Computational Study of Contaminant Control by Multi-slotted Hoods in

Proceedings of Clima 2007 WellBeing Indoors

Computational Study of Contaminant Control by Multi-slotted Hoods in an Industrial Exhaust System Ali Bahloul¹, Mauricio Chavez², Marcelo Reggio² ¹Institute IRSST, Canada ²Ecole Polytechnique de Montreal, Canada. Corresponding email: [email protected]

SUMMARY The subject of this paper is the numerical simulation of the capture of contaminants with a local exhaust system. The objective is to evaluate the influence of multi-slotted hoods on the capture efficiency and its impact on indoor air quality. The ventilation in the proximity of slots and the contaminant dispersion throughout the room were predicted using the commercial tool “Fluent”. Characteristics of the polluted air were examined for different geometrical opening configurations for a two-dimensional model. Two parameters were examined: the number of slots and the slot width. Two-dimensional simulations revealed that, at a constant volumetric exhaust flow rate, a gradual reduction in contaminant concentration is experienced throughout the room as the number of slots increases. It was found that there is an optimal number of slots that reduces this concentration to 12% compared with a nonslotted hood system. The slot width analysis also revealed the existence of an optimum value for which the contaminant reduction is maximal. Following this basic assessment, computations were performed on a more realistic, three-dimensional model. These preliminary calculations indicate that flow computations need to be three-dimensional to address real-life situations more accurately.

INTRODUCTION Industrial exhaust ventilation systems are used to remove airborne contaminants consisting of particulates, vapor and gases, all of which can create an unsafe, unhealthy or undesirable atmosphere for workers. There are two types of exhaust systems: general exhaust ventilation (GEV), in which an entire work space is exhausted without considering any specific operation; and local exhaust ventilation (LEV), in which the contaminant is controlled at its source [13]. In the industry, LEV is the preferred method because the flow rates, and therefore the costs, are lower than in GEV. Moreover, with GEV only, it may be difficult to achieve the high level of contaminant control that is needed to reduce the worker’s exposure near a contaminant source. The main concept used in an LEV to select the adequate volumetric flow to with draw air through a hood is the capture velocity. This is the velocity of the air at the point of contaminant generation. The contaminant enters the moving air stream at the point of generation and is conducted along with the air into the hood. Traditionally, the design of LEV hoods is based on the empirical velocity formulas [4,13] that give the capture velocity profile at the front of the hood. While useful, this method does not quantitatively take into account the effects on the efficiency of the LEV of the momentum of the contaminant source, disruptive air currents and obstacles in the flow field. For this reason, a better option is to study indoor air quality using computational fluid dynamics (CFD), because CFD is capable


of providing information on factors such as the distribution of flow and concentration at all grid points, independently of the complexity of the geometry. The single rectangular slot is highly applied since it is very efficient for capturing large amounts of contaminants. CFD has been used on this type of slot to assess the performance of LEV systems and to define new design guidelines [1,8,10]. Kulmala [2] investigated the accuracy of the numerical simulation of an air flow field generated by a rectangular exhaust opening. The calculations were made using the standard k-ε model, and the results were verified with laser Doppler measurement. Multi-slotted hoods are often used on exhaust systems, and it is widely excepted that the slots only help to distribute air over the hood face and do not influence capture efficiency. In this paper, we use CFD to analyze the influence of slot number and slot width on capture efficiency. We first examine the effectiveness of the multi-slotted hood in a 2-D model, and then we apply similar concepts to the 3-D case of a worker positioned near a contaminant source. BASIC GEOMETRY The 2-D room geometry, including a hood configuration with 6 slots, is depicted in Fig. 1 (not to scale). The contaminant source is considered to spread material over a surface 2 m in length. The area to be studied is near the hood, and the dimensions of the room have been increased to impose boundary conditions (BC) that will not affect the region of interest. 6 7

18 m exhaust 1m

1

5

slots

2

source of contaminant 0.1 m 3 1m 4 1m

2m

18 m

Figure 1: Geometry with slots. NUMERICAL METHOD Governing Equations The aim of the numerical prediction is to solve the governing set of partial differential equations representing an isothermal incompressible flow without buoyancy effects. The equations that describe the flow of a fluid, heat and concentration within an enclosure are based on the conservation of mass, momentum, energy and species concentration. The general form of transport equation for property Φ is:

∂ ⎛ ∂Φ ⎞ ∂ ( ρΦ ) ∂ ⎟ + S Φ ; i=1, 2, 3 ⎜ ΓΦ + ( ρΦ U i ) = { ∂xi ⎜⎝ ∂xi ⎟⎠ Source ∂t3 ∂xi 12 1 42 43 1 42 4 43 4 Transient Convection

Diffusion


In this expression, ρ represents the density of the fluid, ΓΦ the diffusion coefficient, SΦ the source term and U i the velocity components along the xi coordinates. From this general form, the Navier-Stokes, energy and species concentration equations can be obtained. Namely: Conservation of mass:

∂ρ ∂ρU i + =0 ∂t ∂xi

Conservation of momentum: ∂ ∂P ∂ρU ∂ (ρU iU j ) + =− + ∂xi ∂x j ∂x j ∂t

⎛ ∂U i ⎜μ ⎜ ∂x j ⎝

⎞ ⎟ + g i (ρ − ρ 0 ) ⎟ ⎠

Conservation of energy: ⎞ ⎛ ∂ρH ∂ (ρU i H ) = ∂ ⎜⎜ λ ∂T ⎟⎟ + ∂P + ∂t ∂xi ∂xi ⎝ ∂xi ⎠ ∂t

Conservation of species: ∂ (ρU i C ) = ∂ ⎛⎜⎜ D ∂C − ρ μ i c' ⎞⎟⎟ ∂xi ∂xi ⎝ ∂xi ⎠

where P , H , T , μ , g , λ , C and D denote pressure, enthalpy, temperature, dynamic viscosity, gravity acceleration, thermal diffusivity, concentration and molecular diffusivity respectively. The contaminant used in this study is a gas. To handle turbulence, the renormalization group (RNG) k − ε was selected. The SIMPLE algorithm was used for the pressure-velocity coupling. Boundary conditions and meshing aspects are discussed in the next section. Grid and boundary conditions

In order to obtain a numerical solution of the above equations, a descretization of the room is required, followed by the application of a solver. Because solutions will be sought using the commercial package Fluent, the companion software Gambit was applied to generate the grid. Based on the topology room and of the slotted hood, hybrid grids, both structured and unstructured, were applied. An adaptive mesh refinement algorithm around the slots was employed, which permits a more accurate representation of the boundaries. In order to compute a solution, boundary conditions need to be applied. In this study, the most relevant parameter is at the exhaust boundary. To enforce an adequate exhaust mass flow rate, an adequate capture velocity must be established. Based on successful experiments, ASHRAE [13] proposes ranges of capture velocities for several industrial operations under specific conditions of contaminant dispersion. In this case, we consider the contaminant source as an evaporation tank, which means that the contaminant is released into still air with essentially no velocity. The proposed capture velocity range is 0.25 – 0.5 m/s [13]. To ensure the corresponding exhaust mass flow rate, the transport equations were solved several times until a velocity of 0.35 m/s was obtained at a reference point. This was located 1 m from the hood face and 0.5 m above the surface of the source of contaminant. At the outlet (side 1 in Fig 1), a mass flow rate of 0.1 kg/s was imposed. This same rate was also imposed at the inlet (side 5). Solid walls were considered on all the other surfaces. A


constant standard temperature of 300o K was considered at both the inlet and the outlet. All solid walls where considered to be adiabatic. Table 1 summarizes the boundary conditions.

1 2 3 4,6,7 5

Table 1: Boundary Conditions Exhaust Mass flow - outlet = 0.1 kg/s Hood slots Wall - adiabatic Contaminant source Wall - adiabatic with diffusion flux. Mass fraction = 1 Wall Wall - adiabatic Inlet Mass flow - inlet = 0.1 kg/s

Below, we present the solution of the governing equations for 2-D and 3-D geometries using the commercial package Fluent [11]. 2-D CALCULATIONS

These calculations were carried out to assess the impact of the number of slots and the slot width. Influence of the number of slots

This test is quite simple and involves conducting computations of hood performance by changing the number of openings at the hood inlet. Fig. 2 shows iso-values of species concentration for various numbers of slots for a constant outlet mass flow rate of 0.1 kg/s. Although this qualitative view indicates better suction with the increase in the number of openings, a quantitative analysis is required. This result is illustrated in Fig. 3, where the total mass of the contaminant in the entire room has been plotted against the number of slots. Based on this simple representation, it appears that the optimum outcome corresponds to 6 slots, and that a further increase in their number does not help to reduce the species concentration. On the contrary, it amplifies it.

a) open

b) two slots

c) four slots d) six slots Figure 2: Iso-values of species concentration. The outlet mass flow rate is constant, at 0.1 kg/s.

