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Chemical modeling of waste sludges
Author(s) -
C.F. Weber,
E.C. Beahm
Publication year - 1996
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/432768
Subject(s) - leaching (pedology) , environmental science , chemical process , process (computing) , waste management , process engineering , biochemical engineering , chemistry , computer science , engineering , soil science , organic chemistry , soil water , operating system
The processing of waste from underground storage tanks at the Oak Ridge National Laboratory (ORNL) and other facilities will require an understanding of the chemical interactions of the waste with process chemicals. Two aspects of sludge treatment should be well delineated and predictable: (1) the distribution of chemical species between aqueous solutions and solids, and (2) potential problems due to chemical interactions that could result in process difficulties or safety concerns. It is likely that the treatment of waste tank sludge will begin with washing, followed by basic or acidic leaching. The dissolved materials will be in a solution that has a high ionic strength where activity coefficients are far from unity. Activity coefficients are needed in order to calculate solubilities. Several techniques are available for calculating these values, and each technique has its advantages and disadvantages. The techniques adopted and described here is the Pitzer method. Like any of the methods, prudent use of this approach requires that it be applied within concentration ranges where the experimental data were fit, and its use in large systems should be preceded by evaluating subsystems. While much attention must be given to the development of activity coefficients, other factors such as coprecipitation of species and Ostwald ripening must also be considered when one aims to interpret results of sludge tests or to predict results of treatment strategies. An understanding of sludge treatment processes begins with the sludge tests themselves and proceeds to a general interpretation with the aid of modeling. One could stop with only data from the sludge tests, in which case the table of data would become an implicit model. However, this would be a perilous approach in situations where processing difficulties could be costly or result in concerns for the environment or health and safety

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