CN113837549B - Natech risk calculation method and system based on coupled probability model and information diffusion method - Google Patents
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Abstract
The invention discloses a Natech risk calculation method and a Natech risk calculation system based on a coupled probability model and an information diffusion method, and belongs to the technical field of risk calculation of technical accidents caused by natural disasters. Aiming at the problem that the calculation accuracy of the Natech risk in a large-scale area is insufficient in the prior art, the invention provides a method, wherein the probability of natural disasters is calculated by coupling a probability model and an information diffusion method, different types of Natech environmental event risks are analyzed in a gridding mode, the failure probability of equipment under natural disasters is calculated, and the probability of the Natech risk is further calculated.
Description
Technical Field
The invention relates to the technical field of risk calculation of technical accidents caused by natural disasters, in particular to a method and a system for calculating the risk of a Natech by coupling a probability model and an information diffusion method.
Background
As a large industrial development country and one of countries with serious natural disasters in the world, China has the problem that the influence of the risk of a technical accident (Natech) induced by natural disasters cannot be ignored. Currently, a lot of studies have been conducted by many scholars for the risk of Natech. Comprehensive analysis finds that most researches are concentrated on small-scale Natech risk quantitative analysis of parks, enterprises and the like, or evaluation of the Natech risk in large-scale areas is low in refinement degree, systematic and high-precision researches of large-scale areas are lacked, and how to realize identification and analysis of the Natech risk areas is the key point of the existing researches.
From the high risk distribution of Natech, the atmospheric risk level is higher than the water environment risk level, but the distribution trends of the atmospheric risk level and the water environment risk level are approximately the same. Wherein, in the Natech risk analysis triggered by flood, the high risk areas of the atmosphere and water respectively account for 3.69 percent and 1.42 percent, and the high risk areas are distributed along the river network. In risk analysis caused by Natech earthquake, high risk areas of atmosphere and water respectively account for 0.32% and 0.04%, and the high risk areas are mainly concentrated in mountainous areas such as the northern part of Sichuan and the northern part of Yunnan. In the risk analysis of Natech caused by typhoon, high risk areas of the atmosphere and the water body respectively account for 2.85 percent and 1.73 percent, and are mainly concentrated in parts of areas in the west of the river and southeast of Hunan province. Therefore, the spatial resolution map can help us to know spatial features, identify hot spots of the Natech risk and provide scientific reference for the macro decision of environmental risk management.
The applicant has already disclosed Chinese patent application on 11.12.2020/12.disclosing a method and a system for risk assessment of a natural disaster induced technical accident, and discloses a method and a system for risk assessment of a natural disaster induced technical accident, aiming at the problems of immature risk assessment method, unclear risk space distribution pattern, low risk assessment accuracy and the like of the natural disaster induced technical accident in the prior art, the method is expanded to corresponding secondary indexes based on four primary indexes of risk source, natural disaster causing factor, control level and receptor vulnerability, scores are calculated according to weights obtained by an analytic hierarchy process, index calculation is completed, a risk assessment system is constructed, and risk indexes are calculated. The risk calculation method has higher accuracy for a garden or a small enterprise, but the calculation accuracy for a large-scale area cannot meet the requirement.
Through retrieval, a patent with publication number CN112907731 and publication date 2021, 06 and 04 applies for a multi-disaster accident coupling three-dimensional simulation system of a major oil and gas infrastructure, and on the basis of the existing Natech accident analysis method, a multi-disaster accident coupling link of the major oil and gas storage and transportation infrastructure is considered, and all potential accident links are identified; in daily management, the probability and the accident consequence of accidents of each unit under the coupling of multiple kinds of disasters are analyzed, and a basis is provided for the reasonable arrangement of safety protection facilities and emergency evacuation drilling; in the emergency rescue stage after an accident occurs, the most probable propagation path and evolution time of the accident under the coupling of multiple kinds of disasters are analyzed, and decision support is provided for the development of emergency rescue actions.
