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Determination of Wastewater Behavior of Large Passenger Ships Based on Their Main Parameters in the Pre-Design Stage
Journal of Marine Science and Engineering ( IF 2.9 ) Pub Date : 2020-07-22 , DOI: 10.3390/jmse8080546
Volkan Şahin , Nurten Vardar

Wastewater formed on ships is divided into blackwater and graywater. While blackwater refers to wastewater from toilets, graywater defines wastewater from sinks, laundry and restaurants. Even though some treatments are applied onboard before discharge, wastewater contains significant amounts of fecal bacteria, heavy metals, etc., in excess of water quality standards. Dilution is a secondary natural treatment in the ship-wake region, which occurs after wastewater discharging. According to the Environmental Protection Agency (EPA), the natural treatment process is quantified by dilution factor, which is strongly dependent on vessel width, draft, speed and wastewater discharge rate. In this study, an Artificial Neural Network (ANN) model linked with the main ship parameters was developed to estimate the dilution factors while the ship is in the preliminary design stage. Gross ton, deadweight ton, passenger number, freeboard, engine power, propeller number and block coefficient values of 1041 large cruise ships were used to estimate the likely dilution factors. The best ANN estimation model was determined by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) methods. A decision tree was created for the results and the most important parameters affecting the dilution factors were determined. The main ship dimensions are needed for the dilution factor formulation of EPA whereas in the model created in this study only the gross ton or engine power of the ship is sufficient to estimate the dilution. Moreover, this new model is also usable for the estimation of dilution factors even if the main dimensions of the ship are not known.

中文翻译:

设计前根据主要参数确定大型客船废水行为

船上形成的废水分为黑水和灰水。黑水是指厕所的废水,而灰水是指洗手池,洗衣店和餐馆的废水。即使在排放前在船上进行了一些处理,废水中仍含有大量的粪便细菌,重金属等,超过了水质标准。稀释是在船舶尾水区进行的次要自然处理,在废水排放后发生。根据环境保护署(EPA)的说法,自然处理过程是通过稀释因子来量化的,稀释因子在很大程度上取决于容器的宽度,吃水深度,速度和废水排放率。在这个研究中,在船舶处于初步设计阶段时,开发了与主要船舶参数关联的人工神经网络(ANN)模型来估算稀释因子。使用1041艘大型游轮的总吨,载重吨,乘客数量,干舷,发动机功率,螺旋桨数量和阻滞系数值来估计可能的稀释系数。最佳的ANN估计模型由均方根误差(RMSE)和均值绝对误差(MAE)方法确定。为结果创建决策树,并确定影响稀释因子的最重要参数。EPA的稀释系数公式需要船的主要尺寸,而在此研究中创建的模型中,仅船的总吨或发动机功率足以估算稀释度。此外,
更新日期:2020-07-22
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