首页> 外文期刊>Desalination: The International Journal on the Science and Technology of Desalting and Water Purification >Prediction of the behaviour of the Silt Density Index (SDI) in the Caribbean Seawater and its impact on RO desalination plants
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Prediction of the behaviour of the Silt Density Index (SDI) in the Caribbean Seawater and its impact on RO desalination plants

机译:加勒比海水中泥沙密度指数(SDI)的行为预测及其对反渗透淡化厂的影响

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摘要

The environmental characteristics of the seawater and its impacts on planning and operating RO desalination plants were always the concern of several scientists around the world. In this article, a study has been performed to investigate the seasonal characteristic of seawater in the Caribbean. The Radial Basis Function Networks (RBFN) was the methodology used in this paper where the redistribution of centres and the input training data possess significant effects in the model. The proposed method is based on clustering of input space vectors and computing weights of Euclidian distances and histogram equalization within each cluster for determining the centre and width of each receptive field. The model allows predicting the behaviour of the SDI using field data (turbidity and salinity) taking into account the tides (the Gulf of Paria) and seasonal changes (hurricane or dry seasons). The results indicated that during the hurricane season, the parameters can change up to 32% between seasons along year due to the change of direction of the inshore currents. Also values higher than 6 in the SDI indicated a very high potential for fouling. This article offers to the project engineers a new door in the application of precautionary principles in the design of desalination plants.
机译:海水的环境特征及其对反渗透海水淡化厂的计划和运营的影响一直是世界各地数位科学家关注的问题。在本文中,已进行了一项研究以调查加勒比海海水的季节性特征。径向基函数网络(RBFN)是本文使用的方法,其中中心的重新分布和输入的训练数据在模型中具有重要影响。所提出的方法基于输入空间向量的聚类,并计算每个聚类内的欧几里得距离的权重和直方图均衡,以确定每个接收场的中心和宽度。该模型允许使用潮汐(Paria湾)和季节变化(飓风或旱季)的现场数据(浊度和盐度)来预测SDI的行为。结果表明,在飓风季节,由于近海水流方向的变化,这些参数在一年四季之间最多可变化32%。 SDI中的值也高于6表示结垢的可能性很高。本文为项目工程师提供了在淡化厂设计中应用预防原则的新门。

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