Disclosure of Invention
1. Technical problem to be solved
Aiming at the problem that the accuracy of the Natech risk calculation in a large-scale area is insufficient in the prior art, the invention provides a Natech risk calculation method and a system for coupling a probability model and an information diffusion method.
2. Technical scheme
The purpose of the invention is realized by the following technical scheme.
A Natech risk calculation method of a coupling probability model and an information diffusion method is characterized in that a Natech risk probability is calculated based on a grid information diffusion method, a calculation result is visualized, and a Natech risk space distribution map is drawn;
the Natech risk probability is calculated through natural disaster probability and equipment failure probability under natural disasters, and the Natech risk calculation formula is as follows:
Natech risk＝P(NH)×P(release|NH)×Consequence
in the formula, P (NH) represents natural disaster probability, P (release | NH) represents conditional probability of release of harmful substances under natural disaster, and sequence represents Natech risk result, wherein the Natech risk includes atmospheric environmental risk and water environmental risk.
Preferably, the risk calculation model is respectively constructed according to different Natech risk inducing factors of flood, earthquake or typhoon.
Preferably, for the flood-induced risk of Natech, calculating the flood probability by taking the flood recurrence period as a parameter;
when the equipment failure probability model under the action of flood disasters is constructed, the flood scenes are firstly classified according to the water depth and the speed, the storage tank leakage model under the action of flood is constructed according to the volume, the diameter, the tank length and the wall thickness of the cylinder body of the storage tank,
the leakage model expression under the action of the flood of the vertical storage tank is as follows:
wherein CFL1At a critical filling level, pwsIs flood hydrostatic pressure, pwdKinetic pressure of flood water, pcrCritical pressure of the vessel, pfIs the internal pressure of the container, g is the acceleration of gravity, H is the height of the storage container,
at the point of the maximum filling level,
at minimum filling level, Ψ1The conditional probability of leakage of the vertical storage tank;
the leakage model expression under the action of the flood of the horizontal storage tank is as follows:
wherein, CFL2At a critical filling level, prefDensity of a reference substance for defining a correlation of CFLs, A 'being a modified A coefficient of the common storage substance, B' being a modified B coefficient of the common storage substance, Ψ2The conditional probability of a leakage from a horizontal tank,
at the point of the maximum filling level,
is the minimum fill level.
And matching the storage tank leakage condition probabilities under each scene according to the enterprise industry type and the enterprise scale, sequencing all enterprises, and distributing according to the probability percentile to obtain the failure probability of the equipment under the flood disaster.
Preferably, for the Natech risk induced by the earthquake, calculating earthquake frequency according to the historical earthquake disaster frequency, and calculating the earthquake occurrence probability by adopting an information diffusion method according to the earthquake occurrence frequency;
calculating the failure probability of equipment under the earthquake disaster according to the vulnerability and the Probit coefficient of the equipment under the earthquake action, wherein the Probit model represents the failure probability of the storage tank under the earthquake disaster, a vulnerability model is constructed according to the equipment type and the damage state, and the vulnerability curve F is as follows:
wherein F is the cumulative value of lognormal distribution F, mu is the mean value, beta is the standard deviation, alpha is the value exceeding given DS or RS, PGA represents the earthquake peak ground acceleration, DS represents the damage state, RS represents the risk state, F is linearized by the Probit function, and the vulnerability model is obtained as follows:
Yi，j＝k1，i，j+k2，i，j ln(PGA)
Yi，jrepresents the Probit intermediate variable, where k1，i，jAnd k2，i，jIs a model coefficient related to the device type i and damage state j, by fitting the variable Yi，jAnd integrating to calculate the failure probability of the equipment, wherein the calculation formula is as follows:
wherein V ═ PGA.
Preferably, for the typhoon-induced Natech risk, calculating the typhoon frequency according to the typhoon path data of time and area, and calculating the typhoon occurrence probability by adopting an information diffusion method according to the typhoon occurrence frequency;
and calculating the failure probability of the equipment under the action of the typhoon disaster according to the failure probability of the shell layer breaking under the action of the typhoon disaster and the failure probability under the action of the wind.
