameters were recently investigated in the framework of the project ACCUWIND (Cuerva et al. 2006) and reviewed by different authors (Sturgeon 2005, Wauben 2005). The influence of temperature, icing, air density, relative humidity or turbulence was analysed by using a reference anemometer and different other anemometers (3-cup and sonic) for Tweede jaarlijks rapport 9

10 comparison. The conclusion was that this influence could be neglected, within the activity range of our project. Finally, the comparison between 3-cup anemometers and sonic was excellent, above a specific value of the wind speed. Figure 9: Different models of Sonic anemometers (Cuerva, Sanz-Andres et al. 2006). After an analysis and a comparison of the materials available, 2 WindMaster Pro Ultrasonic anemometers from Gill Instruments Ltd were bought (Figure 10). According to the supplier (Gill Instruments 2007), the resolution is < 0,01m/s and the accuracy if lower than 1,5% RMS. A check of the whole measuring and DAQ system was performed in the laboratory (see Figure 11). Figure 10: WindMaster Pro Ultrasonic Anemometer (Gill Ltd) and sonic theory. Tweede jaarlijks rapport 10

11 Figure 11: Check of the installation of the sonic and 3-cup anemometers at BBRI. Additional 3-cup anemometers were also bought to obtain information on the wind speed along the altitude around the building. Future activities From a technical point of view, the first database of measurements on the WINDHouse building is ready to be used. A specific interface was developed to compare more easily with numerical simulation results. During the next months, a close cooperation with the team dealing with WP will be organised. Based on the comparison with specific runs, it should be possible to define a reference for calibration of the simulation models. Moreover, new measurements will be performed on the facades on the WINDHouse building, together with measurements of the wind structure with the new measurements grid and in particular with the above mentioned sonic anemometers. It is expected that a complementary set of records will be available in April VRT building (Daidalos) It was decided to include also the measurement results from the VRT building (performed by Daidalos) in the analysis of this workpackage. The data can be used as a realistic test case for numerical simulations. The measurement campaign involves a large building where detailed wind speed measurements are performed close to the façade, simultaneously at 6 points. These measuring locations are changed frequently during the measurement period and also a wind mast on the roof top is used as a reference. WP1.1.2 Development of a hybrid RANS-LES technique of flow over buildings From a computational point of view it is not feasible to perform Large Eddy Simulations (LES) of flow around buildings (LES = resolving the large turbulence structures in the flow and modelling the small structures). A very fine mesh near the building walls is required to accurately resolve the flow. This leads to very large computational costs. At the other hand, simulations with Reynolds Averaged Navier-Stokes equations result in very poor predictions of the flow field over a building (RANS = modelling all the turbulence structures). That is the main reason for the development of hybrid models. In such a model an unsteady Reynolds Averaged Navier-Stokes (RANS) model is used in the near-wall regions, while far from the wall a sub-grid scale (SGS) model is used within a LES-formulation. In this way the best Tweede jaarlijks rapport 11

