30120130405023

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 5, September - October (2013) © IAEME

AND TECHNOLOGY (IJMET)

ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 4, Issue 5, September - October (2013), pp. 200-207
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2013): 5.7731 (Calculated by GISI)
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IJMET
©IAEME

CFD ANALYSIS OF WIND DRIVEN NATURAL CROSS VENTILATION FOR
A GENERIC ISOLATED BUILDING
N.S. Venkatesh Kumar1, Prof. K. Hema Chandra Reddy2
1

(Research Scholar, Department of Mechanical Engg., JNTUA, Anantapuram, A.P., India)
2
(Registrar, JNTUA, Anantapuram, Andhra Pradesh, India)

ABSTRACT
Natural ventilation, which provides occupants with good indoor air quality and a high level of
thermal comfort with reduced energy costs, has been drawing importance in sustainable strategy in
building designs. This investigation used computational fluid dynamics (CFD) models to study the
ventilation properties for a room with different opening configurations. The 3D steady RANS
equations are solved in combination with the shear-stress transport (SST) k- ω model. The inlet wind
velocity profile is defined according to the logarithmic law in accordance with urban climate.
Ground surface roughness is considered for the analysis. The flow around a building captured the
circulating bubbles upstream and downstream of the building, and the steady flow pressure
coefficient has the same trend as the experimental ones. Air momentum transport seems to be carried
mainly by convection and hardly by turbulent diffusion for cross ventilation.
Keywords: computational fluid dynamics, ventilation, velocity profile, flow pattern, cross
ventilation
1. INTRODUCTION
Natural ventilation, which provides occupants with good indoor air quality and a high level of
thermal comfort with reduced energy costs, has been drawing importance in sustainable strategy in
building designs and is thus attracting considerable interests from designers [1] & [2].
Wind and buoyancy are the driving forces for natural ventilation. Wind pressure differences
along the façade and differences between indoor and outdoor temperatures create a natural air
exchange between indoor and outdoor air. The ventilation rate depends on the strength and direction
of these forces and the resistance of the flow path. Prediction of ventilations rates is difficult as these
physical processes are complex. Hence, it is challenging to control natural ventilation in order to
obtain the required indoor environment conditions.
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The configurations of building rooms and especially the location of inlet and outlet openings
in relation to dominant wind direction at the site have major effects on the ventilation rates in
buildings. Studies identified that locating Inlet openings near high-pressure surfaces of a building
and exit openings at low-pressure ones produces higher flow rates through windows. Accordingly, an
understanding of air flow around the building is necessary to design well-ventilated residences.
External flows around buildings are very complicated involving severe pressure gradients, streamline
curvature, swirl, separation and reattachment together with the resulting effects of enhancing and
suppression of turbulence.
Empirical models, experimental measurements and computational fluid dynamics (CFD)
simulations are the three approaches available to study natural ventilation. The empirical models, as
reviewed by [3], are often developed from analytical solutions and experimental data. Although the
models are very useful for natural ventilation design, they could not provide sufficient information
on natural ventilation and may not be so accurate. It has been proven that the experimental
measurements are effective as a tool to obtain realistic information about natural ventilation [4]. The
measurements are not only very expensive but also time consuming. Added to this, the data may not
be in great enough detail for understanding the mechanism of natural ventilation.
CFD has a number of clear advantages compared with the other approaches: (1) as opposed
to most experimental techniques including Particle Image Velocimetry (PIV) , CFD provides field
data as regards whole-flow, i.e. data on the relevant parameters in every point of the computational
domain; (2) CFD avoids the sometimes incompatible similarity requirements in reduced-scale testing
because simulations can be performed at full scale; and (3) CFD allows full control over the
boundary conditions and easily and efficiently allows parametric studies to be performed[5]. CFD
models are currently most popular and particularly suited for studying indoor air quality and natural
ventilation, as these are difficult to be predicted using other models. For the above reasons, many
studies on evaluating and optimizing the natural ventilation potential of buildings have employed
CFD.
In view of above factors, the present work is aimed to employ computational fluid dynamics
to determine the distribution of steady, three-dimensional and turbulent in-room and external flow
field of an isolated generic building. Although the effects of neighboring buildings can be significant,
only an isolated room is considered for the present work to test the basic natural ventilation rules as
affected by relative opening location and different sizes. The CFD simulations are carried out using
ANSYS-CFX, CFD software. The two-equation SST turbulence model is used.
2. CFD SIMULATIONS
Computational settings and parameters for the reference case are outlined and accordingly the
results for this case are presented. Later on, these settings and parameters will be systematically
modified for the parametric study.
2.1. Computational domain and grid
The dimensions of the generic isolate building and computational domain were chosen from
[5]. The buildings had dimensions W x D x H = 100 x 100 x 80 mm³ and thickness of the walls is 2
mm (reduced scale) corresponding to full-scale dimensions W x D x H = 20 x 20 x 16 m³.
Computational domain dimensions are calculated as width WD = W +10H, height HD = H + 5H and
upstream and downstream length of 3H and 15H .The resulting dimensions of the domain were W x
D x H = 0.9 x 1.54 x 0.48 m³ (reduced scale), which corresponds to 180 x 308 x 96 m³ in full scale.
The computational grid is made of unstructured mesh with Hexa-core, tetrahedral surface mesh and
prismatic elements on building walls. The prismatic elements at wall boundaries of building are able

