METHODOLOGICAL MODELS FOR OPTIMAL CONTROL OF MARINE OIL SPILL

METHODOLOGICAL MODELS FOR OPTIMAL CONTROL OF MARINE OIL SPILL

ABSTRACT

The frequency of accidental discharge of oil into aquatic environment has presented a significant threat to marine biota with related adverse effects on the supply of products and services of importance to human cultures. This threat of economic and environmental devastation led to the development of a number of monitoring and clean-up alternatives such as remote sensing and chemical dispersants, respective. This study proposed a new possible research direction in marine oil spill modeling where the monitoring and clean-up alternatives would be optimized to enhance locations selection for the deployment of containment and combating technique evaluation before actual usage. A novel optimal control theory has been developed through operational research formalism as a critical first step in mitigating the problem of oil spill look-alike phenomenon associated with remote sensing, and the conflicting priorities in the application of chemical dispersants, which may be toxic to marine biota, during marine oil spill clean-up. Markovian decision processes with sequential optimization techniques were utilized in formulating the control-theoretic methodological models that would aid environmental managers in minimizing the uncertainty in the remote sensing data to reduce the high number of false alarms (oil slick look-a-likes) phenomena, minimizing the apparent toxicological effect of clean-up technique like chemical dispersants, determining the control measure that would cause a process to satisfy the physical constraints of chemical dispersants applications, and at the same time optimizing some performance criteria for all future earnings from marine biota. A dynamic model for a new strategy based on a diffusion process, which makes the distinction between two types of optimization objectives: increasing awareness and changing predisposition to adopt coherent pluralistic technique has been developed and the optimality condition forminimization of false alarm in ……………………..