首页> 外文期刊>Bioresource Technology: Biomass, Bioenergy, Biowastes, Conversion Technologies, Biotransformations, Production Technologies >Optimization of the moving-bed biofilm sequencing batch reactor (MBSBR) to control aeration time by kinetic computational modeling: Simulated sugar-industry wastewater treatment
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Optimization of the moving-bed biofilm sequencing batch reactor (MBSBR) to control aeration time by kinetic computational modeling: Simulated sugar-industry wastewater treatment

机译:通过动力学计算模型优化移动床生物膜测序间歇反应器(MBSBR),以控制曝气时间:模拟制糖工业废水处理

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A novel approach was applied for optimization of a moving-bed biofilm sequencing batch reactor (MBSBR) to treat sugar-industry wastewater (BOD5 = 500-2500 and COD = 750-3750 mg/L) at 2-4 h of cycle time (CT). Although the experimental data showed that MBSBR reached high BOD5 and COD removal performances, it failed to achieve the standard limits at the mentioned CTs. Thus, optimization of the reactor was rendered by kinetic computational modeling and using statistical error indicator normalized root mean square error (NRMSE). The results of NRMSE revealed that Stover-Kincannon (error = 6.40%) and Grau (error = 6.15%) models provide better fits to the experimental data and may be used for CT optimization in the reactor. The models predicted required CTs of 4.5, 6.5, 7 and 7.5 h for effluent standardization of 500, 1000, 1500 and 2500 mg/L influent BOD5 concentrations, respectively. Similar pattern of the experimental data also confirmed these findings. (C) 2016 Elsevier Ltd. All rights reserved.
机译:一种新颖的方法被应用于优化移动床生物膜测序间歇反应器(MBSBR),以在2-4小时的循环时间内处理制糖工业废水(BOD5 = 500-2500和COD = 750-3750 mg / L)( CT)。尽管实验数据表明MBSBR达到了较高的BOD5和COD去除性能,但未能达到上述CT的标准限值。因此,通过动力学计算模型并使用统计误差指标归一化均方根误差(NRMSE)来对反应堆进行优化。 NRMSE的结果表明,Stover-Kincannon模型(误差= 6.40%)和Grau模型(误差= 6.15%)可以更好地拟合实验数据,并可用于反应堆的CT优化。该模型预测,分别对进水BOD5浓度分别为500、1000、1500和2500 mg / L进行标准化,分别需要4.5、6.5、7和7.5小时的CT。实验数据的相似模式也证实了这些发现。 (C)2016 Elsevier Ltd.保留所有权利。

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