Preferably, the concentration is calculated according to the enterprise distribution, and the concentration coefficient W is calculated according to the formula:
wherein N isdistrictRepresenting the number of enterprises in the county where the risk is located, and N representing the total number of enterprises in the risk calculation area.
Preferably, the sub risk information matrix is constructed for each environmental risk source, i.e. the risk calculation area is divided into a 1km × 1km grid, which is expressed by an m × n matrix, and the element q in the matrix isijRepresenting information of a corresponding grid area in space, and representing a matrix expression formula for a calculation area as follows:
the information diffusion influence range calculation formula is as follows:
wherein r is a risk value calculated at a central point of a certain grid, r0An environmental risk value that is a source of risk; x is the distance from the grid center point to the risk source, m; l' is the maximum value of the influence radius of the heavy injury area; l is the maximum impact radius value; wherein r is0P × C, P is the probability of an accident and C is the consequence of an accident; based on the ratio of the material stock of the risk material to a critical value as a risk sourceAnd determining the influence radius of the risk accident.
Preferably, the calculation formula of the atmospheric environment value of the risk of Natech is as follows:
V＝3.14×l2×d×50％
the water environment risk value of the Natech risk is calculated as follows:
S＝S1×W1+S2×W2+S3×W3；
wherein Q represents the ratio of the material stock of the hazardous material to the threshold value, V represents the atmospheric vulnerability index, S represents the water vulnerability index, d represents the population density in the different diffusion buffers, and 50% indicates the use of LD50Or LC50As a basis for calculating mortality.
A Natech risk calculation system for coupling a probability model and an information diffusion method uses the Natech risk calculation method for coupling the probability model and the information diffusion method, and the system comprises a data acquisition unit, a data storage unit, a risk calculation unit and a visualization unit;
the data acquisition unit is used for acquiring the Natech risk related data in the calculation area, the data storage unit is used for storing the Natech risk related data acquired by the data acquisition unit, the risk calculation unit performs Natech risk calculation according to the Natech risk related data acquired by the data acquisition unit, and the visualization unit generates a Natech risk map according to the calculation result of the risk calculation unit and displays the Natech risk in a visualization mode.
Preferably, the risk calculation unit comprises a natural disaster probability calculation module, a natural disaster equipment failure probability calculation module and an information diffusion calculation module,
the natural disaster probability calculating module calculates the natural disaster probability; the natural disaster equipment failure probability calculation module is used for constructing an equipment failure probability model under the action of natural disasters and calculating the equipment failure probability under the natural disasters; the information diffusion module is used for performing information diffusion on the Natech risk probability calculated by the natural disaster probability calculation module and the equipment failure probability calculation module under the natural disaster, and calculating the Natech risk probability.
According to the method, the spatial characteristics of the Natech risks can be known through different types of Natech environmental event risk maps subjected to spatial analysis, hot spot areas of the Natech risks induced by flood, earthquake and typhoon are identified, and scientific and fine references are provided for Natech environmental risk zoning of the country or the area and macroscopic decision of risk management, such as Natech risk zoning, risk management priority determination, area risk management resource allocation optimization and the like.
3. Advantageous effects
Compared with the prior art, the invention has the advantages that:
the risk calculation method used by the invention makes up the problem of low risk evaluation precision of the Natech in the large-scale area, is beneficial to identifying the high-risk hot spot area, realizes the preferential management of the Natech risk, and provides a direction for reducing the Natech risk.
The invention innovatively provides a grid Natech risk assessment method combining a probability model and an information diffusion method, and in the process, high-precision risk assessment is carried out by taking 1km multiplied by 1km as a unit, and the precision is higher than that of a district level and a county level. The method comprises the steps of evaluating the Natech risks caused by flood, earthquake and typhoon with the spatial resolution of 1km multiplied by 1km, calculating natural disaster probability through a coupling probability model and an information diffusion method, then constructing an equipment failure probability model under the action of natural disasters, calculating the equipment failure probability under the natural disasters, and finally calculating the probability of the Natech risks according to the natural disaster probability and the equipment failure probability under the natural disasters.
