Bing Chen, Ph.D., P.Eng., M.RSC-C, M.GYA
Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, Canada
Visiting Scholar, CCRM


Responses to major offshore oil spills always involve dynamic changes of spilled oil, complicated multi-stage decisions and actions, and diverse and limited response resources (e.g., personnel and equipment). The lack of effective decision support can result in compromise of response efficiency and waste of time and resources. It is therefore much desired to dynamically integrate the simulation of oil weathering and recovery processes and the optimization of response actions. This talk will introduce our recent research on offshore oil spill modeling and response decision making. Special considerations will be given to the following three aspects:

  1. Agent based modeling: A new a simulation-based multi-agent particle swarm optimization (SA-PSO) method for response decision making was developed by dynamic coupling of agent based modeling (ABM) and PSO algorithm. The ABM as an emerging simulation method was introduced into oil spill responses in the first time to simulate the response actions with consideration of dynamic interactions among individual devices and/or response centers. A PSO method was further adopted to optimize the allocation of response devices/vessels among spill sites and warehouses with minimal total cost and time. Through an oil spill case study, the proposed SA-PSO approach showed strong capability and efficiency in reducing response time and optimizing responses.
  2. Modeling uncertainties: To improve oil spill simulation performance and have a better understanding of factor impact and interactions, a new design of experiment (DOE) aided method was developed for analyzing modeling sensitivity and uncertainties associated with input data and modeling parameters during offshore oil spill simulation. It was then applied for a marine oil spill case in the North Atlantic Ocean. The case study demonstrated that the developed method could effectively identify key modeling parameters and quantify their interactions and further facilitate modeling parameterization. The interactions of key parameters, such as wind speed/direction, windage, current, and diffusion coefficient, were quantified and their impacts on modeling results were analyzed.
  3. Human factors: Diverse human factors play important roles in oil spill and response processes; however, they have not been well studied, especially in a quantitative manner. The factors range from well workers’ lack of knowledge or skills, poor work performance, misjudgments, or incorrect operations, to responders’ lack of training or information, wrong decisions, inappropriate selection/operation of response devices, etc. Better consideration and integration of human factors into the spill response decision making processes would be highly valuable. This preliminary study was the first attempt to quantitatively incorporate several key human factors into an oil spill decision making process. Through a case study, the impact on the modeling results was analyzed, leading to potentially valuable information for accident prevention and risk reduction.

Bing Chen, Ph.D., P.Eng., M.RSC-C, M.GYA
Dr. Chen is currently a Full Professor in the Department of Civil Engineering, Director of the Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, and Advisor of the Environmental Systems Engineering and Management Program at the Memorial University of Newfoundland in St. John’s, Canada. He obtained his B.Eng. and M.Sc. degrees from Jilin University and Peking University in China, respectively, and his Ph.D. degree from University of Regina in Canada. He worked as NSERC Postdoctoral Fellow at University of British Columbia in Canada and conducted visiting research in Environment Canada before joining Memorial in 2006.

Dr. Chen’s research areas mainly focus on oil spill responses and cleanup, environmental emergency response, advanced wastewater treatment and reuse, decision making under uncertainty, impact and risk assessment, environmental nano/biotechnology, site remediation, watershed modeling and management, waste management, and environmental sustainability. He has acted as PI or Co-PI in over 40 research projects and contracts. He has authored or co-authored more than 270 technical publications, including over 80 refereed journal articles. He is the founding director of the NRPOP Lab, a first of its kind in Canada. The lab focuses on innovative, cross-disciplinary research on quantitative understanding of persistent and toxic pollution and effects and on development of innovative engineering and managerial solutions by integration of environmental engineering with nano/biological technologies and coupling of risk-simulation-optimization methods.

Dr. Chen has received many prestigious awards and honors, such as induction into the Royal Society of Canada (RSC) College of New Scholars, Artists and Scientists, and the Global Young Academy (GYA), Canadian Foundation for Innovation (CFI) Leaders Opportunity Fund Awards, Terra Nova Young Innovator Award, and FEAS Award for Research Excellence.


Meeting Recording (link coming soon)

Meeting Presentation (link coming soon)

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