**Table 2.**

*Wind direction & velocities for Montenegro.*

*The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

**Figure 4.** *Plan and landscape view of the case study area.*

In this study, CFD Fluent was preferred to simulate pedestrian level comfort conditions and wind condition environments due to both the bureaucratic and economic constraints encountered for field measurements and the more comprehensive analysis parameters provided by numerical simulation. The CFD simulations were performed using CFD code Fluent and the 3D steady RANS equations. The closure was provided by the realizable (k-ε) turbulence model. The choice of this turbulence model was based on recommendations by Franke et al. [63] and earlier validation studies for pedestrian-level wind conditions [64]. Sensible modeling of the atmospheric boundary layer in CFD is one of the most important criteria in external aerodynamic analyzes around the building. Many of the analysis software conduct flow analysis for materials with a low roughness coefficient, and therefore the roughness coefficient is defined as 0 in the CFD. Depending on the region where the structure is located, the roughness coefficient should also be defined. Since it is an open zone surface, the surface roughness is defined as 0.2 m [9].

Pressure differences occur on the surfaces of buildings exposed to wind. Due to the pressure difference in the building envelope caused by the wind and the density difference between the indoor and outdoor air, it causes air exchange around the building and in the buildings. Pressure coefficients largely depend on the shape of the buildings and the influence of neighboring buildings. The pressure field in a complex urban area can be analyzed to reveal the potential for natural ventilation in the urban texture. Modeling of wind flow and velocity around buildings in urban texture has traditionally been applied with full-scale measurements and wind tunnel tests when studies in the literature are examined. However, the creation and adaptation of atmospheric flow conditions in wind tunnel tests is a serious problem. Numerical simulations based on CFD are quite common as a tool to support the assessment of airflow around buildings in urban texture. CFD solves the problem of establishing and adapting atmospheric flow conditions encountered in a wind tunnel by providing both the actual wind flow velocity of the study area and the distribution of turbulence over the entire study area. The case study area of wind modeling, which takes into account regional terrain conditions and meteorological period average data of the region, includes surface roughness modeling in an atmospheric boundary layer [60, 65, 66].

Although RANS remains very popular in research projects, especially in the areas of wind flow and comfort between buildings, urban air pollutants and pollution dispersion, urban thermal performance, urban natural ventilation, and indoor airflow, the application of the large eddy simulation (LES) technique allows taking into account the characteristics of the wind at the atmospheric scale. The LES provides a deeper insight into the unstable flow properties. Many situations that are interesting for urban planning applications still seem to be beyond the reach of such simulations today [60].

Pressure fluctuations occurring on building surfaces depending on the average wind speed lead to both laminar and turbulent flow through leaks from the surface and between buildings [67]. High-frequency fluctuations around buildings create a turbulent distribution of air across inter-building openings containing eddies of similar or smaller size. The frequency-domain analysis of wind speed and wind pressure on the building facades is effective on the rate and amount of air exchange.

Wind-induced air change rate ACH (1/h) is given by the following equation.

$$\text{ACH}d\left(\mathbf{t}\right) = \left(\frac{\text{3600}}{\text{V}}\right) \sum\_{l=1}^{n} \left(\text{Kd}j(Vq)\right)Aj\tag{1}$$

$$\left[\mathbf{0}.\mathsf{5}\rho\left(\mathbf{C}p\_{d,j}^{\mathrm{ex}} - \mathbf{C}p\_{d,j}^{\mathrm{int}}\right)\mathbf{V}\_d^2\left(\mathbf{t}\right) + \mathbf{0}.\mathbf{0}\mathbf{4}\mathbf{z}\_\restriction\Delta\mathbf{T}\left(\mathbf{t}\right)\right]^{0.5}\tag{2}$$

This equation describes the calculated air exchange rate for different building components that are exposed to a positive pressure difference or a negative pressure difference caused by the wind blowing from d at time t.

