1. Improving and Trouble Shooting CleanroomHVAC System Designs By George Ting-Kwo Lei, Ph.D. Fluid Dynamics Solutions, Inc. Clackamas, Oregon

2. Outline • Introduction to cleanroom HVAC design • Introduction to Computational Fluid Dynamics (CFD) and its applications • A case study: Examination of flow laminarity of a cleanroom with a subfab underneath • A case study: Computer aided design of chemical exhaust systems for vicinity near I/O of an implanter. • A case study: Computer aided design improvement of a duct transition • A case study: Size reduction of the vortexes behind equipment • Conclusions

3. Introduction to cleanroom HVAC design • Primary functions of cleanroom HVAC systems • Provide filtered supply air at sufficient flow rate and with effective flow patterns to reach a specified class of cleanliness. • Provide filtered outdoor air for occupants and equipment. • Exhaust effectively unwanted chemicals. • Maintain specified cleanroom pressure. • Add or remove moisture to regulate cleanroom humidity. • Add or remove thermal energy to regulate cleanroom temperature.

4. Types of cleanroom flow • Conventional type of cleanroom flow • Unidirectional flow • Mixed type of cleanroom flow • Minienvironment • Types of Cleanroom layout • Ballroom type • Service chase type • Minienvironment type

5. Conventional type of cleanroom flow Air Supply Critical zone Air Exhaust

6. Unidirectional flow Air Supply Critical zone Air Exhaust

7. Mixed type of cleanroom flow Air Supply Critical zone Air Exhaust

8. Minienvironment Air Supply Critical zone Air Exhaust

9. Ballroom type Service area Office and Support area Cleanroom

10. Service chase type Service area Office and Support area Cleanroom

11. Minienvironment Minienvironment type Service area Office and Support area Cleanroom

12. Primary cleanroom HVAC system design parameters • Energy efficiency • Cleanliness • Cost • Temperature uniformity • Humidity control • Chemical exhaust efficiency • Noise control • Make up air supply

13. Methods to improving cleanroom HVAC system design Combinations of the following approaches • Analysis of experimental data • Rules of thumbs and Experiences • Empirical equations • Computational Fluid Dynamics or so called Air Flow Modeling

14. Common problems of a wrongly designed cleanroom HVAC system • Insufficient air flow • Inadequate laminarity • Fail to pressurize to specified pressure level • Local stagnition near point of service • Big stagnition zones • Ineffective chemical vapor exhaust • Too high noise • Temperature variation above specifications • Humidity variation above specifications

15. A case study: Examination of flow laminarity of a cleanroom with a subfab underneath Floor Ceiling CFD model geometry FAB CHASE SUBFAB Slab

16. 8’ • An example of a wrong design and method of trouble shooting 24’ 24’ 16’ 10’ Notes: 1. Flow rate of each RAU, 21,312 cfm 2. 100 % coverage Initial design

17. 8’ 22’ 16’ 18’ 18’ Notes: 1. Flow rate of each RAU, 21,312 cfm 2. 100 % coverage Improved design

18. Comparison of two designs • Pressure drop across the plenum excluding HEPA filter • Initial Design: 0.6 inches of water • Improved Design: 0.3 inches of water • Energy savings for a 2 system running 2 inches of water (0.6-0.3)/2.0 = 15% • Avoid Failure of system air performance

19. Introduction to Computational Fluid Dynamics (CFD) and CFD Applications • Navier-Stokes Equations

20. Divide solution domain into finite cells. • Formulate CFD equations by Finite Volume or Finite Element method. • Solve CFD equations by a digital computer.

21. CFD Assumptions • Assumptions are often necessary when formulating CFD equations. • Examples of assumptions Flow entrances Flow exits Filters Perforated plates Turbulent models Computer model geometry

22. Comparison among Various Cleanroom HVAC System Design Methods • Rules of thumb Advantages: Designs are done very quickly and inexpensively. Disadvantage: Rules are very general and may require large safety margins to ensure that the design is successful. • Empirical equations Advantages: The equations can be used to quickly predict conventional usage of the design. Disadvantages: When the parameters of the design vary, the uncertainties of solutions can often be significant.

23.  Physical Modeling Advantages: Designer can see and feel the environment governed by this design. Disadvantages: Expensive. • Computational Fluid Dynamics (CFD) Advantages: (1) Less expensive compared to physical modeling. (2) May sometimes predict some potential design flaws so that they can be remedied before the facility is constructed. (3) May quickly explore possible opportunity for improved performance. (4) Can model a variety of options for both planned and operating designs so that the most economical solutions can be pursued with a high degree of confidence in their validity. Note: In some applications, physical modeling is still required after flow modeling. However, flow modeling can reduce the number of prototypes.

24. A case study: Examination of flow laminarity of a cleanroom with a subfab underneath Floor Ceiling CFD model geometry FAB CHASE SUBFAB Slab

25. Flow pathlines for the case with 35% floor peroration ft/min.

26. Flow angles for the case with 35% floor peroration degree

27. Flow pathlines for the case with 20% floor peroration ft/min.

28. Flow angles for the case with 20% floor peroration degree

29. Flow pathlines for the case with 10% floor peroration ft/min.

30. Flow angles for the case with 10% floor peroration degree

31. Flow pathlines for a narrower cleanroom for the case with 35% floor perforation ft/min.

32. Flow angles for a narrower cleanroom for the case with 35% floor perforation degree

33. A case study: Computer aided design of chemical exhaust systems for vicinity near I/O of an implanter. Exhaust system setup, Case 1

34. Exhaust system setup, Case 2

35. Flow pathlines, air originated from the ceiling at x = 8.75 inches

36. Chemical concentration at x = 8.75 inches

37. Flow pathlines, air originated from the ceiling at y = -4 inches

38. Chemical concentration at y = -4 inches

39. A case study: Computer aided design improvement of a duct transition CFD model geometry, Case 1

40. CFD model geometry, Case 2

41. CFD model geometry, Case 3

42. CFD model geometry, Case 4

43. Velocity distribution at x = 42”, Case 1

44. Velocity distribution at x = 42”, Case 2

45. Velocity distribution at x = 42”, Case 3

46. Velocity distribution at x = 42”, Case 4

47. Pressure contour at x = 42”, Case 1

48. Pressure contour at x = 42”, Case 2

49. Pressure contour at x = 42”, Case 3

50. Pressure contour at x = 42”, Case 4