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Hanratty, Thomas J. Iliopoulos, Ilias 2015-09-25T20:44:08Z 2015-09-25T20:44:08Z 10000-01-01 1998 1998 Stochastic Lagrangian simulations are computationally efficient, since the equations to be solved are not partial differential equations as in the direct simulations. They are ideally suited for parallel computers. The stochastic model is about 120 times faster than the DNS on a single processor on the Convex C-3. Furthermore, the stochastic models can be used at higher Reynolds numbers and in more complex situations that is possible with a DNS. Made available in DSpace on 2015-09-25T20:44:08Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9904486.pdf: 9093349 bytes, checksum: 206bfd72c23630ea58cf6d21dd3c3bca (MD5) Previous issue date: 1998 Embargo set by: Seth Robbins for item 83731 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 234 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1998. http://hdl.handle.net/2142/82450 (MiAaPQ)AAI9904486 eng Engineering, Mechanical A Stochastic Lagrangian Model for Non-Gaussian Fluid Turbulence and Its Application to Describe Particle Dispersion in a Channel text Chemical Engineering Chemical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.