CFD is applied to vast range of building types
and ventilation strategies throughout the design
process, from feasibility or concept through to detailed
design and even post-occupancy. Although CFD is traditionally
thought of as a specialist application, its use is
becoming more widespread and mainstream throughout
the building industry opening up to non-expert and
expert users alike.
One important application of CFD in the built environment
is the modeling of office spaces. Such airflows can
be placed into two categories. Firstly, natural ventilation
flows are those generated by air movement through
openings in the façade. This air movement
can be buoyancy-driven with internal heat gains (e.g.
people, machinery, lighting and solar gains) creating
temperature differentials between inside and outside
and/or wind-driven by the external pressure field.
Secondly, flows may be driven by mechanical ventilation
systems. In this case, the air movement has different
regions of momentum sources and mixing with heated
or cooled air interacting with other sources of buoyancy
within the space yielding complex flow patterns.
Natural ventilation can be combined with mechanical
ventilation (mixed mode) either by design or with
user interaction, e.g. opening a window. A typical
feature of internal flows is that the driving forces
are usually small.
For either of these types of ventilation, one of
the fundamental measures is occupant thermal comfort
(Fanger 1972). Furthermore, one of the typical requirements
for thermal comfort is low air speeds and a fairly
narrow band of air temperatures within the occupied
zones. A number of solutions have been developed
within the HVAC industry and these can be categorized
into mixing ventilation and displacement ventilation.
Mixing ventilation is where air is supplied into
the space with relatively high momentum flux in order
that the air in the space will be mixed to a reasonably
uniform temperature, yet satisfying the requirement
for low air speeds. This is usually achieved by supplying
air at high level within the space (i.e. outside
the occupied zone). This form of ventilation generates
vertically mixed air within a space. The second approach
is displacement ventilation whereby air is supplied
into the space at low level and with low momentum.
The natural sources of buoyancy generate upward flowing
plumes which carry heat and pollutants to high level
and away from the occupants. This approach leads
to temperature stratification within the space and
has the advantage that the supply air volume can
be lower than for a mixing system and energy can
be saved with air supplied at a higher temperature.
Descriptions of natural and mixing flows and buoyant
convection in confined spaces can be found in Linden,
Lane-Serff and Smeed (1990), Linden (1999), Morton
et al (1956) and Baines and Turner (1968).
Many buildings are satisfactorily designed and
constructed without recourse to CFD analysis. Indeed,
for tried and tested design solutions, there is little
to be gained by more complex analysis. However, there
are cases with an unconventional air distribution
design, for example, where an assessment of the likely
performance of the proposed design may be required
in order to provide confidence in the design. The
design process may use CFD with or without other
calculation techniques such as dynamic thermal modeling
or hand calculations.
The performance assessment usually relates to a
greater understanding of the air movement and air
temperature distribution within a space or, more
precisely, the interaction of the HVAC system with
the building envelope, internal heat gains and climatic
influences over a year. Other issues, such as moisture
levels, may require consideration in certain circumstances,
e.g. a condensation risk analysis.
1. Example: Office space
In the application challenge carried out by Arup,
an assessment was made of a ventilation system for
an open plan office. An intermediate system (between
a standard displacement and mixing system) is used
where air is supplied through floor-mounted swirl
diffusers from ducts in an underfloor void. The supply
air has greater momentum and mixing than that which
would be typically associated with a displacement
system.
 The
office is situated next to the docks at Cardiff Bay
and was designed in 1994-1997 using in-house thermal
analysis software [Oasys Ltd] and a commercially
available CFD code [STAR-CD]. The structural design
comprises a 4-storey steel frame with pre-cast concrete
ceilings. The external envelope is traditional brick,
cavity and block construction. The building is L-shaped
with sides approximately 35m long, its width varying
between 14 and 18m (see Figure 1). The floor plate
has an area of 3,100m2 and is open plan with a limited
number of cellular offices. A notional corridor goes
through the center of each floor plate and the work
spaces are either side of the corridor. The building
uses a mixed mode ventilation system with a night
purge facility incorporating mechanically-operated
vents and the thermal mass of soffit and walls.
CFD predictions were carried out in 1997 as part
of the building design process, i.e. a “design
stage” analysis. The building was occupied
in August 1998 (see Fig 1 above).
Measurements of the completed building were carried
out as part of the monitoring process during summer
2001. Finally, as part of the application challenge
in 2003, “post-occupancy” CFD predictions
using STAR-CD were carried out using boundary conditions
taken from the monitoring process. The primary objective
was to understand the effect of air supply flow rate
on the air temperature distribution within the space.
2.Test data
Monitoring was used to compare the internal environment
on the 2nd and 3rd floors and also understand the
performance of the building fabric between these
floors. In addition, the measurements were used to
generate information to feed back into the original
CAD design tools to enhance future designs.
