Treffer: Advances in Modeling Completely Mixed Flow Reactors for Ion Exchange

Title:
Advances in Modeling Completely Mixed Flow Reactors for Ion Exchange
Source:
Journal of environmental engineering (New York, NY). 136(10):1128-1138
Publisher Information:
Reston, VA: American Society of Civil Engineers, 2010.
Publication Year:
2010
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Dept. of Environmental Engineering Sciences, Univ. of Florida, P.O. Box 116450, Gainesville, FL 32611, United States
Dept. of Environmental Sciences and Engineering, Univ. of North Carolina at Chapel Hill, CB# 7431, Chapel Hill, NC 27599, United States
ISSN:
0733-9372
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Pollution
Accession Number:
edscal.23233719
Database:
PASCAL Archive

Weitere Informationen

This work advances the mathematical modeling of ion exchange treatment in completely mixed flow reactors in which there is recycle and regeneration of the ion exchange resin. The most common application of this process is magnetic ion exchange resin to remove dissolved organic carbon from raw drinking water. The motivation for this work was the complex distribution of resin particle ages and sizes that result from the recycle and regeneration processes. The newly developed model uses a single age-averaged diffusion equation to represent resin particle age as compared with the previous Monte Carlo model that uses a large number of diffusion equations to represent various resin particle ages. Advantages of the age-averaged model over the Monte Carlo model include a closed-form analytical solution for the steady-state case of the model, advanced numerical techniques used for the nonsteady-state case of the model, and model simulations require much less computational time and yield more accurate results. The age-averaged model is a robust numerical tool that can be used to evaluate a range of treatment scenarios as a result of these advancements.