12 qualities of RANS and LES are combined in one model. The use of a RANS model in the near-wall regions allows using much coarser meshes in those regions and this saves computational time. Obtained results During the second project year, many hybrid models have been investigated, including the more-or-less standard Detached Eddy Simulation (DES) model of Spalart et al., the k-l model of Davidson, and the k-l model of Tucker and the hybrid model developed by our own research group (C. De Langhe): ε-l model. Since only the DES model is implemented in Fluent, the other models needed to be programmed. This has been done by writing User Defined Functions (UDF). In the first project year, we tested the DES of Spalart, the k-l of Davidson and the ε-l model on flow over a periodic part of a square section of a tower building. In the second project year, we found that this test case is extremely delicate. To obtain good results, very fine grids are necessary. This is due to the extreme large scale time-dependency of the flow caused by large-scale vortices. Therefore, the test case was changed to a cube on a flat plate. There is one well-known test case documented in the literature. The test case is more representative for a building of limited height, and is therefore more appropriate for the project. This case is less sensitive because the boundary layer stabilizes the flow, so that the flow is less timedependent. Very coarse grids were tested, as typically used in RANS-simulations: to cells. Velocity profiles are available for a number of stations on the cube and in the wake of the cube. The pressure distribution is available on the flat plate around the cube, but not on the cube itself. RANS-simulations. RANS-simulations were tested in steady flow, as most often used in practice for determination of the flow field around a building. Basic RANS-models lead to bad results, but there are possibilities to ameliorate the performance of RANS-models. Two ameliorations suggested in the literature were investigated. The first amelioration is to introduce the wall shear stress as boundary condition at walls, instead of a zero velocity boundary condition. This is a typical practice in high-reynolds formulations, where the grid in wall vicinity is very coarse. Proposals exist for a blended calculation of the wall shear stress such that simulations are possible for grids that are rather fine in wall vicinity. We need this possibility, as it cannot be hoped that good results can be obtained with extremely coarse grids. Several proposals in the literature were investigated and an own variant was developed. The second amelioration consists of bringing in a model for the source term in the equation for turbulent kinetic energy, instead of calculating the source term directly, which becomes quite inaccurate on coarse grids. This is also a practice used with the high-reynolds form of RANS-models, where the grid in wall vicinity is coarse. Here, proposals of blended formulations of such a term were investigated, so that the model can be used on fine grids and as well on coarse grids. Again, we developed an own variant. The ameliorations result in an improvement of the velocity prediction in the vicinity of the cube. The prediction of the flow in the wake of the cube remains bad. The prediction of the pressure distribution on the flat plate in the vicinity of the cube is very good. This good pressure distribution on the plate is, of coarse, not a guarantee for a good pressure distribution on the cube itself, but a reasonable conclusion is that the pressure distribution on the cube cannot be very bad, since the velocity distribution in the vicinity of the cube is quite good, although not perfect. Hybrid RANS/LES-simulations. Hybrid simulations result in a very good prediction of the velocity field in the vicinity of the cube and a good prediction of the velocity field in the wake Tweede jaarlijks rapport 12

13 of the cube. The blended formulations of the wall shear stress (WSS) and production term (PK) in the RANS-part of the simulation contribute also to the quality of the predictions. However, the major difference between a steady flow RANS simulation and an unsteady flow hybrid RANS/LES simulation is caused by taking into account the unsteadiness of the flow. In the formulations that we tested, unsteadiness comes in through length scale limitation in the modelled turbulence away from walls. In this sense, the simulations can also be called unsteady RANS simulations. The RANS model is not changed for use in the LES zones, but by limitation of the length scale. The pressure distribution on the plate around the cube is less good with the hybrid simulations than with the RANS simulations. This observation is very confusing. Our expectation is that the pressure distribution on the cube is better with a hybrid simulation since the velocity field in the vicinity of the cube is much better, but this conjecture cannot be verified with the data of the test case. LES-simulations. The available LES models in FLUENT were tested: the constant coefficient Smagorinsky model and the dynamic coefficient k-model. The results of the LES simulations on the coarse grids that are used, are not really bad. The predicted velocity profiles in the vicinity of the cube are not bad, but not as good as with the hybrid simulations. The predicted velocity profiles in the wake are very good. The pressure distribution on the plate is not good. Moreover, on the coarse grid that was used, the results are not very sensitive to the particular LES subgrid model. Without any model, the results are not significantly different. This means that the results are very much polluted by numerical dissipation. The grids that are tested are thus much too coarse for a reliable LES simulation. So, this observation is a very strong argument for the use of hybrid RANS/LES simulations. Furthermore, the results obtained with LES prove that taking into account the flow unsteadiness is vital for good predictions. Practical conclusion on hybrid RANS/LES simulation. From the study in the second year, the conclusion definitely is that only hybrid RANS/LES is a practical method for simulation of the flow around a building, using rather coarse grids. From our study is concluded that the most practical way to come to a hybrid simulation is to use a RANS model as subgrid model in the LES part by limiting the length scale according to the grid size. Terms currently coming into use for such an approach are URANS (unsteady RANS) or seamless hybrid RANS/LES. An older term is DES (detached eddy simulation). DES is associated most often to the Spalart-DES approach, but can also be seen as general approach to switch to LES in detached flow zones starting from any turbulence model by changing the length scale of the model. It is also found that ameliorations in the RANS-part concerning the wall shear stress boundary condition (WSS) and the production term of the turbulent kinetic energy (PK) improve the quality of the simulations. Note that WSS and PK ameliorations are already implemented in FLUENT in the enhanced wall functions option. These ameliorations are not identical to the ameliorations that are developed in this workpackage, but the precise formulation is not critical. Therefore, the DES-SST model in FLUENT was tested together with the enhanced wall functions option. The basis of the model is the SST-k-ω model, which is known to be one of the best RANS turbulence models. The DES-hybridisation means that the length scale is limited by the grid size, when this one becomes smaller than length scale predicted by the model. The conclusion is that the DES- SST simulation leads to results that are comparable to the results obtained with our own hybrid variants. So, for use by other partners in the project, DES-SST with enhanced wall functions is recommended. Tweede jaarlijks rapport 13