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to provide fine mesh for capturing boundary layer. The geometry and mesh is generated using ICEM
CFD, meshing software.

Fig.1: Surface mesh for domain (tetrahedral)

Fig.2: Volume mesh on central plane

Fig.3: Dense mesh around

2.2. Boundary conditions
The inlet boundary conditions used in the simulations were based on the measured incident
vertical profiles of mean wind speed and turbulence intensity. The inlet wind velocity profile is
defined according to the logarithmic law with Y0 = 0.025 mm (Eq. 1), where 0.3627[m s^-1] is the
ABL friction velocity, the von Karman constant (0.42) and y the height coordinate.
Expression incorporated in CFX ;
(0.3627[m s^-1]/0.42)*ln((y+0.000025[m])/0.000025[m])

(1)

For the ground surface, the no-slip wall functions with roughness height of 0.28 mm are
chosen. No-slip wall functions are also used at the building surfaces, but with zero roughness height.
Zero static pressure is applied at the outlet plane. Free-slip wall functions are used at the remaining
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domain surfaces. The computational domain with boundary condition and velocity profile at inlet is
as shown below.

Fig.4: Applied boundary conditions

Fig.5: velocity profile at inlet

2.3. Solver settings
The 3D steady RANS equations were solved in combination with the shear-stress transport
(SST) k- ω model. Advection scheme adapted for solving momentum governing equations is High
resolution and for turbulence equations first order scheme. The convergence criteria are taken as 10-6.
3. RESULTS AND DISCUSSION
CFD simulations of wind driven natural cross ventilation for generic isolated building are
carried out using ANSYS CFX, CFD software. The results presented here are for three cases named
as case I, case II and Case III. Case I refers to cross ventilation with equal area of inlet and exit
openings, both are situated at center of wall. Case II is with larger opening and small inlet area and
situated same as in Case I. The third one represents for equal inlet and exit opening areas and inlet is
situated at bottom center and top center of front and rear wall. The pressure and velocity distributions
are shown by contour plots and velocity vectors.
3.1. Case I
The velocity vector field and pressure contours in the vertical center plane are presented
below. Main features of the flow simulated are the standing vortex upstream of the building, the
contraction and expansion of the indoor flow, the recirculation zone behind the room and the
separation zone on the roof. External flow features resembles that of square block.

Fig 6: central plane vertical
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Fig 7: pressure distribution in CPV
The velocity vector field shows the inlet velocity profile which varies with the height and
ground surface roughness which accounts the nature of surroundings. The results are thus expected
to be varying in accordance with building height and surrounding ground roughness.

