COMPUTATIONAL METHODS IN ENGINEERING AND SCIENCE
EPMESC X, Aug. 21-23, 2006, Sanya, Hainan, China
©2006 Tsinghua University Press & Springer
Investigation of Particulate Matters with the Aid of CFD
L. M. Tam 1, V. K. Sin 1, H. I. Sun 2*, K. I. Wong 2
1
2
Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau
Institute for the Development and Quality, Macau
Email: [email protected]
Abstract Particulate matters, being one of the major indoor contaminates, can lead to serious effect to our health.
Especially for those having the aerosol diameter less than 10μm (PM10), since those are the particles that generally
pass through the throat and nose and enter the lungs. Once inhaled, these particles can affect the heart and lungs and
cause serious health effects. Therefore, concern should be paid to the indoor pollution from PM10. In this study, the
particulate matters of an industrial workshop are suspected to be at a high concentration, therefore, an investigation has
been performed to check the level of particulate matters and the air flow path of them. The investigation is conducted
by two means: experimental measurement for the particulate matter and computational simulation for the air flow field
of the room. Experimental data showed that the particulate matters are much higher than the Hong Kong indoor air
quality objective value which is 0.180mg/m3 and simulation results showed that the particulates generated are
spreading everywhere within the room before extracted away by the HVAC system. In order to protect the occupants
inside the workshop, the HVAC system is proposed to be modified into a three-level negative pressure system.
Performance of the three-level negative pressure system is verified by CFD tool and result showed that the new HVAC
system can immediately extracted the contaminants away without contaminating the occupants inside.
Key words: particulate matters, indoor air pollutant, computational fluid dynamics, negative pressure system
INTRODUCTION
In the last several years, a growing body of scientific evidence has indicated that air at indoor environment can be more
seriously polluted than the outdoor air in even the largest and most industrialized cities [1].Most people are only aware
of outdoor air pollution but actually they have forgot that they spend over 80% of their time in indoor environment [2],
therefore, indoor air pollution has a very close relationship to human beings. Indoor pollution sources that release
contaminants, including both gases and particles, into the air are the primary cause of indoor air quality problems.
There are many types of indoor air pollutants such as particulates, formaldehyde, volatile organic compounds and
ozone, etc. When the concentration of these contaminants are accumulated to a certain high level in indoor
environment, the health of the occupants will be affected and poor indoor air quality can lead to discomfort, ill and
other health effects.
Particulate is one of the common contaminants found in the indoor environment and it can be classified into
microbiological particulates, animal and plant particulates combustion particulates, metallic and mineral particulates
[3]. Microbiological particulates include bacteria, virus mould and spores. Combustion particulates include tobacco
smoke, cooking fume, incense and heating appliances. Metallic and mineral particulates include asbestos, fibers, and
radioactive particulates. The health effect of particulates depends on size, shape and chemical composition of the
particulates. PM10 refers to particles less than or equal to 10 micrometers in diameter and these particles can penetrate
the upper regions of the body’s respiratory defense mechanisms [4]. This study investigates the problem of PM10 at an
industrial workshop and the suggested solution for it will be discussed.
In this study, an industrial workshop which will generate particles during the working process (polishing) is
investigated. In this workshop, many workers complaint that they got some health symptoms such as sore throat,
cough, eyes and nose irritation when they are working at the workshop and the symptoms will be relieved when they
left the workshop. Therefore, it is suspected that particulates have been generated during the working process and the
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level of them has reached a concerned level and so an investigation of checking the level of PM10 should be done.
Moreover, an investigation of the airflow path is performed to get an idea on the dispersion of the particulates and
check whether the particulates can be extracted successfully or not. The airflow path is investigated by measuring the
air velocity of the workshop and simulating the airflow field by computational software.
EXPERIMENTAL INVESTIGATION
The parameters measured in this study are respirable suspended particulates (PM10) and air velocity. The Dust-Trak air
monitor (Model 8520, TSI Inc.) which is working by the principle of light scattering is used to measure PM10. The air
velocity is measured by the Velocicalc Plus (Model 8386, TSI Inc.) which is working by the principle of thermal
sensor. The parameters are monitored for 2 hours continuously and carried out at 9:00 to 11:00 in the morning which is
the peak working hours for the workshop. According to the Hong Kong Indoor Air Quality Guideline [3], the
minimum sampling point is 1 per 500 m2 for the total floor area under 3000m2. As the floor area for this workshop is
576m2, 2 sampling points is to be conducted in this investigation. Since Macau does not have indoor air quality
guideline or standard, this investigation will take Hong Kong Indoor Air Quality Objective [3] as a reference for the
acceptance of the measured results.