Kd,j in the formula; a leakage function presented as a linear function of Vq regarding the flow rate from the building openings to the area of the building component j and the corresponding pressure drop across the openings for the wind blowing from there, d( <sup>3</sup> *m kg* / ); vq—"frictionless flow rate" (m/s) through openings; n—the number of elements of the building envelope facing only positive or only negative pressure difference; V—volume (m3 ); Aj—area of jth element (m2 ); ρ air density (kg/m3 ); , *ext Cpd j* ; assumed external pressure coefficient (−) for facade j exposed to wind from direction d; int *Cpd j* , ; assumed internal pressure coefficient for facade j exposed to wind from direction d (−); vd (t)—wind blowing from direction d (m/s); zj—the vertical distance from the neutral pressure layer to the center of the jth building element (m); ΔT(t)—10-min mean temperature difference between outside and inside (K) treated later on as slowly changing 1-hour mean.

Pressure differences and fluctuations in wind flow caused by turbulence around buildings affect airflow through openings and cracks in the building envelope and between buildings. The character of the wind flow depends on the scale of the wind flow length and the geometrical properties of buildings and their cracks in relation to the Reynolds number for airflow [68, 69].

### **7. Computational domain settings-parameters and meshing system**

A solid model of the case study area was created with the information obtained from the 2-D architectural project and site plans of the buildings. Threedimensional model of the project is illustrated in **Figure 5**. The definition of wind direction is illustrated in **Figure 3**. The CFD model represents buildings set along with the real topography of their location. The 1000 m × 1000 m topography, where the case study buildings are situated has been obtained from the Google Earth software. For the atmospheric boundary layer to be formed correctly, a denser grid was used in regions with rapid changes in geometry and near the surface. As a result, the quality of the grid affects the precision when the results are compared with the experimental values. Using the grid tuning twice during the analysis caused the grid *The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

**Figure 5.** *3D model view of the case study.*

to become denser where necessary and the flow solution to converge in the continuous flow regime. It was applied automatically in every 300 iterations depending on the average pressure changes on the predetermined surfaces in the buildings. The design of buildings must account for wind loads, and these are affected by wind gradients. The respective gradient levels, usually assumed in the Building Codes, are 500 m for cities, 400 m for suburbs, and 300 m for flat open terrain [70].

The approaching wind was created from a power-law model to approximate the mean velocity profile:

$$U = U\_r + \left(\frac{Z - d}{Z\_r}\right)^a \tag{3}$$

where; U = mean wind speed, Zr = reference height, Ur = wind speed at reference height Zr, d = zero plane displacement, and α = power-law exponent. The exponent α varies according to the type of terrain; α = 0.14, 0.25, and 0.33 for open country, suburban, and urban exposures, respectively. At the inlet condition, the power-law equation is used to simulate a mean wind velocity of 30.5 m/s at the building height according to an exponent α, which depends upon the surface roughness of the terrain surrounding the building model. The input parameters for wind density, ρ, and wind dynamic viscosity, η are based on the real wind characteristic.

Mean wind velocity 30.5 m/s was used as inlet boundary conditions at ten directions. A total of 30.5 m/s maximum wind velocity was used as inlet boundary conditions at ten directions as shown in **Table 1**, so that the worst scenarios could be considered.

The accuracy of simulation results is highly dependent on the appropriate computational modeling, such as domain size, grid size, and grid discrepancy. Therefore, the CFD simulation modeling for the validation approach discussed in this study complies with the AIJ (Architectural Institute of Japan) guidelines, which is one of the standards in the literature for the urban pedestrian wind environment. AIJ guidelines are based on a series of cross-comparisons between CFD, wind tunnel experiments, and field measurements. In contrast, another popular guideline, cost recommendations, is based on a literature review [71]. The calculation area size for the validation experiment is 500 m × 500 m × 50 m (W×L×H). The domain is divided into 125,170 grid points. Pressure velocity coupling was taken care of by the simple algorithm. Secondorder discretization schemes were used for viscous terms of the governing equations. Simulations were performed for ten wind directions as seen in **Table 3**. The iterations were terminated when the scaled residuals showed a very little further reduction with an increasing number of iterations. The following minimum values were reached:

#### *Environmental Management - Pollution, Habitat, Ecology, and Sustainability*


#### **Table 3.**

*Power law exponents for various descriptions of terrain.*

**Figure 6.** *Computational domain mesh numerical grid system.*

For x, y, z-velocity components: 10−8. For (k –ε): 10–7. For continuity: 10−6 Four layers (layer height: 0.5 m) are arranged below the assessment height (2.25 m above ground) to comply with AIJ guidelines. In the first step, a flow volume is created around the buildings. This area is called the computational area. This area is knitted with the network structure while creating the mathematical model. Then, boundary conditions are defined. After these definitions are made, the equations are solved and the result is reached. In all simulations, a denser network structure has been created in areas where velocity and pressure gradients are predicted to be high.

The first step is to discretize a part of the continuous space around the considered building. This part of space is named the computational domain. The domain was divided into a finite volume. For each volume of the computational domain, the basic equations were set up. Subsequently, the equations are solved given a set of initial and boundary conditions. For all performed simulations a mesh is used which is denser in regions where velocity gradients or pressure gradients will be high. An example of the mesh used is illustrated in **Figure 6**. The computational domain mesh consisted of about 12 million polyhedral and hexahedral cells.

## **8. Results and discussion**

Pressure differences occur on the surfaces of buildings exposed to wind. Due to the pressure difference in the building envelope caused by the wind and the density difference between the indoor and outdoor air, it causes air exchange in/around the buildings. Evaluation of the effect of wind on the air exchange rate is generally limited to analysis of hourly average wind speed. The wind pressure and the pressure coefficient in the leeward area mostly depend on the form characteristics of the building according to the wind direction. The frequency-domain analysis of wind speed and wind pressure on the building facades is effective on the rate and amount of air exchange. Thus, due to the changing rate and amount of air exchange around

#### *The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

the building, the amount of air exchange around the building will vary in the urban texture, and both the urban air quality and the pedestrian level will be effective on microclimatic comfort values. Air exchange in buildings and around the buildings is caused by the pressure difference in the building envelope caused by the wind and the density difference between the outside and indoor air. So, the minimum and maximum wind pressure difference on buildings causes air exchange around and inside the building [69]. For this reason, in this study, the minimum and maximum pressure values that affect the amount of air exchange around the buildings in the urban texture were examined. Evaluation of the effect of wind on the air exchange rate is generally limited to analysis of hourly average wind speed.

It was observed that the region with the highest pressure difference occurred in the region where the C01-C05-SPA buildings and TOWER buildings are located (**Figures 7** and **8**). In the case of northerly wind flow, the highest air exchange rate between buildings was observed in the region where the C01-C05-SPA-TOWER buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C01-C05-SPA buildings are located (**Figures 9** and **10**). In the case of southerly wind flow, the highest air exchange rate between buildings was observed in the region where the C01-C05-SPA is located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

**Figure 7.** *Maximum & minimum pressure on building facades for wind direction: North (N).*

**Figure 8.** *Velocity streamlines and pressure gradient for wind direction: North (N).*

#### *Environmental Management - Pollution, Habitat, Ecology, and Sustainability*

**Figure 9.**

*Maximum & minimum pressure on building facades for wind direction: South (S).*

**Figure 10.** *Velocity streamlines and pressure gradient for wind direction: South (S).*

It was observed that the region with the highest pressure difference occurred in the region where the C01-ML-SPA-MP buildings are located (**Figures 11** and **12**). In the case of East wind flow, the highest air exchange rate between buildings was observed in the region where the C01-ML-SPA-MP are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C01-C04-ML-P2-SPA buildings are located (**Figures 13** and **14**). In the case of west wind flow, the highest air exchange rate between buildings was observed in the region where the C01-C04-ML-P2-SPA buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C01-ML-SPA buildings are located (**Figures 15** and **16**). In the case of North–East wind flow, the highest air exchange rate between buildings was observed in the region where the C01-ML-SPA buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C02-P2-P3-SP buildings are located (**Figures 17** and **18**). *The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