14 Example The cell distribution around the cube for the coarse mesh is shown in Figure 12. Figure 12: Cell distribution for the coarse mesh used in the simulations. In Figure 13, the effect of the modifications on the RANS predictions is shown. Red lines represent the standard k ε model, the blue lines the same model but with WSS and PK ameliorations. Figure 13: Comparison of RANS (red lines) and RANS + WSS + P k (blue lines) with experiments at 2 locations in the symmetry plane. Pressure profiles on the channel base plate are given in Figure 14. Left is the standard k ε model, right is the same model with WSS + PK amelioration. Tweede jaarlijks rapport 14

15 Figure 14: C p profiles on the channel base plate with RANS. The empty circles represent experimental data at X/H = -0.06, the empty squares those at X/H = 0.5, the black triangles those at X/H = 1.06 and the empty diamonds those at X/H = The respective colored symbols are the simulation results. The DES SST simulation results are presented in Figure 15. The red lines represent the hybrid model with WSS + PK amelioration as in FLUENT while the blue lines represent the results with our own method for WSS +PK. Figure 15: Comparison of DES-SST with ameliorations as in FLUENT(red lines) and with own modifications (blue lines) with experiments. Finally, in Figure 16, the pressure distributions for both models are presented. Tweede jaarlijks rapport 15

16 Figure 16: Pressure distributions for the DES-SST model. Left: with ameliorations as in FLUENT, right with own modifications. Deliverables WP1.1.1 The test setup for the WINDHouse is operational. The complete filtering and adaptation of the existing database of pressure measurements on the WINDHouse building is performed. WP1.1.2 Several hybrid techniques were evaluated. Some were available in the software while others were implemented by the researcher. Out of this extensive study, the most accurate technique was identified. Planning WP1.1.1 A measurement campaign will start for the WINDHouse. A measurement campaign on the VRT building is planned WP1.1.2 Test data for flow over a cubic building of 6 m x 6m x 6 m is found in literature. The pressure distribution is available on two cuts of the cube: with the vertical symmetry plane in flow direction and with a horizontal plane. These data will be used for further validation of the obtained results with the aim to come to a final conclusion on the use of hybrid methods for analysis of flow over a building. The WINDHouse of the BBRI will be simulated using the data as available from the BBRI. The VRT-building will be simulated and results will be compared to the data from the measurement campaign of Daidalos. Tweede jaarlijks rapport 16

