Abstract

In order to solve the difficulty in simulation and prediction the evolution of oil spill incidents in port water area caused by system complexity and environment variety, a simulation model based on Dynamic Data-Driven Application System (DDDAS) was developed. By assimilating real-time data, simulation model can update its initial condition and solutions, and modify its parameters. Firstly, the framework for DDDAS-based simulation model was designed. Then the method for mapping of real-time data to simulation model, the method for recovery of initial data for DDDAS, and the algorithms to simulate the behavior of oil spill were studied. Finally, numerical tests were provided to illustrate the validity of the proposed model. Results indicate that the DDDAS-based simulation method can improve the prediction accuracy of oil spill incidents.

Highlights

  • Marine crude oil transport has the characteristics of large ship capacity and high liquidity

  • Considering the difficulty in predicting accident developing during emergency management, a DDDAbased simulation model for oil spill emergency decision is developed to improve the accuracy of simulation and prediction of oil spill

  • The real-time data here is mainly obtained by sensor, and the initial condition refers to the condition of simulation model at the last decision-making moment, not the condition when the simulation model starts

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Summary

Introduction

Marine crude oil transport has the characteristics of large ship capacity and high liquidity. Analysis of the evolution mechanism based on the simulation and prediction of diffusion process of oil spill incidents is one of the key issues to improve science and effectiveness of emergency response. Considering the difficulty in predicting accident developing during emergency management, a DDDAbased simulation model for oil spill emergency decision is developed to improve the accuracy of simulation and prediction of oil spill. Problems such as the method to map real-time data to simulation model, the method to recovery initial data of simulation model and the algorithms to simulate behavior of oil spill are designed

Framework of DDDAS-Based Simulation Model
Simulation Model
Algorithms for Oil Spill Diffusion
Algorithm for Simulation Data Update
Numerical Experiments
Conclusions
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