KR101797179B1 - Hazard potential evaluation method for complex disasters - Google Patents

Abstract

The present invention relates to a scenario-based hazard potential evaluation method for a big complex disaster, which is improved to display hazard potential evaluation of a big complex disaster on a navigation screen by forming a scenario of an occurrence expectation calculation process by using a hazard map and interdependence calculation for each disaster of a database in a hazard potential evaluation server and using an expert computer of an expert survey for defining interconnectivity between disaster types. To achieve the same, according to the present invention, the hazard potential evaluation server networks with the expert computer (10) of the expert survey for defining the interconnectivity between the disaster types and the database (20) of an existing research material such as an avalanche hazard map, a coastal flooding prognostic chart, and a wind speed probability map. The hazard potential evaluation server individually uses the generation of a natural disaster and social disaster matrix and generation of the map from a hazard map DB (50) for each disaster, from an interdependent database (40) for each disaster in a big complex disaster integrated database system (30). The hazard potential evaluation server selects the disaster in a case in which the interdependence is larger than a preset value in the occurrence expectation calculation process (60) and forms the scenario in accordance with the first disaster. The hazard potential evaluation server classifies the hazard map of a grid unit about a whole country as a result on the disaster forming the scenario and applies the same to the expectation calculation in accordance with the scenario. The hazard potential evaluation of the big complex disaster is displayed on the navigation screen (70) by using a scenario search unit of the disaster, reliability, relation, and disparity, a map display unit on which a grade of the hazard potential is displayed, and a disaster scenario pop-up unit.

Description

[0001] HAZARD POTENTIAL EVALUATION METHOD FOR COMPLEX DISASTERS [0002]

The present invention utilizes a professional computer of a professional questionnaire for establishing a correlation between disaster types and constructs scenarios of the expectation value calculation process through the risk assessment server and the risk interdependence calculation and risk map of the database, Which can be displayed on a navigation screen.

The safety consciousness of modern people is managed by various methods in complex natural environment and social environment, and it can be seen that the type of disaster and safety accident is very wide. To ensure the efficient management of disasters and safety accidents, the Safety Administration has enacted and announced disaster management standards and safety management standards to be adhered to by central, local governments and public institutions.

Disaster management standards include disaster relief plans for disaster prevention and mitigation, operations of disaster management organizations, disaster management continuity management, disaster management monitoring, disaster alert / alarm, situation propagation and command system, systematic situation management and resource management It contains unified definitions of disaster-related terms, particularly those that are used differently or have no clear definition. In the safety management standards, safety management standards for safety management planning, implementation and operation, evaluation of operation situation, and improvement of safety management measures are proposed.

According to the classification and definition of disaster disasters and safety accidents, natural disasters can be classified into three categories: typhoons, floods, heavy rain, strong winds, storm surges, storm surges, tsunamis, tidal storms, heavy storms, lightning, droughts, earthquakes, / Declination of steep slopes, volcanic eruptions, and cosmic disasters.

Social disasters can be classified as infectious disease epidemics, livestock epidemic epidemics, explosion accidents, gas accidents, accidents, accidents, traffic accidents, collapse of buildings, destruction of energy infrastructures, destruction of information and communication facilities, destruction of transport infrastructure, destruction of healthcare facilities, , Water infrastructure destruction, fire, forest fire, environmental pollution accidents, cyber terrorism and so on. There are 37 types of disasters.

Large-scale complex disasters generally refer to disasters in which human and material damage occur due to the simultaneous occurrence of two or more disasters simultaneously and concurrently due to a single disaster in the first instance. For example, earthquakes, tidal waves, typhoons, and floods have been analyzed as a single disaster and terminated in the short term. On the contrary, complex disasters are caused by large-scale and simultaneous damage, Recovery and response are prolonged.

Therefore, social and technical disasters are generally responsible for the disaster management personnel who caused the disaster, but the social and technical disasters caused by natural disasters are unclear, It was unclear.

Recent disasters occur in a large complex form, but the existing disaster management system is becoming less adaptive to disasters that are changing in a dichotomous divide between natural and social disasters. The enormous, complex, and networking of disasters can lead to economic damage and social disruption as well as to national crises.