17 WP1.2 Driving rain load distribution Objectives WP Laboratory and in situ experiments of contact phenomena of driving rain impinging on different building materials. The final amount of water that may enter the building enclosure (the boundary conditions for the building envelope model) will be determined by splashing effects, adhesion, evaporation, run-off and capillary absorption. All these phenomena strongly depend on the material properties of the building enclosure. Parameters are porosity of the material, moisture capacity, capillary activity,. WP Development of a water uptake and run-off model for building materials. Numerically, the transformation of individual rain drops, absorbed by the building material towards a smeared wetting as assumed in building envelope models, will be investigated. In addition, starting from the work of Kondic (2001) a run-off model for rain water run-off on capillary active materials will be developed. (Blocken et al. 2003) developed a simple preliminary model, combining a model for capillary absorption and for rain water run-off using the thin film theory. This model however showed to be very time consuming due to the time scale difference between the development of a film and the capillary absorption. The research of the previous two sections of this subtask (WP and WP1.2.2) was conducted in strong collaboration with a PhD student working on a KUL OT-project where the contact phenomena (bouncing, splashing and spreading) and surface phenomena (absorption, evaporation and run-off) are also of interest. Out of this research it has become clear that the outside boundary conditions, namely convection and radiation, have a large impact on the evaporation at building facades wetted by wind-driven rain. Therefore the focus of the PhD student that is involved in this SBO project (PhD1) will be mainly on these topics and an additional subtask (WP1.2.3) has been introduced below. WP Numerical and experimental analysis of convective heat and mass transfer at exterior building surfaces. More accurate predictions of the convective transfer coefficients are obtained, considering the influence of wind speed, wind direction and building surroundings and spatial distribution across the surface. Also the influence of specific materials and surface texture is investigated. Description of work WP Laboratory and in situ experiments of contact phenomena of driving rain impinging on different building materials. As mentioned in the previous report, a laboratory set-up was used to study contact phenomena of raindrops impinging on a building material. With this set-up, raindrops of different sizes were released from a certain height until they reached terminal velocity after which they impinge on the building material. As the raindrop trajectory was captured by a high-speed camera, the different types of contact phenomena could be distinguished, namely bouncing, splashing and spreading (Figure 17). The data obtained with this measurement setup were processed in detail (Figure 18), which led to more insight regarding influence of impact angle, impact speed and droplet diameter on the spreading length and width of a single droplet. Tweede jaarlijks rapport 17

18 Figure 17: Photos of wetted areas on ceramic material surface: (a) Spreading: d = 2.0 mm, v = 6.8 ms -1, θ = 90.0 ; (b) Bouncing: d = 2.0 mm, v = 6.8 ms -1, θ = 24.5 ; (c) Bouncing: d = 3.9 mm, v = 7.5 ms -1, θ = 90.0 ; (d) Splashing: d = 3.9 mm, v = 7.5 ms -1, θ = 15.0 (d = droplet diameter, v = impact speed, θ = impact angle). Figure 18: Dimensionless maximum spreading length L s (a) and spreading width W s (b) versus impact angle θ (d = drop diameter (mm), v = impact speed (ms -1 )). Each symbol represents data of a single drop. 3 drops bounced and 6 drops splashed, whereas all other drops spread. An experimental setup (Figure 19) for field measurements of wind-driven rain loads and the response of walls was developed at the VLIET building for validation purposes (see previous report). Measurements of near-wall wind speed and direction, WDR intensity, material weight and temperature are possible. Detailed measurement campaigns were performed last year, capturing several rain events. Thereby large datasets are provided (Figure 20) which can be used for validation of numerical simulations. Tweede jaarlijks rapport 18

19 (a) (b) outdoor indoor WDR gauge B thermocouples in the box WDR gauge B fulcrum m 2 decimal balance WDR gauge A contactless roller measured specimen (only this side is open) cylinder pressure gauge subsection A subsection C subsection B subsection D X Figure 19: Test setup at VLIET building for WDR measurements SWDR 5 SWDR, wmea (g) SWDR I WDR wmea IWDR (mm/h) SWDR, wmea (g) wmea I WDR I WDR (mm/h) Figure 20: Measurement results during two rain events (W mea : weight change of the specimen, S WDR,mea : cumulative amount, I WDR,mea : intensity of wind-driven rain). WP Development of a water uptake and run-off model for building materials. The simple run-off model that was implemented in HAMFEM, which is an in-house HAM modelling tool developed by the Laboratory of Building Physics at the K.U.Leuven, was extended. Now the model includes the effects of evaporation and absorption by the material on the run-off progression which results in more realistic modelling of this phenomenon (simulation example: Figure 21). Tweede jaarlijks rapport 19

