زهرا شيخ ساماني

Today, as a result of industrial development, large amounts of dangerous goods are produced annually, and it is obvious that their production is carried out along with their transportation. Meanwhile, rail transportation of dangerous goods has become a growing problem worldwide due to the increase in the volume of transportation. In fact, historical evidence has shown that accidents caused by hazardous emissions during transportation can lead to serious consequences. Therefore, it is necessary to identify and simulate the consequences of such accidents. In this research, the feasibility of providing a method to identify the changes and consequences that occurred as a result of the accident was investigated. Thus, in order to investigate the consequences, real conditions extracted from satellite images and simulated conditions caused by the accident of dangerous goods rail transportation were eva‎luated and compared. In this research, in order to use satellite images to estimate the changes and consequences caused by the accident, satellite images of the accident site were prepared before and after the accident. After uploading these images, the necessary pre-processing was done on each of them. Then by applying unsupervised and supervised classification methods on each of these images, the complications of the accident site were identified before and after the accident. For this purpose, ISODATA clustering method, Maximum Likelihood and Support Vector Machine classification methods were used and the most appropriate method was chosen. Then, according to the changes that occurred in the classified satellite images related to before and after the time of the accident, the consequences of the accident were eva‎luated. On the other hand, in order to simulate the consequences of the accident, all information about the accident was collected. This information includes the location of the accident site, information related to the environment where the dangerous goods accident occurred, weather conditions (including wind speed and direction, cloud cover, air temperature, stability class, altitude and humidity). The type of dangerous goods released and the physical and chemical properties of the substances in the process, and the characteristics of the release source. In addition, the scenario was prepared according to the actual scenario of the accident to show the consequences of fire and explosion. After simulating the accident according to the accident information, its consequences were eva‎luated in a spatial information system, and the area of various urban tolls due to the consequences of fire and explosion in the existing scenario separately in each of the red areas. Orange and yellow were estimated. Finally, the results obtained from the analysis of satellite images were compared with the simulation results. To eva‎luate the proposed method, the accident of the explosion of propane and butane tanks of a freight train in Hiterino, Bulgaria dated 12/10/2016 was considered. In this research, ENVI software was used to process satellite images, and ALOHA and ArcGIS software were used to simulate the accident and eva‎luate its consequences. The results showed that the support vector machine classification method provided better results than the maximum similarity classification method and the ISODATA clustering method. Then, the amount of changes caused by the accident was calculated as 751,500 square meters. In addition, the results of the accident simulation in ALOHA software for the chemical butane showed that the radius of the red, orange, and yellow ranges were 510, 720, and 1123 meters, respectively. Then according to the results of ArcGIS software, the area of urban tolls in the red, orange and yellow zones was estimated as 819817, 814982/9405 and 2341006/792 square meters, respectively, and recommendations to reduce the consequences of accidents in Each of the risk ranges was stated. At the end, the results obtained from the analysis of satellite images and the simulation model were compared with each other.

حمل و نقل ريلي كالاي خطرناك , ارزيابي ريسك , سيستم اطلاعات مكاني , سنجش از دور

rail transportation of dangerous goods , risk assessment , Geographic Information Systems , Remote sensing

Zahra Sheikh samani

Dr. Morteza Bagheri