Radiation Environment and Medicine 2022 Vol.11, No.2 61–65

ReportUtilization of Computational Fluid Dynamics Simulation for Gas
Exposure Chamber
Kazuki Iwaoka1*, Miroslaw Janik1, Yuki Tamakuma1, 2, Masahiro Hosoda3,Shinji Tokonami3 and Reiko Kanda1
1National Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan
2
Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan3
Hirosaki University, 66-1 Honcho, Hirosaki, Aomori 036-8564, Japan
Received 22 December, 2021; revised 10 February, 2022; accepted 18 February, 2022

Testing devices and measuring physical parameters are often carried out in gas chambers.
However, if the environmental conditions (e.g. gas concentration) inside the chamber isinhomogeneous, we may expect incorrect results of experiment. Confirmation of the gas
distribution in various environmental conditions is an important problem in the design of thechamber. For checking the gas distribution, a theoretical approach using the computational fluid
dynamics (CFD) simulation can be relatively-easily used. The article demonstrates the utilizationof numerical calculations based on the CFD simulation for the analysis of gas uniformity in thevirtual chamber.
Key words: gas, chamber, exposure

1. Introduction
Gas exposure chambers are often used for testing andexperimenting gas measuring instruments under various
exposure conditions1-3). However, if the environmentalconditions (e.g. gas concentration and temperature) inside
the chamber are spatially uneven, incorrect results intesting and experimenting for gas measuring instruments
may occur. Therefore, it is important to check whether
the environmental conditions in the chamber are
homogeneous in different exposure scenarios.
Two approaches to checking chamber homogeneity
can be considered: 1) experimental, using passive typedevices that do not interfere with the chamber operation;*Kazuki Iwaoka: National Institutes for Quantum Science and Technology, 4-9-1
Anagawa, Inage, Chiba 263-8555, Japan
E-mail: iwaoka.kazuki@qst.go.jp
https://doi.org/10.51083/radiatenvironmed.11.2_61
Copyright © 2022 by Hirosaki University. All rights reserved.

2) theoretical, using the computational fluid dynamics(CFD) simulation. The experimental approach makes
it possible to check the homogeneity of the chamberbased on the variability of data from passive type devices
installed in the chamber, while it can be relatively heavy
work in terms of time and cost. On the other hand, thetheoretical approach with CFD simulations is relatively
easy to perform, which has been presented in this paper.
In the present work, distribution of gas in the exposure
chamber is numerically simulated by using open source
CFD toolbox, OpenFOAM version 8.
2. Computational fluid dynamics simulation
Nowadays computational fluid dynamics (CFD) provides
the state-of-the-art capabilities of simulating the gas
distribution in the exposure chambers. In this study, anOpen source OpenFOAM toolbox4) was applied because
it allows to easily implement a complex physical model.

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Kazuki Iwaoka et al./ Radiation Environment and Medicine 2022 Vol.11, No.2 61–65(a)Fig. 1. Schematic of the virtual exposure chamber.

(a)

(b)

(b)

Fig. 3. The collimator-2 in this study (a: schematic of the virtual
exposure chamber with the collimator-2; b: shape of the collimator-2).

3. Demonstration of the calculation

Fig. 2. The collimator-1 in this study (a: schematic of the virtual
exposure chamber with the collimator-1; b: shape of the collimator-1).

OpenFOAM has extensive capabilities, including models
for transport, turbulence, thermodynamics, chemicalreactions, particle flows, surface films etc. While it isopen source architecture where complete source code isavailable to all users, it can be customized and extended
at no cost. The 2D and 3D figures with simulated results
can be presented using ParaView5) software.

3.1. Calculation condition
To illustrate CFD modeling, a virtual concentration (i.e. apassive scalar) was used as an indicator of diffusion in thefluid. Passive scalar is a scalar quantity that is not activelyinvolved in the flow physics of the CFD simulation. Theequation governing transport of the passive scalar isexpressed as follows:∂C/∂t +∇• (UC)−∇2 • (DC) = 0(1)where C is the passive scalar concentration, U is thevelocity, D is the diffusion coefficient and t is the time6).
In the present work, the virtual gas exposure chamberfor CFD simulation was set to the size of 1 m×1 m×1 m (1 m3), as shown in Figure 1, with reference to thestructure of actual radioactive gas exposure chambers
located on the National Institutes for Quantum Scienceand Technology (QST) and Hirosaki University7, 8). Two
different configurations with collimators, as shownin Figure 2 (collimator-1) and Figure 3 (collimator-2),
were used to calculate the gas distribution in the virtualchamber. The simulations were performed by using air

Kazuki Iwaoka et al./ Radiation Environment and Medicine 2022 Vol.11, No.2 61–65

63(b)

(a)

Fig. 4. Sampling points for data on the passive scalar concentration (a: y-z plane; b: x-y plane).

