Semester

Summer

Date of Graduation

2003

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Nigel N. Clark.

Abstract

Characterizing particulate matter (PM) in diesel exhaust emissions during transient test cycles has been a challenge for researchers. Acquisition of real-time PM data was proposed by the use of a Rupprecht and Patashnick Co., Inc. Series 1105 Diesel Particulate Monitor Tapered Element Oscillating Microbalance (TEOM) mass measuring device. The objectives of testing with a TEOM diesel particulate analyzer were to validate its collection capability and evaluate its real-time characteristics on transient test cycles. Conventional PM filtration was used as the base line for evaluating the TEOM collection capability. To evaluate real-time TEOM characteristics, the real-time mass rate data were separated into positive and negative values, then integrated over the duration of the test. The integrated positive mass was divided by the integrated negative mass to create a positive-to-negative mass ratio. This ratio was indicative of real PM collected versus moisture released from the filter. TEOM sample tube temperatures at 35°C yielded the best TEOM to conventional PM filtration ratio. However, a compromise between conventional filter data and real-time data was made in selecting the temperature set point of 40°C as the most desirable sampling temperature. Sample flow rate was varied from one to four liters per minute (lpm). The 1 lpm set point provided the best TEOM to conventional filtration ratio. The flow rate of 3 lpm was chosen to be a compromise between TEOM to conventional filtration ratio and real-time results. The best TEOM to conventional filtration ratio measured was 0.97. The filter collection efficiency of a new filter was found to be a significant source of variability. When the initial test with a new filter was disregarded, the 99% confidence interval in TEOM results was +/-4.3%. In comparison, the 99% confidence interval in conventional PM results was +/-1.7%.

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