Use of computational fluid dynamics for predicting air-flow and contaminant mass transport within a laboratory environment

Details

• Personal Author:
  Baker J ; Bennett J ; Ericson S ; Gruberrt M ; Kolesnikov A ; Baker J ; Bennett J ; Ericson S ; Gruberrt M ; Kolesnikov A
• Description:
  Many common laboratory handling practices such as weighing, pipetting, container transfer, autoclaving, and incubating can introduce aerosols, gases, and vapors into the inhabited environment. In addition, laboratory use of high-throughput technology with hazardous solvents (e.g., OMSO, methanol), biological agents (e.g., HIV, TB, hepatitis), and novel compounds of unknown potency (e.g., drugs), is rapidly expanding. Increased safety awareness leads to steady refinement of regulations emphasizing the need to accurately perform risk assessment studies of human exposure to airborne contaminants in cases of their accidental or intentional release into an indoor occupied space. Experimental tests are costly. and provide only limited data. The goal of this study is to explore, hence validate the use of computational fluid dynamics (CFD) for generating reliable predictions of laboratory airflow patterns hence contaminant mass transport distributions. Laboratory contaminant mass transport is dictated by room airflow patterns and contaminant source momentum. Mechanical ventilation (including the buoyancy effects of heating/cooling), location and characteristics of contaminant sources, occupancy, and lab equipment determine the contaminant concentration field. Quantitative inhalation exposure assessment therefore requires detailed assessment of the indoor ventilation velocity vector distribution. The presentation is inaugurated via CFD prediction for established experimental room airflow bench-marks describing supply, forced and mixed ventilation scenarios. The availability of quality experimental data for each case enables detailed validation studies to assess the impact of different turbulence closure models, numerical dissipation and domain discretization density. Following, airflow and contaminant mass transport CFD experiments are detailed for a current NIOSH experimental laboratory environment. Pollutant source, ventilation supply/exhaust and equipment locations are all shown to play important roles in the resultant contaminant distributions within the floor plan, The impact of approximations made in forming the CFD models is specifically addressed, to quantitatively assess the associated error mechanisms in prediction fidelity. [Description provided by NIOSH]
• Subjects:
  Aerosols Air Pollutants, Occupational Air Pollution, Indoor Biological Products Environmental Health Laboratories Occupational Health Risk Assessment Risk Factors Safety Safety Management Solvents Ventilation

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• Keywords:
  Air-contamination Biological-agents Exposure-levels Gases Hazards Indoor-air-pollution Indoor-environmental-quality Risk-analysis Risk-factors Safety-measures Safety-practices Vapors

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• Publisher:
  American Industrial Hygiene Association
• Document Type:
  Text
• Genre:
  Abstract or Summary ; Abstract or Summary
• Place as Subject:
  Ohio ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH) ; National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DART - Division of Applied Research and Technology ; DART - Division of Applied Research and Technology
• Topic:
  Workplace Safety & Health ; Workplace Safety & Health
• Location:
  North America ; North America
• Pages in Document:
  70
• NIOSHTIC Number:
  nn:20045107
• Citation:
  VENT 2006: 8th International Conference on Ventilation, May 13-18, 2006, Chicago, Illinois. Fairfax, VA: American Industrial Hygiene Association, 2006 May; :70
• CAS Registry Number:
  Methanol (CAS RN 67-56-1) ; Methanol (CAS RN 67-56-1)
• Federal Fiscal Year:
  2006
• Peer Reviewed:
  False
• Source Full Name:
  VENT 2006: 8th International Conference on Ventilation, May 13-18, 2006, Chicago, Illinois
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:c547ed9617e22e59e192a223b857a72ab8aebeb79b0c620943f5960911ca379b033abf8c06bf91e835770626b26230a52c7de50d360173cd46c5a16378be872c
• Download URL:
  https://stacks.cdc.gov/view/cdc/200634/cdc_200634_DS1.pdf
• File Type:
  [PDF - 1.44 MB ]