The invention discloses a natural disaster probability model coupled to a risk calculation system for the first time so as to realize the application of an information diffusion method to the Natech risk assessment. Finally, the difficulty in estimating and determining the final influence radius of the risk accident is overcome by introducing the hazard of taking the ratio of the material stock of the risk substances to a critical value (namely Q value) as a risk source; and a specific reference that an information diffusion method in consequence calculation is not suitable for the Natech risk is provided, and the calculation difficulty of the vulnerability index of an atmospheric environment receptor and a water environment receptor in the Natech risk is overcome by introducing the population density of a buffer zone and the water body attribute index.
In the specific implementation mode, a high risk area is identified and analyzed by taking a Yangtze river economic zone as an example, and through different types of Natech environmental event risk maps of spatial analysis, when the failure probability of equipment under natural disasters is analyzed, the spatial characteristics of the Natech risk are analyzed, hot spot areas of the Natech risk induced by flood, earthquake and typhoon are identified, scientific and fine references are provided for the Natech environmental risk zoning of the country or area and the macro decision of risk management, and operations such as Natech risk zoning, risk management priority determination, area risk management resource allocation optimization and the like are realized.
The method can make different risk control key points aiming at different types of Natech risks, and can better avoid unreasonable industrial structure. The method provides support for further perfecting a risk management system of a large-scale area and strengthening risk control of multiple disaster species, and provides reliable reference data for adding Natech risk management into the management system in the future.
Drawings
FIG. 1 is a schematic diagram of failure probability distributions under different scenarios according to an embodiment of the present invention;
FIG. 2 is an atmospheric risk level spatial distribution of flood induced Natech risk (scenario a) according to an embodiment of the present invention;
fig. 3 is a water risk level spatial distribution of flood induced Natech risk (scenario a) according to an embodiment of the present invention;
FIG. 4 is an atmospheric risk level spatial distribution of earthquake induced Natech risk (scenario a) according to an embodiment of the present invention
FIG. 5 is a water risk level spatial distribution of earthquake induced Natech risk (scenario a) according to an embodiment of the present invention;
FIG. 6 is an atmospheric risk level spatial distribution of a typhoon-induced Natech risk according to an embodiment of the invention;
FIG. 7 is a spatial distribution of water risk levels for a typhoon-induced Natech risk according to an embodiment of the invention;
fig. 8 is a schematic flow chart of the method for calculating the risk of Natech according to the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and specific examples.
Example 1
In this embodiment, a method for calculating a gridding Natech risk by coupling a probability model and an information diffusion method is described in detail by taking the economic zone of the Yangtze river as an example.
The embodiment discloses a risk calculation system, which comprises a data acquisition unit, a data storage unit, a risk calculation unit and a visualization unit; the data acquisition unit is used for acquiring environmental risk related data in a risk calculation area, the data storage unit is used for storing the environmental risk related data acquired by the data acquisition unit, the risk calculation unit performs Natech risk calculation and evaluation according to the environmental risk related data acquired by the data acquisition unit, during risk calculation, a probability model and an information diffusion method are coupled to obtain risk probability, the visualization unit generates a Natech risk map according to a calculation result of the risk calculation unit, and the Natech risk in a large-scale area is visually displayed.
A detailed description of how the above system achieves the natach risk calculation by meshing is given below. For the large-scale area, the calculation method of the embodiment calculates the risk probability of the Natech based on the grid, and then calculates the risk probability of the Natech by a grid information diffusion method.
The process of the Natech risk calculation method is shown in FIG. 8 and comprises the following steps:
step 1: and calculating the risk probability of the Natech based on the grids.
