- freely available
Energies 2016, 9(3), 177; https://doi.org/10.3390/en9030177
2.1. Urban Morphologies Selected for the Study
2.2. CFD Prediction Results for Air Speed and Building Surface Pressure Distribution
2.3. Results of Air Infiltration and Expected Impact on Energy Consumption Calculations
- The highest values of average speed and the lowest for turbulent kinetic energy within street cavities were observed in the case of urban morphology UM-1. However, it seems that this layout exhibits better aerodynamic properties that allow a reduction of wind induced energy consumption by approx. 41% compared to urban morphology UM-2. Therefore, designing built neighborhoods according to this overall spatial shape should be considered to achieve lower energy consumption of smart cities.
- The highest wind induced air change rates and pressure differences on building surfaces were observed for urban morphology UM-2. Mixed building height and highest average building height and street width ratio resulted in a significant increase of the estimated heat load required to cover the heat losses despite the wind direction.
- A relatively small difference between the results of the layouts UM-1 and UM-3 was found. These models however, were similar in that buildings were joined into blocks in both cases. This leads to overall lower values of air leakage areas as, in this study, air leakage areas were calculated from specific leakage area (AL, cm2/m2) according to the exposed surface areas of the buildings.
4.1. Urban Morphologies and Boundary Conditions
4.2. Tools and Procedures Used for CFD Simulations
4.3. Validation of the CFD model
4.4. Air Infiltration Estimation
- Reading the pressure values for each grid cell of the building’s exposed surfaces obtained by CFD, and calculating the surface weighted mean external pressure. This defines the building’s inner pressure.
- Determining overall pressure difference by using the difference between the sum of the values which are higher than the inner pressure on the building surface, indicating air infiltration and the sum of the values which are lower than the inner pressure, indicating exfiltration.
- The pressure difference thus obtained was used for calculating the air flow rate by applying the ELA equation :
- Discharge coefficient—0.6 (i.e., the discharge coefficient for a sharp-edged orifice) ;
- Equivalent leakage area was calculated by using the specific leakage area i.e., the ratio of (AL) and exposed surface area of the building. This ratio was considered 4 cm² per 1 m² of the building surface area ;
- Air density—1.16 kg/m³.
- Building air change rate was calculated as follows:
- The total energy consumption of the built neighborhood was estimated by calculating total air flow rates using the average built volume between the simulated cases and air change rates of each particular case. Heating load required to cover air infiltration heat losses was calculated as follows :q = ΣQ·ρ·cp·Δt
Conflicts of Interest
Computational fluid dynamics
Equivalent Leakage Area
Indoor air quality
|Step||Description and Known Values||Values Obtained|
|1-2||Calculating the mean pressure on building surfaces and determining the pressure difference||(p-pavg) > 0 = 6.88 Pa|
(p-pavg) < 0 = –3.24 Pa
|Δp = 10.12 Pa|
|3||Air flow rate calculation||Building volume—20979 m³|
Air leakage area—1.69 m²
|Q = 15222 m³/h|
|4||Building air change rate calculation||ACH = 0.726|
|5||Heating load required to cover air infiltration heat losses at Δt = 10 K||q = 40.3 kW|
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|Urban Morphology||Height of Buildings, m||Hb/W 1|
|UM-2||16 and 36 m||1.73|
|UM-3||8 to 16 m||0.76|
|Wind Direction||Urban Morphology||Average Speed in Street Cavities at 2 m, m/s||Weighted Average Δp, Pa||Weighted Air Change Rates 1||Heat Losses at Δt=10K, kW||Percentile Increase Compared to Lowest Result|
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