20 12.8 cm 5.08 cm position (y-coordinate) [m] s 10 s 15 s 23 s side A side B thickness of the water film [mm] Figure 21: Numerical simulation with run-off model. WP1.2.3 Laboratory experiments and numerical modelling of the influence of outside boundary conditions on the heat and mass transfer at building façades wetted by wind-driven rain. As mentioned before, the effect of the outside boundary conditions, such as convection and radiation, was found to be of significant importance in the assessment of the response of building walls after a rain event for simulations such as described in WP Therefore, WP1.2.3 was created. In a first stadium, only convective heat and mass transfer was considered and only forced convection was taken into account. A numerical study with CFD was carried out to asses the convective heat transfer on a 10 m high, cubic building placed in an atmospheric boundary layer. The RANS approach was used to model turbulence. In order to resolve the boundary layer, the commonly used wallfunction modelling technique was compared with the low-reynolds number modelling approach. The latter however requires a very high grid resolution in the boundary-layer region. First, the used numerical techniques were validated with experimental data for flow over a heated cube placed in a turbulent boundary layer at low Reynolds numbers. Fairly good predictions of the CHTC could be obtained for windward and leeward facades with the low- Reynolds number modelling approach. From the results, it is suggested that the conventional wall-function modelling technique should not be used to predict the CHTC. Wall functions are found to model the inner part of the boundary layer not accurate enough. The prediction of heat transfer in this region is however found to have a large impact on the CHTC. Therefore the influence of roughness can also have a significant influence on the CHTC and simulations will be performed to clarify this. For the cubic building, the CHTC was correlated with the mean wind speed at a height of 10 m above the ground but, in contrast to previously used correlations, the spatial distribution across the façade was also taken into account by which correlations on each location on the building façade could be obtained (Figure 22). Moreover, the sensitivity of the convective heat transfer coefficient to the approach flow profile, wind direction and thermal boundary conditions was investigated. Tweede jaarlijks rapport 20

21 Figure 22: Distribution of the correlation of the CHTC (power law with coefficients C and B) with the wind speed (U 10 ) over the windward façade of a cubic building. An experimental setup was built, namely a small atmospheric boundary-layer wind tunnel with a test section of 0.5x0.5m² and a wind speed range from 1-12 m/s. It will be used to validate the numerical techniques for the previous problem at higher Reynolds numbers. It will also be used for the study of other problems, such as the effect of shelter of surrounding buildings on the CHTC distribution. Both temperature and velocity measurements will be performed. A study of the effect of convection on combined heat and mass transfer in porous materials was also within the scope of this workpackage. Solving mass transfer in porous materials (which involves both liquid and vapour transport) is not possible with the CFD software that is used. Therefore the CFD code is coupled (explicitly) with HAMFEM (Figure 23). The air flow is entirely resolved within the CFD package whereas the heat and mass transport in the porous material is resolved within HAMFEM. Preliminary validation simulations have been carried out in order to validate the coupled program. More extensive validation and verification is planned. Moreover, the program will be further developed in order to study more complicated geometries. Tweede jaarlijks rapport 21

