2018•Chemical engineering transactionsOpen access

Risk Simulation and Route Optimization for Hazardous Chemical Transportation Based on Gaussian Plume Model

Lei Yu

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Abstract

The boom of chemical industry has made China heavily demanding for hazardous chemicals. In response to this, the security of road transport for hazardous chemicals has become even more important, while in the academic circles, the great challenge is to study how to ensure the security in the course of highway transportation of hazardous chemicals. It is suggested that the consequences of possible accidents occurred in transition be predicted accurately and effectively, by which a safer route can be chosen for transporting these chemicals. The most effective ways of how to reduce the probability of accidents resulting from hazardous chemicals and how to mitigate the consequences of road transport accidents resulting from hazardous chemicals are nothing but choosing an ideal transport route for these. This paper simulates the leakage of dangerous chemicals with the Gaussian plume model to determine its affected area, analyze the key factors affecting the choice of transportation routes and the route tuning objective. There are two problems: how to reduce the road transport risk and how to optimize the transport route for dangerous chemicals. We should settle both of them to provide the clues to improving the security of road transportation for dangerous chemicals.

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The boom of chemical industry has made China heavily demanding for hazardous chemicals. In response to this, the security of road transport for hazardous chemicals has become even more important, while in the academic circles, the great challenge is to study how to ensure the security in the course of highway transportation of hazardous chemicals. It is suggested that the consequences of possible accidents occurred in transition be predicted accurately and effectively, by which a safer route can be chosen for transporting these chemicals. The most effective ways of how to reduce the probability of accidents resulting from hazardous chemicals and how to mitigate the consequences of road transport accidents resulting from hazardous chemicals are nothing but choosing an ideal transport route for these. This paper simulates the leakage of dangerous chemicals with the Gaussian plume model to determine its affected area, analyze the key factors affecting the choice of transportation routes and the route tuning objective. There are two problems: how to reduce the road transport risk and how to optimize the transport route for dangerous chemicals. We should settle both of them to provide the clues to improving the security of road transportation for dangerous chemicals.

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Available abstract

The boom of chemical industry has made China heavily demanding for hazardous chemicals. In response to this, the security of road transport for hazardous chemicals has become even more important, while in the academic circles, the great challenge is to study how to ensure the security in the course of highway transportation of hazardous chemicals. It is suggested that the consequences of possible accidents occurred in transition be predicted accurately and effectively, by which a safer route can be chosen for transporting these chemicals. The most effective ways of how to reduce the probability of accidents resulting from hazardous chemicals and how to mitigate the consequences of road transport accidents resulting from hazardous chemicals are nothing but choosing an ideal transport route for these. This paper simulates the leakage of dangerous chemicals with the Gaussian plume model to determine its affected area, analyze the key factors affecting the choice of transportation routes and the route tuning objective. There are two problems: how to reduce the road transport risk and how to optimize the transport route for dangerous chemicals. We should settle both of them to provide the clues to improving the security of road transportation for dangerous chemicals.

Key concepts: Hazardous waste, Plume, Gaussian, Computer science, Gaussian network model, Environmental science, Mathematical optimization, Engineering

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