Fig: 8 Velocity vector in CPV around the building and in room
The below figures show velocity vector field, velocity and pressure contour in the horizontal
plane at height of 0.04 m. It can be seen that only the area spanned by the cylindrical stream tube is
actually ventilated. The ventilated zones are generally referred as active and non-ventilated as calm
or dead zone. The blue color zone represents the dead zone. The red color in pressure contour
represents stagnation flow field which is located at top of front wall and on two sides of opening.

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Fig: 10 Pressure vector in CPV around the
building and in room

Fig: 10 Velocity contour in CPV around the

3.2. Case II
The results presented are for cross ventilation with increased area for exit openings. Supply
and exhaust window location are at the center of opposite walls. The below figures shows the air
flow vector field velocity and pressure contours in the vertical center plane. The plan of the
ventilated zone seems to have larger area at exit and looks resembles a trapezoid. Transport of air
momentum seems to be carried mainly by convection and hardly by turbulent diffusion.


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Fig: 11 Pressure contour in CPV around the

Fig: 12 Velocity contour in CPV around the

Fig: 13 Velocity vector field in the horizontal
plane plane at height of 0.04 m

Fig: 14 Pressure contour in the horizontal
at height of 0.04 m

3.3. Case III
The results presented are for cross ventilation with equal inlet and exit openings. Inlet
opening located at bottom ad outlet at top. The below figures shows the air flow vector field and
pressure contours in the vertical center plane. There is an increased area of the calm zone at center of
room as compared to Case I and fresh air is more attached towards the wall. The quality of air inside
of room is decreased. The external flow features are same as that of other cases.

Fig: 15 Velocity vector in the vertical center plane
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Fig: 16 Velocity contour in the vertical center plane
4. CONCLUSIONS
The model for flow around a building captures the circulating bubbles upstream and
downstream of the building, and the steady flow pressure coefficient has the same trend as the
experimental ones. The two-equation turbulence model is a useful tool for predicting in-room flows.
Cross ventilation is useful for ventilating the areas passed by the stream tube between inlet
and exit openings, but outside the stream tube recirculation zones with no domination of fresh air.
The low turbulence level is not enough to enhance momentum transfer from the stream tube to the
otherwise stand still air outside the tube.
Based on the locations of humans inside the room, the wind incidence angle can cause an
increase in velocity magnitude and reduction of calm air zones inside the room.
REFERENCES
[1] Etheridge, D., Sandberg, M, Building ventilation: theory and measurement (New York: John
Wiley and Sons, Chichester; 1996).
[2] Allard, F,.Natural ventilation in buildings: a design handbook (UK: James & James, London,
1998).
[3] Allocca, C, Single-sided natural ventilation: design analysis and general guidelines, M.Sc.
Thesis, Department of Mechanical Engineering, Massachusetts Institute of Technology,
Cambridge, MA. 2001.
[4] Katayama T., Tsutsumi J., Ishii A., Full-scale measurements and wind tunnel tests on crossventilation (J. Wind Eng. Ind. Aerodyn. 1992, 41-44) 2553-2562.
[5] Ramponi R, Blocken B., CFD simulation of cross-ventilation for a generic isolated building:
impact of computational parameters, Building and Environment, 2012, 53, 34-48.
[6] Tarun Singh Tanwar, Dharmendra Hariyani and Manish Dadhich, “Flow Simulation (CFD) &
Static Structural Analysis (FEA) of a Radial Turbine”, International Journal of Mechanical
Engineering & Technology (IJMET), Volume 3, Issue 3, 2012, pp. 252 - 269, ISSN Print:
0976 – 6340, ISSN Online: 0976 – 6359.
[7] P.S. Jeyalaxmi and Dr.G.Kalivarathan, “CFD Analysis of Flow Characteristics in a Gas
Turbine- A Viable Approach to Predict the Turbulence”, International Journal of Mechanical
Engineering & Technology (IJMET), Volume 4, Issue 2, 2013, pp. 39 - 46, ISSN Print:
0976 – 6340, ISSN Online: 0976 – 6359.
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