22 Figure 23: Coupling procedure of CFD program with HAMFEM. Deliverables WP1.2.1 The experimental setup for field measurements regarding wind-driven rain loads at the VLIET building was used to gather detailed datasets for several rain events. WP1.2.2 A more extensive run-off model is developed which takes into account the effect of evaporation and absorption on the run-off process. WP1.2.3 Validation of the numerical methods was performed. A study of the CHTC on building surfaces was conducted by which more detailed information regarding the wind direction and the relation with the wind speed was provided. An experimental setup has been constructed for CFD validation and for analysing the influence of different parameters on the CHTC distribution on facades at high Reynolds numbers. Planning WP1.2.1 The experimental setup will be used to obtain more datasets during rain events. WP1.2.2 No further actions are planned for the coming year. WP1.2.3 Wind-tunnel tests are planned regarding the CHTC on building surfaces The coupled CFD-HAM model will be further verified and validated. Numerical simulations considering the effect of micro roughness on heat and mass transport are planned. Tweede jaarlijks rapport 22

23 WP2.1 Development of HAM model Objectives The aim of this subtask is to develop a comprehensive building envelope model for the coupled analysis of heat, air and moisture transport through building enclosures. The model will be based on existing scientific models available from the partners. Because of the different time-scales between heat, moisture and air transport, and the associated numerical obstacles, a stabilised solution method could not be achieved when dealing with air transport. Therefore the main objective of this subtask is to tackle this problem. Description of work The researcher is studying different numerical modelling techniques and gathered information and knowledge on existing HAM-models with a particular emphasis on the HAM-modelling program HAMFEM, developed at the KULeuven. There is a need to incorporate air transport in the heat and moisture transfer model. In order to attain more insight in the complexity of HAM-modelling and to overcome the difficulties in numerically solving the combined HAMproblems further research need to be conducted. Deliverables Due to the fact that the initial researcher left the project and a new researcher started only some months later, there are no deliverables at this stage of the research Planning Some possible numerical techniques will be checked in a simplified MATLAB code. Afterwards based on the results, the most optimal method will be implemented into HAMFEM. A review paper will be prepared about the existing HAM modelling techniques. The experimental setup at the VLIET building (WP2.2) will be simulated with HAMFEM (without air component) and comparison will be made with the available measurement data in order to evaluate the effect and importance of airflows and/or air leakage through the building wall. In a later stage of the project the upgraded version of HAMFEM will be used to fully simulate heat, air and moisture transfer in building components. Tweede jaarlijks rapport 23

24 WP2.2 Experimental analysis on building enclosures Objectives This subtask focuses on the analysis of HAM transport through building enclosures based on measurement data. It was decided to limit the experimental analysis of this workpackage to the VLIET building of KULeuven. The experiments are conducted in a wall of the row house constructed in the previous year (see the report of 2007). The obtained data can be used to get physical insight about the HAM transport phenomena and as a validation tool for the numerical model to be developed under WP2.1. Description of work During the first year, a test-setup was built at the VLIET-building of the K.U.Leuven in Heverlee (Figure 24). In the building, a terraced house has been constructed (see the report of 2007) Figure 24: Schematic representation of the VLIET-building and the terraced house. In this project year, a test wall at the north east side of the terraced house has been constructed. The constructed test wall is a lightweight wall divided in three different parts. In all parts, the necessary measuring devices were installed. This section describes the test setup and depicts the first measurement analysis. WP2.2.1 Temperature, humidity and heat flux measurement The experimental set up is installed in one of the VLIET building walls (Figure 25). The considered wall is subdivided into three vertical parts (left, central and right). The left wall is air and vapour open at the inside, the right part is airtight but vapour open (gypsum board at the interior). Each part contains three measuring rows (top, middle and bottom). Tweede jaarlijks rapport 24

25 Left part y Central part z x Right part Top row Middle row y y Bottom row y x x x Figure 25: The test wall of The VLIET building. In the wall a total of 57 thermocouples, 18 humidity sensors and 12 heat flux sensors are mounted. The sensors are distributed in top, middle and bottom rows of the wall. Figure 26 shows a section through the wall and heat flux sensors distributions in it. Similarly, but not exactly, thermocouples and humidity sensors are also placed in the wall. Wooden board Cavity Celit 3D Insulation fibre Gypsum board Left part Central part Right part installed in top row installed in middle row installed in bottom row Figure 26: Schematic representation of the wall and heat flux sensors distribution. Tweede jaarlijks rapport 25

