Study of the External Flow: Model Setup

De-coupled CFD external flow simulations predicted wind pressures at location of the building’s openings, which were used for the prediction of the performance of the wind-induced ventilation strategies. The building under investigation and the neighbouring buildings were simulated as individual blocks with all openings

‘closed’. The design was simplified to reduce computational time and therefore shading systems, balconies and trees were excluded from the simulation process. The terrain heights were initially included in the CFD model although after preliminary simulations it was predicted that their influence on the flow field was insignificant, and mostly up to the height of the ground floor level. The terrain heights were excluded from the CFD simulations. The heights of all buildings were increased proportionally to represent the natural differences in height due to the terrain, as described in detail in Chapter 4.3. The domain size, location of the building and computational mesh properties were developed according to existing published work (Chapter 2.6.3)

For the evaluation of the external flow field at first, the case study building was simulated as a stand-alone building according to Visagavel and Srinivasan (2009) and Yik and Lun (2010). However it was considered important to evaluate the performance of the ventilation strategies and the building within its context: the simulation results of the stand-alone simulations were considered insufficient and unrealistic (see Section 6.3.1). Different domain sizes were evaluated, according to literature (Chapter 2.6.3). After exploratory simulations and by considering the recommendations by the software developer, it was decided to model the computational domain proportional to the outline of all buildings. This provided appreciable simulation results at an acceptable computational time, while enabling efficient investigation of various wind directions. The selected building was modelled centred in nine urban blocks and the computational domain faces on x and y were designed 300m offset to the building and the surroundings’ outline (more than 8 times the height of the tallest building). The dimensions of the computational domain (Figure 6.2) were equal to 900m×750m×136.8m and the nine blocks occupied a central area of 40677m² (the domain height was 4 times the height of the tallest building). These were found to be sufficient to model the exterior airflow.

Chapter: 6 | 164

Figure 6.2 Plan view of the building (centred in grey) and its surroundings’ at the neighbourhood scale, with blue and red arrows pointing at north and the wind direction, respectively. Invisible objects that do not affect the airflow calculations assist the refinement of the computational mesh and divide the domain into 9 zones

Wind was modelled using a simulation option in PHOENICS known as the ‘wind object’ that occupied the entire domain. The wind object creates inflow boundaries at the domain edges with a logarithmic profile on the upwind faces and fixed pressure boundaries on the downwind faces, sky and ground plane (Ludwig and Mortimore, 2011). Atmospheric pressure was set at all faces of the wind object, while “the mass flow through the pressure boundaries is a linear function of pressure difference”

(Ludwig and Mortimore, 2011). A series of simulations with different ground plane effective roughness heights predicted that this had negligible influence in the occupied zones. The increase in roughness height resulted in computational time increase. The ground plane was modelled with an effective roughness height of 0.75m because it provided accurate and less computationally demanding results.

The turbulence was modelled with the modified k-epsilon model of Chen and Kim (CHAM Ltd., 2008) which reduces the dissipative nature of the standard k-epsilon

Chapter: 6 | 165 model of Launder and Spalding (Launder and Spalding, 1974), whilst the energy equation was not calculated. The probe used to monitor convergence was located at 7.7m height above the ground level, among the buildings and at varying locations in relation to wind direction. The solution was considered converged when the spot values (of the pressure and the three components of velocity) at a defined monitoring point in the domain, remained unchanged and when the logarithms of the sums of the absolute residual of each variable (errors) in the finite-volume equation were reduced to an acceptable magnitude and below 1E-03.

Figure 6.3 Plan view of the three-dimensional model of the building in PHOENICS, showing the air shaft highlighted in red, the position of the apartment with dash line, the position of the balconies (in light blue) and the penthouse (in dark blue)

A plan view of the building model in CFD is presented in Figure 6.3. The external flow field was modelled for three ventilation scenarios. Pressure values predicted at some models could be used at the study of the internal flow field of different ventilation strategies with the same building design, the three models are:

 Base-case ventilation strategy of the building under investigation using the existing design of the light well. The simulation results assisted the study of the internal flow field of single-sided and cross ventilation strategies ([SS], [CV]).

 The addition of the wind-catcher model to the previous design was investigated, providing pressure values for the study of the wind-catcher and

‘water evaporation’ strategies ([WC], [PDEC-WC]).

 The addition of the dynamic façade provided input values for the dynamic façade and water evaporation strategies ([DF & WC], [PDEC-DF]).

Chapter: 6 | 166 The proposed three models were evaluated for three wind directions (north, east, northwest), the selection criteria of which are presented in Section 6.5, and two wind speeds (3.6m/s and 7m/s), as illustrated in Figure 6.1. A total number of 38 external flow CFD simulations were performed for the purpose of this research. All simulations reached convergence after approximately 8,000 iterations within 50 to 130 hours, with regard to the building model, orientation and the resources available at the time of the simulation. Simulations were performed both in serial and parallel options of the software, the limitations and potential of each are further discussed in Appendix A.4.1.

6.3.1. Mesh independency study

In order to ensure a solution independent of the mesh resolution, six different computational meshes (Cartesian) were created, included in Table 6.2, with dense areas at zones of complex or rapidly changing flow. The CFD model of the ‘wind-catcher’ scenario [WC] was selected for the mesh investigation due to the complex geometry of the wind-catcher requiring very fine mesh elements.

Table 6.2 Computational meshes evaluated for the study of the external flow showing the number of cells at the wind catcher zone, the number of cells of each domain axis and the total number of cells

The first five meshes converged to an acceptable level (see convergence plot for Mesh 5 in Figure 6.4), however, convergence was more difficult to achieve for the sixth mesh. Meshes 4 and 5 provided the most comparable results (Figure 6.5); mesh five was chosen because it provided sufficient design flexibility to include further natural ventilation strategies. Convergence could only be achieved by specifying under-relaxation factors of 0.1 on the three velocity components, which by slowing-down the solved-for variables avert the divergence of the built-in iterative solution process-the convergence rate was noticeably reduced.

Chapter: 6 | 167

Figure 6.4 Convergence monitoring plot showing the reduction in error and the variable values at a user-specified monitor location in the grid ([DF & WC], northeast, Mesh 5)

Figure 6.5 Driving pressures (Pa) predicted by simulations with different number of cells, study of the external flow field.

A plan view and a front view of the building studied with the surrounding buildings and computational domain are presented in Figure 6.6 (xy axis 7m height above the ground level) and Figure 6.7 (x,z axis) respectively. The coarser mesh areas were located towards the corners of the domain and the denser in the centre, where the building of interest was located (i.e. centred among the buildings). Finer mesh was generated at the location of the light wells (or the wind-catcher with regard to the ventilation strategy).

Grid control objects with no effect on the calculations (‘null’ object in PHOENICS) were created at a short distance from the corners of the buildings in x, z and y, z

5.4 5.5 5.6 5.7 5.8 5.9 6 6.1 6.2 6.3

2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 4,500,000

Driving Pressure (Pa)

Number of cells Mesh 1

Mesh 5

Chapter: 6 | 168 areas (Figure 6.2). These provide higher levels of grid control, enabling a fine mesh to be created over the buildings and the more rapid expansion of the grid further away of the building zone (i.e. coarse).

Figure 6.6 Representation of the building studied, surroundings, computational mesh and domain size in plan xy view for the study of the external flow.

Figure 6.7 Representation of the buildings, computational mesh and domain in x,z view.