Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.
Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada; College of Environmental Science and Engineering, Peking University, Beijing, China, 100871.
Mar Pollut Bull. 2018 Feb;127:217-224. doi: 10.1016/j.marpolbul.2017.12.004. Epub 2017 Dec 8.
This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization.
本研究开发了一种新颖的基于概率的代理方法，用于模拟海洋含油废水处理过程。它首先通过构建基于概率的代理模拟模型，然后进行全局敏感性分析和基于遗传算法的校准。通过使用紫外线照射去除海洋含油废水中萘的案例研究对所提出的建模方法进行了测试。使用 8 种类型的代理和 11 种反应，通过基于代理的模拟模型来描述萘的去除。每个反应都由一个概率参数控制，以确定其发生的可能性。建模结果表明，校准和验证运行的模型与观测去除率之间的均方根误差分别为 8.73%和 11.03%。通过比较基于代理的反应概率分析了反应竞争，同时通过绘制实时空间分布来可视化代理的异质性，这为反应器设计和工艺优化提供了巨大潜力。