 Fig
2: Office floor plan with dimensions
Although the floor plans are the same on each floor
(as shown in Figure 2), the geometry differs with
a 3m floor-to-ceiling height on the 2nd floor and
4m on the 3rd floor. In addition, the exposed ceiling
surfaces differ. The 2nd floor has an exposed concrete
soffit and the 3rd floor has a profiled ceiling with
a metal covering.
Measuring stations were located at three positions
on the South West side of the building on each floor,
i.e. six measuring stations in total. Each station
measured the vertical temperature gradient from 0.1m
to 2.8m above the floor (4 points in total). Heat
flux and surface temperatures at ceiling level were
also monitored, but not air speeds.
3. CFD analysis
The “post-occupancy” computational
mesh was made up of approximately 300,000 fluid cells
with increased resolutions close to the surfaces
as well as the supply inlets and extract grilles
(see Fig 3). The flow obstruction due to furniture
was not represented in the model as the displacement
flow direction is predominantly in the vertical direction,
i.e. a small influence on the air movement was assumed.
 Fig
3: Views of the CFD mesh
 Fig4:
Supply air diffuser locations
Swirl diffusers are geometrically quite complex
with small length scales compared with the office
space. A simple representation was therefore used
which was initially compared (air temperatures and
velocities), in isolation, with published manufacturer’s
test data. Adjustments in flow direction and volume
were made to each inlet boundary making up the diffuser
to optimize the jet representation for the chosen
diffuser at the required flow rate (see Fig 4). Wall
and supply air temperatures were set according to
the data obtained from the monitoring process.
One possible source of error between the measurements
and predictions relate to internal heat gains (occupancy
levels and computers in use) as this was not recorded
during the monitoring process. However, standard
office use assumptions were made as follows:
- Occupants - 1 person per 13m2 of floor area
(49 people per floor) at a convective heat output
rate of 35W per person.
- Machines - 10W/m2. This was assumed be 100% convective
and was applied as an equivalent heat source in
W/m3.
- Lights - 10W/m2. This was assumed be 55% convective
(fluorescent lamps) and was applied as an equivalent
heat source in W/m_ at ceiling level.
Air temperature distributions on horizontal and
vertical sections through the space (Figs 5 & 6)
showed the local effects of supply air diffusers
and lighting heat loads as well as the vertical stratification
within the office space.
 Fig
5: Air temp distribution 0.1m above floor
level
 Fig
6: Air temperature distribution on two vertical sections
4. Comparing test data with CFD
predictions
One of the major problems relating to the monitoring
data was that it was not explicitly generated for
comparisons with the CFD predictions. Table 1 shows
an example of comparative data for measured and predicted
post-occupancy air temperatures at one measuring
station location and as an average value for a particular
height above the floor at 16:00 hours (all in °C).
5. Conclusions
Validation of airflow prediction in buildings using
CFD is inherently difficult. Studies are usually
completed long before the building is constructed,
making in situ comparisons between measured data
and modeling extremely rare. Unless there is an airflow
problem with a completed building, the client is
usually unwilling to finance post-occupancy CFD studies.
This challenge is further compounded by the differences
between the input assumptions used in the modeling
and the real operation of the building, e.g. variations
in temperature boundary conditions, internal heat
gains, building operation and control. The majority
of comparative studies are therefore carried out
in academia using test chambers and other experimental
facilities examining particular HVAC or fabric-related
issues.
Although comparisons with measurements are problematic,
there is an increased acceptance of the results with
architects and clients alike. Good correlation is
possible between measured and predicted air temperatures
in a working office space.
6. References
[1] Baines, W.D. & Turner,
J.S. 1968. Turbulent Buoyant convection from a
source in a confined region. J. Fluid Mech. 37,
51-80
[2] Computational Dynamics Ltd. 1988-1999. STAR-CD v3.1 – Theory
manual
[3] Fanger, P.O. 1970. Thermal comfort – analysis and applications
in environmental engineering. 244p Danish Technical Press
[4] Linden, P.F., Lane-Serff, G.F. & Smeed, D.A. 1990. Emptying filling
boxes: The fluid mechanics of natural ventilation. J. Fluid Mech. 212,
300-335
[5] Linden, P.F. 1999. The fluid mechanics of natural ventilation. Ann.
Rev. Fluid Mech. 31, 201-238
[6] Morton, B.R., Taylor, G.I. & Turner, J.S. 1956. Turbulent gravitational
convection from maintained and instantaneous sources. Proc. Roy Soc Lond.
A 234, 1-23
[7] OASYS Ltd 1992. OASYS computer program manual, ROOM analysis
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