Two factors need to be considered when calculating the probability of a Natech accident: the first is the probability of natural disasters of given intensity; the second is the conditional probability that a device is damaged under a given natural disaster, i.e., the device damage probability or the device failure probability. The natural disaster occurrence probability with certain intensity can be analyzed through regional natural disaster historical data records and statistics. However, the statistical data of the equipment damage information of the Natech event is incomplete, and the equipment damage probability is difficult to obtain directly through a probability method.
The calculation formula of the risk probability of Natech is constructed as follows:
Natech risk＝P(release∩NH)×Consequence (1)
in formula (1): p (release. andgate. NH) is the probability of release of dangerous substances under the action of natural disasters, and Consequence represents the Natech risk result. Considering that the occurrence of natural disasters and the release of risk substances are related events, P (release ≧ NH) is defined as:
based on the Bayesian probability model, the Natech risk calculation formula is shown as (3)
Natech risk＝P(NH)×P(release|NH)×Consequence (3)
In the formula (3), P (NH) represents a natural disaster probability, and P (release | NH) represents a conditional probability of releasing a harmful substance in a natural disaster.
Step 1.1: and calculating natural disaster probability according to historical data.
And obtaining the occurrence probability of each natural disaster through statistical analysis of historical data. And calculating the flood probability by taking the flood recurrence period as a parameter. Flood probability PfIs calculated by the formula
T denotes the flood recurrence period. Based on all data of the hydrological annual newspaper in 1998, the maximum flood recurrence period of the main hydrological station in the Yangtze river economic zone in the whole year is combed. The calculation results of flood inundation areas in 1998, 2002, 2010 and 2016 are comprehensively considered. For the part which has been submerged andand (4) considering that the recurrence period is not marked, namely, smaller floods are mostly considered, if the recurrence period is less than 5, the smaller floods are assigned according to the consideration, and finally, all the parameters are integrated to calculate the flood probability.
Step 1.2: and (3) constructing an equipment failure probability model under the action of natural disasters, and calculating the equipment failure probability under the natural disasters.
This example illustrates the risk of flood induced Natech. According to researches, equipment faults in technical accidents caused by flood are mainly normal-pressure equipment storage tanks, the normal-pressure equipment storage tanks are taken as an example to calculate a probability model, no available simplified damage model exists for chemical industrial parks or enterprises under the flood condition, and most of researches are carried out on scenario assumption and analysis based on historical data. Through investigation and research based on the failure probability of the storage tank under different flood scenes, the method finds that in most of the flood scene hypotheses, the flood depth is mostly between 0 and 4m, the flood speed is less than 3.5m/s, and the flood density is 1100kg/m3And the like. In combination with the results of numerous researchers, organizing major flood scenarios according to water depth and speed includes: 1. scenario (a) scenario with higher risk: h is 2m, v is 2 m/s; 2. scenario (b) deeper flood depth scenario: h is 3m, v is 0.5 m/s; 3. scenario (c) flood speed greater scenario: h is 0.5m, v is 2 m/s.
In this embodiment, the storage tank type most susceptible to the influence of the flood is selected to construct a model, as shown in formulas (4) and (5), and based on this model, corresponding calculation is performed by taking the storage tank of a certain chemical industry park in the Yangtze river economic zone as an example. The results of the calculations for a typical tank case are shown in table 1.
TABLE 1 calculation of selected exemplary case tanks
In table 1, NF represents No predicted failure, i.e., No predicted failure value.
The leakage model expression under the action of the flood of the vertical storage tank is as follows:
wherein CFL1At the critical fill level, pwsIs flood hydrostatic pressure, pwdKinetic pressure of flood water, pcrCritical pressure of the vessel, pfIs the internal pressure of the container, g is the acceleration of gravity, H is the height of the storage container,
at the point of the maximum fill level, the fill level,
at minimum filling level, Ψ1Conditional probability of leakage for vertical tanks, pcrAnd carrying out simplified calculation only related to the volume C, and verifying the simplification reasonableness by the simplified model through the calculation comparison result of the final traditional model and the simplified model. And matching and dividing the storage tank volume and the risk Q value to provide a basis.
