Formation, characterization and mathematical modeling of the by Bing-Jie Ni
By Bing-Jie Ni
Aerobic granular sludge expertise will play an immense function as an cutting edge expertise replacement to the current activated sludge strategy in business and municipal wastewater remedy within the close to destiny. meant to fill the gaps within the reports of cardio granular sludge, this thesis comprehensively investigates the formation, characterization and mathematical modeling of cardio granular sludge, via integrating the method engineering instruments and complicated molecular microbiology. The learn result of this thesis contributed considerably to the development of knowing and optimization of the bacterial granulation tactics, the following new release of expertise for affordable organic wastewater treatment.
Dr. Bing-Jie Ni works at complex Water administration Centre (AWMC) of The collage of Queensland, Australia.
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Extra info for Formation, characterization and mathematical modeling of the aerobic granular sludge
Example text
In China, with the recent rapid economic growth and urbanization, a large number of municipal wastewater treatment plants are being constructed. The increasing population of China results in serious shortage of land area. Thus, aerobic granular process might be the promising technique for municipal wastewater treatment. Chapter 11 reports the cultivation of aerobic granules with an excellent settling ability in a pilot-scale SBR for the treatment of low-strength municipal wastewater for the first time.
Water Res. : Aerobic granular sludge in a sequencing batch reactor. Water Res. : Principles of Aquatic Chemistry. : A comparative study of the nature of biopolymers extracted form anaerobic and activated sludges. Water Res. : Effects of oxygen concentration on N-removal in an aerobic granular sludge reactor. Water Res. : High organic loading influences the physical characteristics of aerobic sludge granules. Lett. Appl. Microbio. : The role of energy-spilling reactions in the growth of Klebsiella aerogenes NCTC 418 in aerobic chemostat culture.
Then, the spatially discretized partial differential equations together with the ordinary differential equations and the algebraic equations are integrated numerically in time with the algorithm DASSL (Reichert 1998), which is based on the implicit (backward differencing) variable step, variable-order Gear integration technique. Model parameters represented by constant variables can be estimated with AQUASIM through minimizing the sum of the squares of the weighted deviations between the measurements and calculated model results.