An integrated dynamic model for simulating a full-scale municipal wastewater treatment plant under fluctuating conditions

Chemical Engineering Journal

Volumn 160, Issue 2, 2010, Pages 522-529

  Fang, Fang ^a,b   Ni, Bing Jie ^a   Xie, Wen Ming ^a   Sheng, Guo Ping ^a   Liu, Shao Gen ^a   Tong, Zhong Hua ^a   Yu, Han Qing ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b HOHAI UNIVERSITY   (China)

Author keywords

Activated sludge model (ASM); Genetic algorithm (GA); Integrated model; Mechanistic model; Neural network (NN); Wastewater treatment plant (WWTP)

Indexed keywords

ACTIVATED SLUDGE MODEL; ACTIVATED SLUDGE MODEL (ASM); INTEGRATED MODELS; MECHANISTIC MODELS; WASTEWATER TREATMENT PLANTS;

ACTIVATED SLUDGE PROCESS; BIOACTIVITY; DYNAMIC MODELS; GENETIC ALGORITHMS; NEURAL NETWORKS; SEWAGE PUMPING PLANTS; WASTEWATER; WASTEWATER RECLAMATION; WASTEWATER TREATMENT; WATER RECYCLING; WATER TREATMENT PLANTS;

COMPUTER SIMULATION;

EID: 77954818024     PISSN: 13858947     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cej.2010.03.063     Document Type: Article

References (30)

1. Metcalf & Eddy, Inc., Wastewater Engineering: Treatment, Disposal and Reuse, 2nd ed., 1978.
2. Zeng G.M., Lin Y.P., Qin X.S., Huang G.H., Li J.B., Jiang R. Optimum municipal wastewater treatment plant design with consideration of uncertainty. J. Environ. Sci. 2004, 16:126-131.
3. M. Henze, W. Gujer, T. Mino, M.C.M. van Loosdrecht, Activated sludge models ASM1, ASM2, ASM2d, and ASM3. IWA Scientific and technical report no. 9, IWA Publishing, London, UK, 2009.
4. Yoo C.K., Vanrolleghem P.A., Lee I.B. Nonlinear modeling and adaptive monitoring with fuzzy and multivariate statistical methods in biological wastewater treatment plants. J. Biotechnol. 2003, 105:135-163.
5. Ni B.J., Xie W.M., Liu S.G., Yu H.Q., Wang Y.Z., Wang G., Dai X.L. Modeling and simulation of the sequencing batch reactor at a full-scale municipal wastewater treatment plant. AIChE J. 2009, 55:2186-2196.
6. Gernaey K.V., van Loosdrecht M.C.M., Henze M., Lind M., Jorgensen S.B. Activated sludge wastewater treatment plant modelling and simulation: state of the art. Environ. Model. Softw. 2004, 19:763-783.
7. Vandekerckhove A., Moerman W., Hulle S.W.H. Full-scale modeling of a food industry wastewater treatment plant in view of process upgrade. Chem. Eng. J. 2008, 135:185-194.
8. Wu M.M., Hickey R.F. Dynamic model for UASB reactor including reactor hydraulics, reaction, and diffusion. J. Environ. Eng. ASCE 1997, 123:244-252.
9. Lee D.S., Jeon C.O., Park J.M., Chang K.S. Hybrid neural network modeling of a full-scale industrial wastewater treatment process. Biotechnol. Bioeng. 2002, 78:670-682.
10. Fang F., Ni B.J., Yu H.Q. Estimating the kinetic parameters of activated sludge storage using weighted nonlinear least-squares and accelerating genetic algorithm. Water Res. 2009, 43:2595-2604.
11. Kumar K.V., Porkodi K. Modelling the solid-liquid adsorption processes using artificial neural networks trained by pseudo second order kinetics. Chem. Eng. J. 2009, 148:20-25.
12. Torrecilla J.S., Mena M.L., Yanez-Sedeno P., Garcia J. Field determination of phenolic compounds in olive oil mill wastewater by artificial neural network. Biochem. Eng. J. 2008, 38:171-179.
13. Henriques I.D.S., Aga D.S., Mendes P., O'Connor S.K., Love N.G. Metabolic footprinting: A new approach to identify physiological changes in complex microbial communities upon exposure to toxic chemicals. Environ. Sci. Technol. 2007, 41:3945-3951.
14. Hong Y.S.T., Rosen M.R., Bhamidimarri R. Analysis of a municipal wastewater treatment plant using a neural network-based pattern analysis. Water Res. 2003, 37:1608-1618.
15. Kim Y.H., Yoo C.K., L I.B. Optimization of biological nutrient removal in a SBR using simulation-based iterative dynamic programming. Chem. Eng. J. 2008, 139:11-19.
16. Raduly B., Gernaey K.V., Capodaglio A.G., Mikkelsen P.S., Henze M. Artificial neural networks for rapid WWTP performance evaluation: methodology and case study. Environ. Model. Softw. 2007, 22:1208-1216.
17. Rajendra M., Jen P.C., Raheman H. Prediction of optimized pretreatment process parameters for biodiesel production using ANN and GA. Fuel 2009, 88:868-875.
18. Wang J.L., Wan W. Optimization of fermentative hydrogen production process using genetic algorithm based on neural network and response surface methodology. Int. J. Hydrogen Energy 2009, 34:255-261.
19. Akratos C.S., Papaspyros J.N.E., Tsihrintzis V.A. An artificial neural network model and design equations for BOD and COD removal prediction in horizontal subsurface flow constructed wetlands. Chem. Eng. J. 2008, 143:96-110.
20. Sexton R.S., Dorsey R.E., Johnson J.D. Toward global optimization of neural networks: a comparison of the genetic algorithm and back propagation. Decis. Support Syst. 1998, 22:171-185.
21. Holland J. Adaptation in Natural and Artificial Systems 1975, University of Michigan Press, Ann Arbor, MI.
22. Rezende M.C.A.F., Costa C.B.B., Costa A.C., Maciel M.R.W., Filho R.M. Optimization of a large scale industrial reactor by genetic algorithms. Chem. Eng. Sci. 2008, 63:330-341.
23. Filho A.C.P., Filho R.M. Hybrid training approach for artificial neural networks using genetic algorithms for rate of reaction estimation: application to industrial methanol oxidation to formaldehyde on silver catalyst. Chem. Eng. J. 2010, 157:501-508.
24. Rieger L., Koch G., Kuhni M., Gujer W., Siegrist H. The EAWAG Bio-P module for activated sludge model no. 3. Water Res. 2001, 35:3887-3903.
25. Mjalli F.S., Al-Asheh S., Alfadala H.E. Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance. J. Environ. Manage. 2007, 83:329-338.
26. Machon I., Lopez H., Rodriguez-Iglesias J., Maranon E., Vazquez I. Simulation of a coke wastewater nitrification process using a feed-forward neuronal net. Environ. Model. Softw. 2007, 22:1382-1387.
27. Grady C.P.L., Daigger G.T., Lim H.C. Biological Wastewater Treatment 1999, Marcel Dekker, New York. 2nd ed.
28. Makinia J., Rosenwinkel K.H., Spering V. Long-term simulation of the activated sludge process at the Hanover-Gummerwald pilot WWTP. Water Res. 2005, 39:1489-1502.
29. APHA Standard Methods for the Examination of Water and Wastewater 1995, American Public Health Association, Washington, DC. 19th ed.
30. Reichert P. Aquasim 2. 0-User Manual. Computer Program for the Identification and Simulation of Aquatic Systems 1998, EAWAG, Dübendorf, Switzerland.