The averaged value for the PM10 and air velocity from the measurement is shown in Table1. It can be observed that the
indoor PM10 is much higher than the reference value. Referring to the complaints of the symptoms from the workers
and the measured result, it can be shown that the workers are affected by the high concentration level of the particulates.
Therefore, investigation of the airflow pattern and the effectiveness of the HVAC system should be conducted.
Table 1 Averaged value for the measurement
NUMERICAL EXPERIMENT
The airflow pattern is investigated by simulation performed with the aid of Computation Fluid Dynamics (CFD)
technique. CFD is widely used in different kind of performance tests nowadays and it is applied in different fields such
as HVAC system, thermal comfort [5], distribution of indoor contaminates [6], fire and smoke modeling, etc. By using
this technique in the performance test, the architects and engineers can predict the performance of the designed system
in advance so that it can reduce the cost of further modification after the installation of it. There are many different
CFD software in the market such as Flovent, StarCD, Phoenics, CFX, FDS and Fluent. The one used in this numerical
experiment is Flovent.
Flovent is a commercial CFD software specially designed for modeling 3-D airflow, heat transfer and contaminants
distribution in buildings. In these simulations, Reynolds-averaged Navier Stokes equations are solved with finite
volume technique and turbulence effects upon the mean flow are modeled through the eddy viscosity concept. In this
study, steady state analysis is being simulated and the governing equations [7] used by the software are shown
followed.
where ρ (kg/m3) is density of air; ρr (kg/m3) is reference density of air; μ (kg/ m⋅s) is viscosity of air; Ui (m/s) is mean
velocity; ui (m/s) is fluctuating velocity; Cp (J/kg⋅K) is specific heat at constant pressure of air; λ (W/m⋅K) is thermal
conductivity;
is the Reynolds stress which is defined as:
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where
(kg/ m⋅s ) is turbulent viscosity; δij is Kronecker delta.
Turbulent viscosity,
(kg/ m⋅s), defined from dimensional analysis as:
where Cμ = 0.09; k is turbulent kinetic energy (m2/s2); ε ( m2/s3 ) is dissipation rate of k.
Transport equations for k and ε are:
where C 1 = 1.44; C2 = 1.92; C3 = 1.0; σ k = 1.0; σε = 1.217; P is shear production defined as:
G is production of turbulence kinetic energy due to buoyancy, and is given by:
is the effective viscosity; β is coefficient of volumetric expansion. However, since the
where
temperature field is not to be solved in these simulations so the temperature field is considered to be isothermal so G
will be equal to zero.
In order to test the reliability of the software, the air velocity of the workshop will be simulated so that the simulated
results will be compared with the experimental result.
SIMULATION FOR THE EXISTING SYSTEM
The simulated model is based on the real situation of the workshop in the existing system. The dimension of the
simulated volume is 24m × 17.4m × 5m as shown in Fig. 1 and the configuration is as close to the real situation as
possible. All the working tables and furniture are represented by cuboids with appropriate size and the cuboids in
brown colour represents the polishing machine which is the main source of particulates generated in this workshop.
Figure 1: 3-D model of the existing system
The simulated HVAC system is based on the real designed system which consists of fancoil units and an exhaust
system. The total exhaust rate is 4800 cfm and the flow rate of each fancoil unit is 1200 cfm. 256150 grids are used in
this simulated case and the grids are non-uniformly distributed where the area around the HVAC are used finer grids.
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Since the air flow path is the main concerned parameter for this simulation, the velocity field is to be simulated. The
simulations are terminated when the mass continuity residual (Ep), velocity residual (Eu, Ev, Ew) are reaching the
convergence criteria of Ep=10−4kg/s, Eu=10−3N, Ev=10−3N and Ew=10−3N. The simulations are run by a Pentium IV
2.4GHz personal computer with 512 MB RAM.
Fig. 2 shows the air velocity at the level of 1.1m high which is the height that the experimental measurement is done. It
can be seen that the simulated velocity is very close to the averaged measured velocity which is 0.06m/s and this
increases the reliability of this software.
Figure 2: The simulated results of the velocity field at the existing system
The airflow pattern of the workshop is represented by the velocity vector and particle movement. Fig. 3 shows the
simulated result of the velocity vector. The direction of the arrow shows the air flow direction and it can be seen that
the air coming out from the source is not directly flowing into the exhaust grilles. A clear pattern of airflow field can be
seen by the simulated result of the particle movement as shown in Fig. 4. It can be seen the particle is flowing
everywhere within the workshop before they are exhausted away. This explains why most of the workers inside this
workshop are affected by the high particulates.