(a)

(b)

Fig. 5. The passive scalar concentration in the elapsed time (Slice in the middle of the x axis) (a: with the collimator-1; b: with the collimator-2).

(a)

(b)

Fig. 6. The z-axial air flow velocity in the elapsed time (Slice in the middle of the x axis) (a: with the collimator-1; b: with the collimator-2).

(C = 1 (-)) with volumetric flow rate at 30 LPM. Air wasforced through the inlet on the right side of the chamberand blown out through the outlet on the left side of thechamber. Drawing these structures were performed bya CAD software. As initial conditions, the gravitational
acceleration and temperature inside the chamber was set
to zero and 300 K, respectively. The boundary conditionsof collimators and walls in the chamber were set to beadiabatic. The spatial mesh size was set to be 0.05×0.05×0.05 m for the whole region and 0.0125×0.0125
×0.0125 m for the collimator and hole regions, withcorrection of arc shape. A web-based preprocessor forOpenFOAM was used to create calculation files under
the above conditions9). The passive scalar concentration

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Kazuki Iwaoka et al./ Radiation Environment and Medicine 2022 Vol.11, No.2 61–65(a)

was obtained for the elapsed time (t) from 0 to 60 min,with the 1 second step. In order to assess of concentration
distribution inside the chamber, the Relative Standard
Deviation (RSD = SA / C A) was used in this study, whereC A and S A are the passive scalar average concentrationand standard deviation, respectively. The RSD wascalculated using data comes from 27 sampling points
which were chosen selectively, as shown in Figure 4.
3.2. Calculation result
Using calculated data, heat maps of the passive scalar
concentration and the z-axial air flow velocity against
elapsed time (t e) under two conditions, i.e., with thecollimator-1 and with the collimator-2, are presented inFigures 5 and 6, respectively. As a result of the simulation,differences in the space-time evolution of passive scalar
concentrations between collimator-1 and collimator-2 wereobserved. In the case of the collimator-1 the passive scalar
concentration at the air inlet on the right was transported
towards the z-axis within 10 minutes and then propagatedin the volume of the chamber, while the passive scalar
concentration through the collimator-2 at the air inlet
on the right was propagated upward in 10 minutes andthen transported in the z direction. The differences canbe explained by two reasons: 1) the air flow velocity
through the collimators, because the air flow velocity
through the collimator-1 was faster than that through thecollimator-2 and 2) the number of holes for air passage on
the collimators, i.e. the collimator-2 had more air passage
holes than the collimator-1.
The values of average concentration and RSD at eachsampling point are shown in Figure 7. It can be observedthat the values of RSD with the collimator-1 were
initially lower than those with the collimator-2, whileboth values reached C A < 0.1 in 60 minutes. The averagegas concentration in the chamber with the collimator-2
changed significantly with time compared to the chamberwith the collimator-1 and reached C A > 90% of thesaturation within 60 minutes. According to these results,
it is suggested that the design and selection of collimator
are one of the important factors for gas distribution inside
the chamber.
4. Future WorkIn general, direct measurements, which is the bestsolution, should be conducted f or checking thedistribution of the gas in the exposure chamber. However,direct measurements are not reasonable from a costeffectiveness and time-efficient perspective when it isobvious that the distribution of the gas in the exposure
chamber is homogeneous (e.g, when the convection
velocity in the exposure chamber is large). In such acase, the CFD simulation proposed in this study looks(b)Fig. 7. Average and RSD for the passive scalar concentration at 27
sampling points (a: average; b: RSD).

promising especially. We plan to conduct further researchin terms of the possibility of using CFD simulations
in various situations, including the development andimprovement of a simple small radioactive gas chamber10).
Such efforts are eventually expected to contribute theoptimal selection of gas chamber design parameters (e.g.
size, inlet and outlet velocity) depending on the desired
level of uniformity.
Disclosure
The authors declare that they have no conflicts ofinterest.
Author Contribution
Kazuki Iwaoka performed the study and wrote themanuscript. All authors contributed extensively in thediscussion of the work and the review of the manuscript.
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