Figure 3: Mass integral of contaminants for various numbers of slots.

Influence of slot width

A second test was conducted to analyze the impact of slot width on species concentration. Only the case of a hood with two slots was studied.


a) slot width = 0.3 m

d) slot width = 0.2 m

g) slot width = 0.1 m h) slot width = 0.07 m Figure 4. Iso-values of contaminant concentration for slot widths of 0.3, 0.2, 0.1 and 0.07 m.

Figure 5: Mass integral of contaminants for the variation in slot width.

Again, this is a naïve test, in which the slot width varied from 0.3 m to 0.03 m. As in the previous test, Fig. 4 shows the simulation results by means of iso-values of concentration. As expected, the differences are noticeable behind the hood inlet. However, what is needed is quantitative information on the room. This is presented in Fig. 5 as the total contaminant in terms of slot width. The curve indicates that the slot width plays an obvious role, and that the optimum width is 0.1 m. Using these results as a basic platform, we proceeded with 3-D modeling. 3-D MODELING

Because a 2-D world corresponds to “a slice” of a 3-D geometry, a first calculation in three dimensions was carried out by considering a wall-to-wall hood with various numbers of slots. Thus, a vertical plane passing through the middle of the hood corresponds to the 2-D world previously analyzed. An illustration of this idea is shown in Fig. 6, where iso-values of the species concentration obtained when using four slots are shown. As expected, these results coincide with the 2-D calculations.

Figure 6: Contours of the mass Figure 7: Meshing the worker and the hood. fraction of the contaminant at midplane. After completing this basic verification, a more realistic geometry was considered (Fig. 7), which includes a mannequin positioned near contaminants released from the horizontal surface and controlled by a lateral hood. In this type of 3-D modeling, mannequins have been


introduced ([5] [6]) to investigate numerically the influence of different body shapes on the exhaust efficiency. In these studies, it was found that the use of such a simplified human body is satisfactory when focusing on the global airflow pattern in a ventilated room. In our study, the model is intended to closely represent an actual worker standing in a particular spot. With this more realistic shape, the airflow pattern around the human body may also be addressed. Because there are many possible locations for the person, a position facing the grid exhaust was chosen for a preliminary test. Fig. 8 shows qualitative results by means of path lines near the hood colored according to the mass fraction concentration. Details around the body are shown in Fig. 9, where the swirling nature of the flow in front of the face can be appreciated.

Figure 8: Path lines colored by the mass fraction of the contaminant.

Figure 9: Path lines near the mannequin colored by the mass fraction of the contaminant.

Quantitative results are displayed in Fig. 10, where the total mass integral of the contaminant is shown against the number of slots.

Figure 10: Total mass integral of the contaminants for different numbers of slots. This particular configuration for a mannequin facing the hood shows a similar behavior to that found for the 2D case; that is, a predicted ideal number of slots to achieve a better configuration of the contaminant’s control system.


Note that the number of slots calculated (4) is not the same as that found in the 2-D analysis (6). This has been attributed to two factors: first, the width of the hood, for which the lateral effects do not exist in 2-D; second, to the presence and position of the worker, which were not considered in the 2-D analysis either. From this particular result, it becomes apparent that more elaborate 3-D investigations need to be carried out. CONCLUSION

Two- and three-dimensional studies where conducted using CFD to investigate the benefit (12% concentration reduction) of slotted hoods in controlling contaminant levels in working environments. The commercial software Fluent was used to perform the simulations. An optimum number of slots to reduce the contaminant concentration was found in both cases. Differences in the predicted number of slots indicate that hood size and the presence and position of a worker require a variety of 3-D calculations to assess the impact of the number of slots in more realistic situations. ACKNOWLEDGMENT

The authors are grateful to the Institut de Recherche Robert-Sauvé en Santé et Sécurité du Travail for providing the necessary support to carry out this work. REFERENCES [1]

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