This tendency has been shown not only in Korea but also in the United States and Japan which possess advanced technology of disaster management. From this, we experienced not only astronomical economic loss due to large complex disasters but also paralysis of basic functions of the nation.

Conventionally, as a risk assessment technique for a large complex disaster, a complex catastrophe model using a Bayesian network is constructed for a complex disaster caused by typhoons and heavy rainfall, which are mainly caused in Korea. For example, the second disaster such as the first disaster, typhoon, heavy rainfall and landslide caused by it, floods and torrents were selected as independent variables, and as a dependent variable of disaster and damage caused by these disasters, The Bayesian network model (Nam Ki-hoon, 2014) is the only case in which research is limited.

Korean Patent Laid-Open Publication No. 10-2016-37495 (title of invention: Disaster coping system), it is possible to evacuate safely and quickly in the opposite direction to the place where the disaster occurs, by analyzing the shortest distance using the indoor space information according to the situation And provides a disaster response system that can induce safe and quick evacuation by guiding the evacuation route.

On the contrary, in the present invention, the present invention is not classified according to the type of the first disaster including the natural and technical complex disasters, and it is a pattern in which a secondary and tertiary disaster occurs after an arbitrary first disaster arrives And a scenario of an expected occurrence value calculation process is constructed according to FIG.

Disclosure of the Invention The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a large complex disaster unified database system (DB) of a disaster-based interdependency database (DB) The present invention aims to provide a scenario-based large-scale risk assessment method capable of displaying a large-scale complex disaster risk assessment on a navigation screen.

In order to accomplish the above object, the present invention provides a computer system comprising an expert computer (10) of an expert survey for establishing a correlation between disaster types, an existing research data base (20) such as a landslide risk map, coastal inundation prediction probability maps, A risk assessment server is configured to network; The risk assessment server utilizes the map generation from the risk disaster map database 50 and the natural disaster and social disaster matrix generation from the disaster interdependency database (DB) 40 in the large complex disaster integrated database system 30 ; In the occurrence expectation calculation process (60), the disaster when the mutual dependency is larger than the set value is selected, the scenario is constructed according to the initial disaster, and the grid-level risk map for the whole country is ranked as a result of the disaster constituting the scenario And applied to the expected value calculation according to the scenario; A large complex hazard risk assessment screen is displayed on the navigation screen 70 through a scenario inquiry unit of disaster, reliability, degree of association and degree, a map display unit of a risk grade, and a disaster scenario popup unit.

As described above, according to the present invention, it is possible to construct a risk assessment system for a large-scale complex disaster as a damage probability estimation process determined by physical vulnerability and system vulnerability of the target facility or area, .

FIG. 1 is a system configuration diagram for explaining a scenario-based large complex disaster risk assessment method according to an embodiment of the present invention;
FIG. 2 is a graph showing the interdependency matrix used in the scenario-based large-scale complex risk assessment method of the present invention,
FIG. 3 is a view showing a questionnaire screen for inter-disaster correlation used in the scenario-based large-scale complex risk assessment method of the present invention,
FIG. 4 is a diagram illustrating a special field selection screen of a specialist used in a scenario-based large-scale complex risk assessment method according to the present invention,
5 is a diagram for explaining the expectation calculation process shown in FIG. 1,
6 is a diagram illustrating an example of a typhoon operation in the scenario-based large-scale complex disaster risk assessment method of the present invention,
7 is a diagram illustrating an earthquake operation in a scenario-based large complex disaster risk assessment method of the present invention,
FIG. 8 is a diagram illustrating a storm operation in a scenario-based large complex disaster risk assessment method of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a system configuration diagram for explaining a scenario-based large complex disaster risk assessment method according to an embodiment of the present invention. The present invention employs a professional computer 10 of a professional questionnaire for establishing a correlation between disaster types And the risk assessment server configures the scenarios of the expectation value calculation process 60 through the interdependency and risk map of the disasters of the databases 40 and 50 so that a large complex risk assessment can be displayed on the navigation screen 70 It is a large complex risk assessment method based on one scenario.