26 Figure 27: Heat flux sensor arrangement. Temperature, humidity and heat flux data are available since December The data are collected continuously with a sampling rate of 10 min -1. WP2.2.2 Thermal analysis Thermal resistance Thermal resistance is a measure of a material s ability to prevent heat from flowing through it; the parameter can be determined using theoretical and experimental methods. a) Theoretical method n di Rtheo = i= 1 λi where R theo [m 2 K/W], d [m] and λ [W/mK] are theoretical thermal resistance, thickness and thermal conductivity of material i. b) Experimental methods There are two different ways to obtain the thermal resistance from measurements: The slope method: ΔTi Rs = qi Where T i [K] and q i [W/m 2 ] are measured temperature difference and heat flux across the considered wall respectively. The slope of the linear fit between q i and T i gives the thermal resistance, R s. Here the thermal resistance between the interior finishing (gypsum board or wooden finishing) and the Celit 3D material is calculated for the middle row wall for left, central and right parts. Daily averaged data is used for the analysis. Tweede jaarlijks rapport 26

27 data ΔT i = 5.66*q i 16 ΔT [K] R 2 = q [W] Figure 28: Linear correlation between q i and T i in December 2007 (left part of the wall). Direct method R d = n i= 1 n i= 1 ΔT q i i The quotient between the sum of the temperature differences and the sum of the heat flux data gives the thermal resistance, R d. Table 1: Theoretical and measurement based R-values [m²k/w] at the middle row of the walls. December 2007 January 2008 February 2008 March 2008 April 2008 Left wall Central wall Right wall R s R d R theo R s R d R theo R s R d R theo R s R d R theo R s R d R theo Tweede jaarlijks rapport 27

28 7 6 R s R d R theo 5 R [m 2.K/W] Left part Central part Right part Figure 29: R-values using the three methods (mean values over the four months). In Figure 29, the theoretical and measurement based methods provide comparable R-values for the left and central part of the wall. However, there is a significant discrepancy between the results of the two methods for the right wall. Moreover both the measurement based techniques (the slope and the direct methods) resulted in R-values of the right part of the wall greater than the central part, which is not realistic since the central part contains an extra air cavity (Figure 26). The possible cause of the disagreement between the theoretical and measurement based methods at the right wall will be further investigated. Buoyancy effects Buoyancy, if present, influences heat transfer through building walls. This influence can be assessed qualitatively with a temperature ratio, a dimensionless number which varies between zero and one. Top row T e T x2 T x1 Middle row T i Bottom row Insulation fibre Figure 30: Illustration for temperature ratio computation. Tweede jaarlijks rapport 28

29 Tx 1 Te Tx2 T e τx 1 =, τx2 = Ti Te Ti Te Ti Te where T e [ C] is temperature at the outside surface of the Celit 3D material. T i [ C] is the wall surface temperature in the room side and T x [ C] is temperature in the insulation fibre (Figure 26). The presence of buoyancy effects is analysed through the temperature ratio at both sides of the insulation layer by comparing the top, middle and bottom values. Top Month = Jan. 08 Middle Left wall τ x1 τ x2 Bottom Top Middle Central wall τ x1 τ x2 Bottom Top Middle Right wall τ x1 τ x2 Bottom Figure 31: Temperature ratio for the three parts of the wall. τ In Figure 31 no buoyancy effects can be observed. If buoyancy effects are present, the highest temperature ratio values would occur on the top row followed by the middle row of the wall, indicating the rise of warm air from the bottom. WP2.2.3 Moisture absorption measurement Nine removable, moisture capturing tiles with a commercial name of Celit 3D are used for the analysis. The test set up is shown in Figure 32. Tweede jaarlijks rapport 29

