首页> 外文期刊>Chemical engineering journal >Modelling and optimisation of a multistage Reverse Osmosis processes with permeate reprocessing and recycling for the removal of N-nitrosodimethylamine from wastewater using Species Conserving Genetic Algorithms
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Modelling and optimisation of a multistage Reverse Osmosis processes with permeate reprocessing and recycling for the removal of N-nitrosodimethylamine from wastewater using Species Conserving Genetic Algorithms

机译:使用物种保护遗传算法从废水中除去N-硝基二甲胺的渗透反渗透和再循环的多级反渗透过程的建模与优化

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摘要

The need for desalinated seawater and reclaimed wastewater is increasing rapidly with the rising demands for drinkable water required for the world with continuously growing population. Reverse Osmosis (RO) processes are now among the most promising technologies used to remove chemicals from industrial effluents. N-nitrosamine compounds and especially N-nitrosodimethylamine (NDMA) are human carcinogens and can be found in industrial effluents of many industries. Particularly, NDMA is one of the by-products of disinfection process of secondary-treated wastewater effluent with chloramines, chlorines, and ozone (inhibitors). However, multi-stage RO processes with permeate reprocessing and recycling has not yet been considered for the removal of N-nitrosodimethylamine from wastewater. This research therefore, begins by investigating a number of multi-stage RO processes with permeate-reprocessing to remove N-nitrosodimethylamine (NDMA) from wastewater and finds the best configuration in terms of rejection, recovery and energy consumption via optimisation. For the first time we have applied Species Conserving Genetic Algorithm (SCGA) in optimising RO process conditions for wastewater treatment. Finally, permeate recycling is added to the best configuration and its performance is evaluated as a function of the amount of permeate being recycled via simulation. For this purpose, a mathematical model is developed based on the solution diffusion model, which is used for both optimisation and simulation. A number of model parameters have been estimated using experimental data of Fujioka et al. (Journal of Membrane Science 454 (2014) 212-219), so that the model can be used for simulation and optimisation with high accuracy and confidence.
机译:对海水海水和再生废水的需求正在迅速增加,对世界不断增长的世界所需的饮用水的需求不断增加。现在,反渗透(RO)流程现在是用于从工业废水中除去化学品的最有前途的技术之一。 N-亚硝胺化合物和尤其是N-硝基甲酰亚胺(NDMA)是人致癌物质,可以在许多行业的工业污水中找到。特别是,NDMA是二次处理废水流出物与氯胺,氯和臭氧(抑制剂)的二次处理废水流出物的副产物之一。然而,尚未考虑具有渗透物再循环和再循环和再循环的多级RO过程,用于从废水中除去N-亚硝二甲酰亚胺。因此,该研究开始通过研究具有渗透再处理的多级RO方法,从废水中除去N-硝基吡嘧嘧啶(NDMA),并通过优化在抑制,回收和能耗方面找到最佳配置。我们首次应用了物种节约遗传算法(SCGA)在优化RO工艺条件下进行废水处理。最后,将渗透再循环加入到最佳配置中,并且作为通过模拟再循环的渗透量的函数评价其性能。为此目的,基于解决方案扩散模型开发了一种数学模型,其用于优化和仿真。使用Fujioka等人的实验数据估计了许多模型参数。 (膜科学454(2014)212-219的杂志,使模型可用于仿真和优化,高精度和置信度。

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