The system of the present invention includes an expert computer 10 of a professional questionnaire for establishing a correlation between disaster types, a road map for a landslide hazard map, a heavy snow risk map, a river flood risk map, a traffic safety index, A risk evaluation server is configured to network the existing research data base 20 such as a probability wind map.

In the risk assessment server, the large complex disaster integrated database system 30 utilizes the generation of the natural disaster and the social disaster matrix from the disaster interdependency database (DB) 40 and the corresponding map generation from the disaster-specific risk map DB 50 have. Here, the corresponding numbers are mutually displayed using the 37 * 37 matrix generation shown in FIG.

In the occurrence expected value calculation process 60 through the large complex disaster integrated database system 30, a disaster in the case where the interdependency is larger than the set value is selected, a scenario is configured in accordance with the initial disaster, As a result, the grid-level risk map for the whole country is graded and applied to the calculation of the expectations according to the scenario.

Therefore, a large-scale composite disaster risk assessment screen is displayed on the navigation screen 70 through a scenario inquiry unit of disaster, reliability, degree of association and degree, a map display unit with a risk rating, and a disaster scenario popup unit. The scenario inquiry unit can select an inquiry button, and the disaster scenario pop-up unit can select an evaluation button.

The scenario of the large composite scenario is composed of two types of strong winds, heavy rain, heavy rain, lightning, hail, storm, landslide, flood, traffic accident, destruction of traffic infrastructure, Interdependence can be seen.

As described above, the present invention can constitute a risk assessment system of a large complex disaster as a damage probability estimation process determined by physical vulnerability and system vulnerability of the target facility or area by graded risk probability.

FIG. 2 shows the interdependency matrix used in the scenario-based large complex disaster risk assessment method of the present invention. Here, 37 kinds are 1 drought, 2 gas accident, 3 cattle infectious disease, 4 infectious disease, 5 strong wind, 6 building collapse, 7 13 traffic accident, 8 destruction of transport infrastructure, 9 lightning, 10 heavy snow, 11 health facilities destruction, 12 cyber terrorism, 13 wildfire, 14 landslides, 15 energy infrastructure destruction, 16 water infrastructure destruction, 17 hail, 29 floods, 31 floods, 31 floods, 31 floods, 32 floods, 19 floods, 19 bogeys, 20 destruction of information and communications facilities, 21 tidal waves, 22 earthquakes, 23 earthquake tsunami, 24 typhoon, 25 destruction of waste facilities, , 33 volcanic eruption, 34 CBRN accident, 35 fire, 36 environmental pollution accident, and 37 dust globes.

FIG. 3 is a screenshot of the inter-disaster correlation used in the scenario-based large-scale complex disaster risk assessment method of the present invention, and FIG. It is a selection screen.

The interdependence matrix is a quantitative representation of disaster-related associations for the 37 major disasters. The interdependency matrix shown in FIG. 2 is configured through a survey, and the configuration method is as follows.

Expert questionnaires are conducted to analyze interdependence through 37 disasters related to disasters. The questionnaire method is classified into 'high', 'medium', 'low', 'no relation' '(See FIG. 3).

Survey respondents are required to select one of the 37 disaster types prior to conducting the questionnaire and respond to all selected disaster questions if multiple selections are made.

As shown in FIG. 4, for example, when only one hurricane is selected as a special field, it is necessary to respond to the questionnaire about the relationship between the typhoon and the remaining 36 kinds of disasters. When two types of disaster are selected, Respond to species' disasters and their relevance to 35 disasters except heavy rain and typhoons.

The reason for choosing the specialist field of the respondent is that there is a possibility that the result will be distorted when responding to the questionnaire items other than the related special field.

The interdependence is calculated by the number of respondents who answered 'high', 'normal', 'low', 'no relation' According to each correlation, the high is 0.9, the average is 0.6, the low is 0.3,

The calculated interdependence is normalized by dividing by 0.9 to have a maximum value of 1 and a minimum value of 0. Thus, the generalized disaster interdependencies are organized as shown in FIG. 2 in a matrix form.

FIG. 5 is a diagram for explaining the expectation value calculation process shown in FIG.

