Transport of solid particles in a slit virtual impactor has been analyzed using visualization techniques. Particle trajectories were observed using laser-induced fluorescence of monodisperse particles seeded in the virtual impactor flow. It was observed from these trajectories that for smaller inertia particles essentially followed the flow streamlines, whereas higher inertia particles tend to deflect from their initial streamlines. These transport characteristics were used to determine particle collection efficiency curves, and the percentage of defect particle transmission, particles transmitted to the major flow that are well beyond the experimentally determined 50% cutoff. Defect percentages were found to be in good agreement with those based on a local stokes number approach, an analytical model using a converging flow velocity profile. It was hypothesized that these defects occur by virtue of larger particles passing through the near wall flow region and consequently transported to the major flow. The trajectories of such defect occurrences clearly show that these particles originated in the near wall region. Performance at higher mass loadings was evaluated using a background dust matrix generated by a turntable aerosol generator. At high mass loadings, clogging of the slit led to the deterioration of the impactor's performance. The time taken to clog the silt was estimated by modeling the slit edge as a single filter fiber of rectangular cross section with the primary mechanism of filtration being interception and was found to be in good agreement with the experimental data. Elimination of defect transmission and clogging would be possible by the provision of a sheath airflow, which ensures that the near wall regions are free of particles.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/538 |
| Date | 30 September 2004 |
| Creators | Seshadri, Satyanarayanan |
| Contributors | Phares, Denis J., Kihm, Kenneth D., McIntyre, Peter M. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis, text |
| Format | 1319052 bytes, 56638 bytes, electronic, application/pdf, text/plain, born digital |
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