000			03541nam a22003017a 4500
999			_c110983 _d110983
003			IE-CoIT
005			20180522083331.0
007			ta
008			180307s2017 ie ||||| |||| 00| 0|eng||
040			_aIE-CoIT
082	0	4	_aTHESES PRESS
100			_aBaker, Nazar H. _9123857
245	1	0	_aInvestigating the parameters that influence the particle mass concentration rates in a grade C cleanroom / _cNazar Baker.
264		1	_aCork : _bCork Institute of Technology, _c2017.
300			_axv, 154, xvi pages : _bcolor illustrations, graphs ; _c30 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490		0	_aPh.D - Mechanical, Electrical & Processing Engineering
500			_aThe cleanroom design engineers use the guidelines tables, in which the Air Change Rates (ACHs) are determined based on the room cleanliness class. These guidelines are based on experience and do not fully address many other critical variables that influence the particulate level and particle distribution. These simplified approaches could often cause significant energy waste. In the last five decades, a number of mathematical models were developed to determine the airflow required in cleanrooms. As a consequence of the approximation of many critical variables in these models, these models can only be used as a qualitative indicator of the airflow required due to approximation. As a result of the lack of accurate mathematical models, these guidelines are still in operation today. The main objective of this work is to quantitatively investigate the most significant variables that influence the particulate concentration levels inside a grade C cleanroom using Computational Fluid Dynamics (CFD) techniques. The CFD model was developed and verified using the Grid Independence Index method (GCI). The accuracy of the Eulerian-Lagrangian simulation was evaluated by comparison with published experimental data. In achieving this objective, the European Union Guide to Good Manufacturing Practice (EU GGMP) has been adopted by imposing constraints on the CFD models variable parameter space. The method involves, the definition of a reduced parameter state space using both Dimensional Analysis Buckingham - theorem, and Design of Experiment (DOE). Statistical software "Minitab17" was used to generate the design matrix, as well as, to develop the response mathematical model. The work completed in this thesis shows that the particle mass concentration rate in the model room can be controlled by a number of parameters depending on the particle size. For fine particles of size 0.5 um the particle mass concentration rate can be controlled by varying the inlet supply and outlet exhaust configurations. For a coarse particle of size 5.0 um diameter, the gowning regimes, as well as the location of the outlet exhausts in terms of high or low sidewall level, play a significant role in reducing the particle mass concentration in the room. Also, it was found that the effectiveness of increasing the inlet air velocity in reducing the particle mass concentration rate depends on the outlet exhaust locations at a sidewall level and particle density - (Thesis abstract)
502			_aThesis. _b(Ph.D) - _cCork Institute of Technology. _d2017.
504			_aIncludes bibliographical references.
650		0	_935386 _aClean rooms
650		0	_972077 _aComputational fluid dynamics
650		0	_940816 _aParticles
650		0	_943722 _aVentilation
942			_2ddc