Modeling marine oily wastewater treatment by a probabilistic agent-based approach

Authored by Liang Jing, Bing Chen, Baiyu Zhang, Xudong Ye

Date Published: 2018

DOI: 10.1016/j.marpolbul.2017.12.004

Sponsors: National Science and Engineering Research Council of Canada (NSERC)

Platforms: NetLogo

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

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.

Tags

Simulation Agent-based modeling Dynamics growth Challenges Global sensitivity-analysis Of-the-art Sludge Marine oily wastewater treatment Probability-based simulation Reaction competition Naphthalene degradation Treatment systems Uv-irradiation