Through the process of a large complex disaster integration database, we construct the interdependency matrix as shown in Fig. 2, select the disasters when the interdependence is greater than 0.33, for example, and construct the scenario according to the initial disaster. As a result of previous studies on the disaster that constitutes the scenario, the grid-level risk map for the whole country is graded and applied to the calculation of the expectations according to the scenarios.

 Here is an example of a scenario that has been constructed. Connects B, C, and D disasters with interdependencies greater than 0.33 from the first A disaster, and C disasters with B disaster and interdependencies greater than 0.33. At the same time, D catastrophe and interdependence link C disasters exceeding 0.33.

는 도 2 에 나타난 상호의존성을 나타내며, 선행연구들로부터 A, B, C, D 각 재난의 위해성 지도를 최대값이 1을 갖도록 일반화하여 0.2 단위로 등급화한다.For each connected node

Shows the interdependence shown in FIG. 2, and from the preceding studies, the hazard maps of A, B, C, and D for each disaster are generalized to have a maximum value of 1 and classified into 0.2 units.

In this scenario, the aggregate expectation of the C disaster is estimated by the following equation.

: A재난의 위해성 등급,

: B재난의 위해성 등급,

: C재난의 위해성 등급,

: D재난의 위해성 등급,

: A재난과 B재난의 상호의존성,

: A재난과 C재난의 상호의존성,

: A재난과 D재난의 상호의존성,

: B재난과 C재난의 상호의존성,

: D재난과 C재난의 상호의존성이다. here,

: A Risk level of disaster,

: B Risk level of disaster,

: C Risk level of disaster,

: D Risk level of disaster,

: A Interdependence of disaster and B disaster,

: A Interdependence of disaster and C disaster,

: A Interdependence of disaster and disaster,

: B Interdependence of disaster and C disaster,

: D Interdependence of disaster and C disaster.

FIG. 6 is a diagram illustrating an example of a typhoon operation in a scenario-based large complex disaster risk assessment method of the present invention.

The interdependence of typhoons and traffic accidents during the typhoon: 0.53, the interdependence of heavy rain and traffic accidents: 0.59, and the interaction between heavy rain and floods. Dependence: 0.97, interdependence of flood and traffic accident: 0.49, interdependence of flood and landslide: 0.64, interdependence of heavy rainfall and landslide: 0.66, intermittency of landslide and traffic accident: 0.48.

Generalized risk grades are considered: disaster types considered: strong winds, heavy rain, floods, landslides, and traffic accidents; generalized risk grades are: strong wind 0.3, heavy rain 0.5, flood 0.2, landslide 0.2, traffic accident 0.2.

The expectation value calculation is as follows: (a) (0.53 * 0.3), (b): (0.59 * 0.5) due to heavy rain, (C): (0.97 * 0.5) * (0.49 * 0.2).

When a landslide occurs directly from heavy rainfall and landslides occur from floods from heavy rainfall, the expectation of traffic accidents is expected to be (d '): (0.66 * 0.5) due to heavy rainfall and floods due to heavy rainfall (D ''): {(0.48 * 0.2) + (0.97 * 0.5 * 0.64 * 0.2)} where the expected occurrence of landslides due to flooding is d ' * 0.2.

Therefore, (a + b + c + d) * 0.2 = 0.119829, and the final expectation of a traffic accident from a complex disaster caused by typhoon is about 0.12.

7 is a diagram illustrating an earthquake operation in a scenario-based large complex disaster risk assessment method of the present invention.

The interdependence of earthquake and traffic accident interdependence is 0.62, the earthquake and landslide interdependence is 0.79, the earthquake and explosion interdependence is 0.78, and the explosion accident And traffic accident interdependence: 0.43, and landslide and traffic accident interdependency: 0.48.

The generalized risk grades are the types of disasters considered: earthquakes, landslides, explosions, and traffic accidents. The generalized risk grades are 0.5 for earthquakes, 0.2 for landslides, 0.2 for explosions, and 0.2 for traffic accidents.

(B): (0.78 * 0.5) * (0.43 * 0.5) where an earthquake caused an explosion due to an earthquake, 0.2), and the expected value (c): (0.79 * 0.5) * (0.48 * 0.2) for the occurrence of landslides due to earthquakes and resulting traffic accidents.