**Figure 11.**

*Maximum & minimum pressure on building facades for wind direction: East (E).*

**Figure 12.** *Velocity streamlines and pressure gradient for wind direction: East (E).*

In the case of North-West wind flow, the highest air exchange rate between buildings was observed in the region where the C02-P2-P3-SP buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C01-C05-P2-TOWER buildings are located (**Figures 19** and **20**). In the case of South–East wind flow, the highest air exchange rate between buildings was observed in the region where the C01-C05-P2-TOWER buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are

**Figure 13.** *Maximum & minimum pressure on building facades for wind direction: West (W).*

**Figure 14.**

*Velocity streamlines and pressure gradient for wind direction: West (W).*

#### **Figure 15.**

*Maximum & minimum pressure on building facades for wind direction: North-East (NE).*

**Figure 16.** *Velocity streamlines and pressure gradient for wind direction: North-East (NE).*

other building groups other than the building groups where the lowest and highest pressure differences are seen.

It was observed that the region with the highest pressure difference occurred in the region where the C01-ML-SPA-SP buildings are located (**Figures 21** and **22**). In the case of South–West wind flow, the highest air exchange rate between buildings was observed in the region where the C01-ML-SPA-SP buildings are located. When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

*The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

**Figure 17.**

*Maximum & minimum pressure on building facades for wind direction: North–West (NW).*

**Figure 18.**

When the maximum and minimum wind pressure values resulting from the wind flows coming from different directions on the roof surfaces of the buildings in the study area were observed, the lowest pressure values were caused by the wind flows coming from the NE and NNE directions (**Figure 23**).

In this study, a total of ten wind directions, four cardinal directions, and six intercardinal directions were discussed on the settlement pattern in the historical Montenegro region, which was considered as a case study. In this chapter, the results of four main directions and four intermediate directions are evaluated in detail. Air exchange in and around buildings is caused by the pressure difference of the wind on the building envelope and the density difference between the outside and indoor air. Therefore, in this study, pressure differences on buildings, which are one of the sources of air changes occurring around the building, are discussed in detail. In this context, the wind directions that cause the most air change on the buildings in the

*Velocity streamlines and pressure gradient for wind direction: North-West (NW).*

**Figure 20.**

*Velocity streamlines and pressure gradient for wind direction: South-East (NW).*

#### **Figure 21.**

*Maximum & minimum pressure on building facades for wind direction: South-West (SW).*

**Figure 22.** *Velocity streamlines and pressure gradient for wind direction: South-West (SW).*

urban texture, which is considered first, are the wind flows coming from the NE and NNE directions.

According to the relationship between the rates of change in the surface pressure differences of the buildings and the air variability between the buildings, the data obtained as a result of the analyzes were examined in detail, it was observed that the C01-C05-ML buildings were the building group with the highest pressure difference and showing similar characteristics in all wind directions. The positive wind pressure is the pressure acting toward the wall, whereas the negative pressure/suction is the pressure acting away from the wall of models. From the pressure contours, it can be observed that on the windward face a positive pressure distribution is observed. The maximum positive pressure is 0.75 kPa at the C01 building on the NNE–ENE

*The Impacts of Air Pressure Differences on Microclimatic Wind Comfort among Low-Rise… DOI: http://dx.doi.org/10.5772/intechopen.101743*

**Figure 23.** *Maximum & minimum pressure on roofs.*

wind direction. Maximum negative pressures (suction pressures) occurred mostly at the ridges and edges of buildings as shown from pressure gradient results.

The wind load also varies between points on the building envelope, with ridges, corners, and edges most susceptible to high wind pressures. These locations are likely to require careful detailing.

When the ACH around the buildings is evaluated according to the ∆Cp values in **Table 1**, it is seen that it is an enough and good level in the regions where there are other building groups other than the building groups where the lowest and highest pressure differences are seen.

When the results of the analyzes on all prevailing wind directions and flows are examined in detail, building layouts can be revised and optimized to allow sufficient pressure on the facades of buildings with the lowest pressure values around each group of buildings. Otherwise, buildings with insufficient wind flow and therefore buildings with low-pressure values will be exposed the insufficient natural ventilation performance.
