Record Display for the EPA National Library Catalog


Main Title Economically Optimal Design of Particulate Air Pollutant Control Equipment.
Other Authors
Author Title of a Work
Stone, Charles W.
Publisher Aeronautical Systems Division,
Year Published 1975
Report Number ASD/XR-TR-75-2; AD-A009 868
OCLC Number 907776941
Subjects Industrial Chemistry and Chemical Processing ; Particles ; Cyclone separators ; Pressure gradients ; Computer programs ; Mathematical models ; Theses ; Gas ionization ; Gas flow
Library Call Number Additional Info Location Last
EKBD  AD-A009 868 Microfiche collection Research Triangle Park Library/RTP, NC 04/27/2015
Collation 154 pages.
"AD-A009 868." "ASD/XR-TR-75-2." "Filmed 6-16-75 NTIS." Microfiche.
Contents Notes
An analytical study of the economically optimal design of particulate air pollutant control equipment is presented. Two major control equipment types, electrostatic precipitators and cyclones, are modeled and optimized with respect to total system economics. The equipment models are defined as a combination of functional elements. Basic mathematical definitions of particle distribution functions, particle collection efficiency, gas flow parameters and gas ionization are employed in the derivation of the various functional elements. The electrostatic precipitator model is developed and optimized using three functional elements. These elements are defined as electrical power requirements, gas flow/pressure drop and the economic considerations of precipitation. The electrostatic precipitator model resulting from the integration of the three functional elements is of such a degree of complexity when examined as a whole that it is more practical to optimize the individual elements. The tangential inlet cyclone model is developed and optimized using two functional elements. These elements are defined as power requirements and cyclone economics. Empirical equations defining the particle collection efficiency and pressure drop of a cyclone system are employed in the formulation of the power requirements model.