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| Treating simulative domestic wastewater using SBBR-CRI process and its simulation study based on artificial neural network. |
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Abstract The water technology of SBBR combined with CRI was employed to treat simulative domestic wastewater. SBBR-CRI process was simulated using the artificial neural network which adapted to the complicated nonlinear relation between the influence factors and the effluent parameters. The artificial neural network with adaptive study algorithm was built with the inputs of DO, wetting time/drying time, aeration time/nonaeration time, the influent COD, NH4+-N, TP and outputs of the effluent COD, NH4+-N,TN, TP using MATLAB software. Combining with the parameter optimization of SI 6, lr 0.13, mc 0.6, studying time 6000, the numerical outputs and the experimental values matched well, and the MARE of the sample were within 7.5% and the RSM were within 0.085. NH4+-N removal efficiency was over 98%, TN and TP removal efficiency were both over 85% and COD removal efficiency was over 94% under the conditions of DO concentration 2 mg/L, aeration time/nonaeration time 2/1 and wetting time/drying time 1/3. Through the weight analysis, it indicated that the influent DO, NH4+-N and TP had a strong impact on the effluent parameters.
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Received: 05 March 2010
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