Therefore, (a + b + c) * 0.2 = 0.07629, and the final expectation that a traffic accident will occur from a complex disaster caused by an earthquake is about 0.08.

FIG. 8 is a diagram illustrating an example of heavy rain operation in a scenario-based large complex disaster risk assessment method of the present invention.

Interdependence between heavy and traffic accidents was 0.59, interdependence between heavy and heavy floods was 0.97, interdependence between floods and traffic accidents was 0.49, , Interdependence of flood and landslide: 0.64, interdependence of heavy rainfall and landslide: 0.66, and interdependence of landslide and traffic accident: 0.48.

The generalized risk grades are considered to be the types of disasters considered: heavy rainfall, floods, landslides, and traffic accidents. The generalized risk grades are heavy rain 0.5, flood 0.2, landslide 0.2, and traffic accident 0.2.

(B): (0.97 * 0.5) * (0.49 * 0.2), which is the expected value of traffic accidents due to heavy rains. .

If landslides occur directly from heavy rainfall and landslides occur from floods from heavy rainfall, the expectation of traffic accidents is expected to be (c '): (0.66 * 0.5) due to heavy rainfall, floods due to heavy rainfall, (C '+ c' ') * 0.2, which is the expected value (c' ') of the occurrence of landslides due to landslides: {(0.48 * 0.2) + (0.97 * 0.5 * 0.64 * .

Thus, (a + b + c) * 0.2 = 0.088029, and the final expectation that a traffic accident will occur from a complex disaster caused by typhoon is about 0.09.

Therefore, in the present invention, a scenario of an expected occurrence value calculation process is configured according to a pattern in which secondary and tertiary disaster occur after an arbitrary first disaster arrives.

As described above, according to the present invention, in the risk assessment server in which the expert computer and the existing research data base are networked, a large-scale complex disaster integrated database system of the disaster-specific interdependency database (DB) , It is possible to provide a scenario-based large-scale disaster risk assessment method which can display a large-scale complex hazard assessment screen on the screen.

It should be noted that the scenario-based large-scale complex risk assessment method of the present invention is not limited to the described embodiments, and various modifications and variations can be made without departing from the spirit and scope of the present invention. It is obvious to the person.

It is therefore intended that such variations and modifications fall within the scope of the appended claims.

10: Expert computer
20: Existing research database
30: Large Combined Disaster Integrated Database
40: Interdependence by disaster DB
50: Risk Map by Disaster
60: Expectation value calculation process
70: Navigation screen

Claims (5)

A professional computer 10 of a professional survey for establishing interrelationships between disaster types and a risk assessment server networking network 20 of existing research databases such as landslide risk maps, coastal inundation likelihood estimates and probabilistic wind maps;
The risk assessment server utilizes the map generation from the risk disaster map database 50 and the natural disaster and social disaster matrix generation from the disaster interdependency database (DB) 40 in the large complex disaster integrated database system 30 ;
In the occurrence expectation calculation process (60), the disaster when the mutual dependency is larger than the set value is selected, the scenario is constructed according to the initial disaster, and the grid-level risk map for the whole country is ranked as a result of the disaster constituting the scenario And applied to the expected value calculation according to the scenario;
A large complex disaster risk assessment screen is displayed on the navigation screen 70 through a scenario inquiry unit of disaster, reliability, degree of association and degree, a map display unit of a risk grade, and a disaster scenario popup unit. Risk assessment method. The method according to claim 1,
The scenarios consisted of the first storm, second storm, heavy rain, third forest fire, lightning, hail, storm, landslide, flood, traffic accident, destruction of traffic infrastructure and water facilities. Based complex large scale disaster risk assessment method. 3. The method of claim 2,
Wherein said interdependency is a natural disaster or a social disaster 37 * 37 matrix generation. The method according to claim 1,
An example of the above scenarios is to connect B, C, and D disasters with interdependencies greater than 0.33 from the first A disasters, connect C disasters with B disasters and interdependencies greater than 0.33, and at the same time D disaster and interdependencies exceed 0.33 A scenario-based large complex disaster risk assessment method characterized by linking C disasters. The method according to claim 1,
Wherein the scenario inquiry unit can select an inquiry button, and the disaster scenario pop-up unit can select an evaluation button.

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