30 Removable nine moisture capturing tiles (Celit 3D) are installed to quantify moisture transfer Celit 3D 20 cm 20 cm 1.7 cm Celit 3D Figure 32: Experimental set up for moisture measurement. The measurement procedure is highlighted below: The nine Celit 3D material kept in the wall for a specific period of time in order to capture moisture (hygric buffering and interstitial condensation) The material is removed for measurement The material is weighed and the data are stored From the successive weight measurements the amount of migrated moisture is quantified as: Moisture content i where: m tot,i is total mass of the i th material(g) m dry,i is dry mass of the i th material (g) mtot, i m dry, i = m dry, i Tweede jaarlijks rapport 30

31 Moisture content [g/gdw] L/T L/M L/B C/T C/M C/B R/T R/M R/B /06 20/06 23/0627/0630/06 04/07 10/07 18/07 25/07 01/0810/08 15/08 22/08 Day/Month Figure 33: Normalised mass of migrated moisture. In Figure 33 abbreviations L, C and R stand for left, central and right parts of the wall respectively. Whereas T, M, B are for top, middle and bottom row of the wall respectively. Deliverables Measurement data is available. Data processing methodology is in place. The data are partially analysed and interpreted. Planning Further thermal and moisture analysis will be conducted using updated experimental data. Natural and forced ventilation system will be installed in the row house. These all strongly determine the air flow and hygric behaviour of the test walls. New campaign of experiments, data analysis and result interpretation will be performed. A test set up will be prepared to study air permeability of the Celit 3D tile. Occurrence of interstitial condensation inside the Celit 3D material will be checked in the winter season. Tweede jaarlijks rapport 31

32 WP3.1 Convective heat exchange and summer comfort Objectives WP3.1 will focus on the convective heat transfer in rooms and offices and its impact on summer comfort performances by solar processing, intensive (night) ventilation and thermally active flooring. Engineering the summer comfort performances depends on the other hand to a large extent on a reliable prediction of the local heating through solar irradiation and the prediction of wind pressures around buildings for ventilation (WP1.1). WP3.1 is subdivided into four parts: WP3.1.1 An experimental analysis of convective heat transfer between the ventilation air and the building surface will be performed. This work focuses on a single zone and will be done in the rotating PASLINK-cell available at BBRI, a highly instrumented test facility. WP3.1.2 An experimental analysis of solar heating and intensive ventilation and its impact on summer comfort will be conducted. WP3.1.3 A numerical prediction of ventilation and local heating through solar irradiation inside buildings will be performed. The solar illuminated patterns on inside surfaces through direct solar radiation will be calculated and converted to local heat powers. For the ventilation, input data from WP1.1 will serve as boundary conditions. The CFD simulations will be coupled with a multi-zone building simulation model and the predictions will be validated by comparison with the test results. WP3.1.4 The numerical methods that are developed will be validated with data measured in projects realised by the industrial partners. Description of work WP3.1.1 Experimental analysis of convective heat transfer between the ventilation air and the building surface It has to be noted that the content of this subpackage has been extended. Now also a numerical analysis (described below) is included in addition to the experimental analysis. Ideally, to predict the building performance in detail is to solve the conservation equations for the temperature and the velocity fields for the room that is of interest. However, because of high computational costs of Computational Fluid Dynamics (CFD), multi-zone energy simulation is currently appraised. An important component of building energy analysis is the prediction of interior convective heat transfer. The convective heat transfer coefficients (CHTC s) are mostly derived from data based on experiments with stand-alone surfaces. Recently there is a trend to develop new CHTC s for real building surfaces according to the flow regime in the room as reviewed by Sacré et al. (2007). Consequently a study (Goethals and Janssens 2008a) is performed to further examine the sensitivity of the predicted performance by ES to the modelling of convective heat transfer. Simulations of a night cooled office are carried out in TRNSYS during the Belgian summer. The examined room is based on the model described by Breesch (2006). In this particular case of night cooling, accurate modelling of convective heat transfer is extremely important, because the CHTC s should be considerably higher than those normally used. The influence of the CHTC correlations, extracted from literature, is evaluated for the summer comfort Tweede jaarlijks rapport 32