Figure 3: Simulated result of the velocity vector for the existing system
Figure 4: Simulated result of the particle movement for the existing system
Since this workshop is designed to prevent the spread of the contaminants to other locations which are situated around
it, this workshop was designed to keep the room pressure at a negative status. Since air flows from place at high
pressure to low pressure place, therefore, air of this workshop which is at negative pressure cannot flow to the other
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places whose pressure is at positive pressure status. Even though this pressure system can protect the other workshops
and offices, the workers inside this workshop is affected by its high particulates. Therefore, it is necessary to protect
the workers by setting a pressure gradient within this workshop in order to control the flow path of contaminates. In
this case, a three-level negative pressure system is suggested to be used. Level 1 negative pressure is applied between
this workshop and the other workshops so that air is flowing from the other workshops to this workshop. This can
protect the occupants in other workshops. Level 2 and Level 3 are used to protect the workers inside this workshop.
Level 2 is applied to area where the workers are located. Level 3 negative pressure is the strongest one and it is applied
to area where the polishing machine are situated so that the particulates generated from the working process can be
extracted away immediately and will not contaminate the workers inside.
SIMULATION FOR THREE-LEVEL NEGATIVE PRESSURE SYSTEM
Before the application of the new HVAC system, the performance of it needs to be proved. However, doing a practical
experiment for it is not cost effective; therefore, the performance test is done by numerical experiment with the aid of
computational fluid dynamics (CFD) software.
The new designed HVAC system consists of 4 supply diffusers, 2 exhaust grilles for level 2 negative pressure system
and 9 exhaust grilles for level 3 negative pressure system as shown in Fig. 5. The whole workshop is setting to be
negative pressure relative to its surrounding area and this is the level 1 negative pressure and this is done by setting the
total exhaust rate of the workshop to be larger than the total supply rate. The level 2 negative pressure consist of 2
exhaust grilles whose flow rate is 300cfm each and located at the area that the workers are located. Level 3 negative
pressure system is set by 9 exhaust grilles which are located above the sources. Each exhaust grille of this level is
having 600 cfm which are the strongest among all the exhaust grilles.
Figure 5: Top view of the 3-level negative pressure system
Fig. 6 shows the simulated result of the velocity vector for the three-level negative pressure system. It can be observed
that the vectors from the source are directly flowing towards the exhaust grilles. Fig. 7 is the simulated result of the
particle movement, it can be observed that the particles generated are immediately exhausted away without affecting
the workers. By comparing the simulated results between the existing system (Fig. 4) and three-level negative pressure
system (Fig. 7), the retrofit of the HVAC can successfully control the airflow direction.
Figure 6: Simulated result of the velocity vector for three-level negative pressure system
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Figure 7: Simulated result of the particle movement for three-level negative pressure system
CONCLUSION
An investigation of respirable suspended particulates (PM10) for an industrial workshop has been performed in this
study by two means: experimentally and numerically by computational fluid dynamics (CFD) technique. Experimental
result showed that the PM10 level was much higher than the reference value and the numerical result showed that the
particulates cannot extract away successfully so that the workers inside this workshop were affected by these
particulates. A three-level negative pressure system which can protect both the workers of other workshops and the
workers inside this industrial workshop are suggested to be used. Simulation result showed that this three-level
negative pressure system can successfully control the flow path of the particulates which in turn protect the workers
from affected by the particulates. From this study, it can be shown that the CFD technique is a good tool for analyzing
the PM10 and airflow path especially at the design phase since the performance can be predicted and optimized to the
best setting before the installation of the HVAC system.
REFERENCES
1. United States Environmental Protection Agency and the United States Consumer Product Safety Commission
Office of Radiation and Indoor Air (6604J). The Inside Story: A Guide to Indoor Air Quality. EPA Document
#402-K-93-007, USA, 1995.
2. Waden RA, Scheff PA. Indoor Air Pollution: Characterization, Prediction and Control. Wiley-Interscience
Publication, 1983.
3. The Government of the Hong Kong Special Administrative Region Indoor Air Quality Management Group.
Guidance Notes for the Management of Indoor Air Quality in Offices and Public Places. 2003.
4. The Particle Pollution Report: Current Understanding of Air Quality and Emissions through 2003. United
States Environmental Protection Agency, 2003.
5. Sin VK, Sun HI, Tam LM, Wong KI. Numerical experiment of thermal comfort in a bedroom equipped with
air-conditioner. Proceedings of the Ninth International Conference on Enhancement and Promotion of
Computational Methods in Engineering Science, Macau, China, 2003, pp. 787-794.
6. Sin VK, Sun HI. A numerical investigation of indoor air quality with CFD. Korea Society of Computational
Fluids Engineering, Journal of Computational Fluids Engineering, 2005; 10(1): 87-93.
7. Flovent Reference Manual. FLOVENT/OL/MM/0801/1/0, Flomerics Ltd, 2001.
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