Numerical study of particulate turbulent flow to investigate recovery period in cleanrooms

Document Type : Article

Authors

Faculty of Mechanical Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-143, Iran

Abstract

The Clean room is a controlled space and is used in various industries such as electronics, medical and military industries. One of the most important tests to evaluate the performance of the cleanroom is recovery test. Recovery test determines the time period during which a clean room returns to its designated cleanliness level after an instant or a period of deliberate or unintentional contamination. In this paper, a thorough investigation of recovery period has been implemented. In this study, air change rate and its pattern were studied using the Eulerian and Lagrangian approaches and LES, DES and k-ω SST turbulent models. Simulation results were evaluated against control volume analysis. Parameters such as the air change rate, the number of particles, and pressure and energy consumption in various radial and tangential angles of diffusers were studied Results showed that radial angle had little positive and occasionally negative effect on recovery period. On the contrary, tangential angle improved decontamination rate, at maximum performance (β=45°), it could reduce recovery period as much as 25% which in turn reduces energy consumption. In addition the DES model provides the best and most coinciding answers between all turbulence models.

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References:
1. Lage, J., Bejan, A., and Anderson, R. "Efficiency of transient contaminant removal from a slot ventilated enclosure", International Journal of Heat and Mass Transfer, 34, pp. 2603-2615 (1991).
2. Lage, J., Bejan, A., and Anderson, R. "Removal of contaminant generated by a discrete source in a slot ventilated enclosure", International Journal of Heat and Mass Transfer, 35, pp. 1169-1180 (1992).
3. Mendez, C., San Jose, J., Villafruela, J., and Castro,F.  "Optimization of a hospital room by means of CFD for more efficient ventilation", Energy and Buildings, 40, pp. 849-854 (2008).
4. Saidi, M., Sajadi, B., and Molaeimanesh, G. "The effect of source motion on contaminant distribution in the cleanrooms", Energy and Buildings, 43, pp. 966- 970 (2011).
5. Chen, S.-C., Tsai, C.-J., Li, S.-N., and Shih, H.-Y. "Dispersion of gas pollutant in a fan-filter-unit (FFU) cleanroom", Building and Environment, 42, pp. 1902- 1912 (2007).
6. Khoo, C.Y., Lee, C.-C., and Hu, S.-C. "An experimental study on the influences of air change rate and free area ratio of raised- floor on cleanroom particle concentrations", Building and Environment, 48, pp. 84-88 (2012).
7. Wang, M., Lin, C.-H., and Chen, Q. "Advanced turbulence models for predicting particle transport in enclosed environments", Building and Environment, 47, pp. 40-49 (2012).
8. British Standard institution, BS EN ISO 14644, in Cleanrooms and Associated Controlled Environments - Part 2: Specifications for Testing and Monitoring to Prove Continued Compliance, Ed., UK (2000).
9. British Standard institution, BS EN ISO 14644, in Cleanrooms and Associated Controlled Environments - Part 1: Classification of Air Cleanliness, Ed., UK (1999).
10. Chung, K.-C. and Wang, S.-K. "Study of appropriate indoor air quality models in the Taiwan area", Indoor and Built Environment, 3, pp. 149-155 (1994).
11. Sabatini, L., Analysis of Airborne Contamination  istribution in Mixed Flow Cleanroom and Consequences in the Control Techniques, Lesatec S.r.l. (2005). 
12. Graebel, W., Advanced Fluid Mechanics, pp. 1-16, Academic Press (2007).
13. Rouaud, O. and Havet, M. "Computation of the air  flow in a pilot scale clean room using K-" turbulence models", International Journal of Refrigeration, 25(3), pp. 351-361 (2002).
14. Zhang, Z. and Chen, Q. "Comparison of the Eulerian and Lagrangian methods for predicting particle transport in enclosed spaces", Atmospheric Environment, 41, pp. 5236-5248 (2007).
15. Menter, F.R. "Review of the shear-stress transport turbulence model experience from an industrial perspective", International Journal of Computational Fluid Dynamics, 23, pp. 305-316 (2009).
16. Menter, F.R. "Two-equation eddy-viscosity turbulence models for engineering applications", AIAA journal, 32, pp. 1598-1605 (1994).
17. Fard, M.B. and Nikseresht, A. "Numerical simulation of unsteady 3D cavitating  flows over axisymmetric cavitators", Scientia Iranica, 19, pp. 1258-1264 (2012).
18. Heidarinejad, G. "Turbulence" , pp. 3-163, Author, IR (2009).
19. Wilcox, D.C., Turbulence Modeling for CFD, pp. 63-163, DCW industries La Canada, CA (1998).
20. Nikbakht, A., Abouali, O., and Ahmadi, G. "Nanoparticle beam focusing in aerodynamic lenses-an axisymmetric model", Scientia Iranica, 14, pp. 263-272 (2007).
21. Zhang, P., Roberts, R.M., and Benard, A. "Computational guidelines and an empirical model for particle deposition in curved pipes using an Eulerian- Lagrangian approach", Journal of Aerosol Science, 53, pp. 1-20 (2012).
22. Friedlander, S.K. and Smoke, D., Haze: Fundamentals of Aerosol Dynamics, Oxford University Press, US (2000).
23. Tominaga, Y. and Stathopoulos, T. "Turbulent Schmidt numbers for CFD analysis with various types of flowfield", Atmospheric Environment, 41, pp. 8091- 8099 (2007).
24. Lu, W., Howarth, A.T., Adam, N., and Riffat, S.B. "Modelling and measurement of air flow and aerosol particle distribution in a ventilated two-zone chamber", Building and Environment, 31, pp. 417-423 (1996).