Predicting model for the amount of destruction of buildings and casualties due to their collapse during an earthquake under different scenarios (Case study: Kermanshah metropolis)

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:
Introduction

All hazards can be generated from natural and unnatural sources caused by technology and human activities, where earthquake is one of the natural ones [2]. In terms of natural disasters, as Iran is one of the 10 accidental countries in the world [1], Therefore, it is very important to locate the relief centers before the accident in order to reduce the casualties caused by the earthquake. Providing relief after an earthquake is very important in reducing casualties, and this possibility is possible with facilities including power, equipment, and proper infrastructure. In order to achieve these goals, it is necessary to take preventive measures from now on and these programs should be based on the knowledge of vulnerable points. According to the need raised, we decided to investigate the vulnerability of buildings and calculate the human casualties caused by earthquakes in order to be able to investigate the construction of relief centers before the accident in different areas with a better view and more accurate information. Pay attention to the severity of their damages and prevent crises in earthquake affected areas.

Materials and Methods

Due to the fact that the deployment of rescue teams to provide relief in each region requires preliminary measures that take time and delay the delivery of relief, therefore the importance of saving the lives of trapped people, the necessity of locating and establishing relief centers before the incident It shows the crisis. In previous researches, locating was based on the amount of destruction of buildings, not the number of people involved and trapped in the buildings, which in this research, according to the people trapped in the destroyed buildings, the nearest place for relief centers was determined. The information required for the presented mathematical model includes the population of each region, the number, type of structure and the density of buildings in each region. The presented model is solved with the help of GAMS software. Also, taking into account the fact that the number of people living in each area is different according to the time, this research has considered different scenarios for day and night. Due to the fact that people are more alert during the day and react better and timely to earthquakes than at night, the number of injured people will be different.

Results and Discussion

People trapped in destroyed buildings are classified into two categories as follows. The first category contains people who leave the building immediately after the accident without getting help, who can be completely healthy or may have injuries. In contrast, the second one contains trapped people in the rubble that need help from relief forces, which can also be divided into two groups.The first group contains trapped people in the rubble who die immediately, whereas the second one is trapped people in the rubble who will be killed if no help is provided, so-called secondary casualties. Kermanshah metropolis is the study area divided into 6 areas, based on which the implementation of the model and its output information are conducted on them.Note that the required information is gathered based on the type of materials, the residential density, the earthquake intensity, and the population density, help the relief teams in prioritizing the areas. In this matter, the priority is given to areas via more alive people trapped in rubble. Traditionally, to save most people in the shortest time, the relief operations are begun in areas with more population. Meanwhile, many people may get out from the rubble in the early hours without the help of relief forces so that there are few trapped. In the following, without having information about the people trapped in the rubble, the relief teams provide relief operations in area with maximum power regarding both the density and type of buildings. Unfortunately, this mistake would result in a delay in the relief operations in other areas associated with more trapped people; hence, the number of killed people will be increased as well.

Conclusion

The results of the presented model showed the highest number of casualties in areas 3, 2, 4, 6, 5, and 1 respectively at the rate of 15.90%, 14.39%, 12.23%, 9.58%, and 9.56% and 9% will occur if a relief center is established, the casualties will be reduced by 6% and with the construction of two, three, four, five and six relief centers respectively 11%, 15%, 20%, 23% and 25% will decrease. The results of the research showed that with the increase in the number of aid centers, the number of casualties decreases. According to the output of the presented model, there are more people trapped under the debris at night than during the day. Considering the darkness and limited visibility, the construction and establishment of relief centers will be delayed a lot, so it is very important to predict the location of the relief teams before the accident, so that they can be settled in their place immediately Start the relief operation after the earthquake.The results of the present study show the superiority of the presented model and indicate the reduction of rescue time and casualties in different situations. In this research, the number of rescue teams under different scenarios has been considered according to the amount of damage to the buildings and trapped people, without taking into account the limitations of the cost and the number of rescue teams, The future is considered in the model which can be used in researches. The method presented in this research helps the crisis managers to take advantage of these results before the crisis by planning for the optimal use of the available time, to increase the operational capacity of the support and relief system in the shortest possible time and also allocate resources should be given to people in need.

Language:
Persian
Published:
Journal of Environmental Hazard Management, Volume:10 Issue: 2, 2023
Pages:
91 to 105
https://magiran.com/p2618873  
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