The leakage model expression under the action of the flood of the horizontal storage tank is as follows:
in the formula (5), CFL is the critical filling level, rhorefDensity of a reference substance for defining a correlation of CFLs, A 'being a modified A coefficient of the generic storage substance, B' being a modified B coefficient of the generic storage substance, Ψ2Is the conditional probability of a horizontal tank leak,
at the point of the maximum filling level,
is the minimum fill level.
According to the leakage probability results of all storage tanks in the case chemical industry park, probability distribution conditions under different situations are plotted, the results are shown in figure 1, and the results show that the failure probability is mostly concentrated in the (0, 0.25) interval.
According to the failure probability calculation results of all cases, firstly, according to the same enterprise industry type and the same enterprise scale, the storage tank leakage condition probability psi of each scene is directly matched and analogized. Secondly, for enterprises which cannot be directly matched, probability matching and analogy are carried out by calculating the enterprise scale probability percentiles of the same industry under different scenes, and taking a certain industry type as an example, all enterprises in the industry are arranged from small to large according to the enterprise scale. Then, corresponding distribution is carried out according to the probability percentile. For example, in scenario a, the proportions are 50%, 19%, 20%, and 11%, respectively. Finally, the failure probability of all areas under the influence of flood is determined, and the distribution standard is also applicable to other areas.
The concept of concentration factor is introduced in view of the limitations of the relevant data, such as the amount of hazardous materials, tank distribution, etc. And calculating the aggregation degree according to the enterprise distribution by taking a district or a county as a unit. And the distribution of dangerous substances or storage tanks is replaced by the concentration coefficient of the enterprise so as to measure the damage degree of different areas. The calculation result of the equipment fault probability under the influence of the flood in the area is further refined and optimized, and the concentration coefficient W is calculated according to the following formula.
In the formula (6), NdistrictThe number of enterprises in the county of the grid is shown, and N represents the number of all enterprises in the economic zone of the Yangtze river.
Step 1.3: and calculating the probability of the risk of Natech according to the natural disaster probability calculated in the step 1.1 and the equipment failure probability under the natural disaster calculated in the step 1.2.
The probability calculation formula of the risk of Natech under the action of flood is as follows:
Nf＝Pf×ff (7)
Pf＝1/T，ff＝Ψ×Wf
in formula (7), PfProbability of flood, T flood recurrence period, ffFor the probability of equipment failure under the influence of flood, Ψ is the conditional probability of leakage, WfIs the concentration factor.
Step 2: and calculating the risk probability of the Natech based on a grid information diffusion method.
The investigation region (YREB) is divided into a 1km x 1km grid, the space being represented by a m x n matrix, the elements q in the matrixijThe information of the corresponding grid area in the space is represented, the whole area can be represented in a matrix form, and the calculation formula is shown as formula (8):
and respectively constructing sub-risk information matrixes for each environmental risk source, wherein the risk is correspondingly reduced and processed according to the concentration reduction of atmospheric environmental risk diffusion, and the influence of weather and terrain factors is not considered in the sub-risk matrixes. Similarly, toxic and harmful liquid is diffused with water, the destructiveness of the toxic and harmful liquid is not reduced along with the increase of the distance in a short time, and the toxic and harmful liquid is equivalently diffused. Over a long period of time, the concentration is graded as the distance increases and can be treated in the same way as gas diffusion. The information diffusion model is simplified by adopting a trapezoidal fuzzy model and is used for model calculation in the embodiment.
The calculation model is shown in formula (9), when calculating the influence range, a circle is made with l' and l as radii, and the area in the circle is the range which can be influenced, that is, the possibility that the harmful substance diffuses in all directions is considered.
In the formula (9), r is a risk value calculated at a central point of a certain grid, and r0An environmental risk value that is a source of risk; x is the distance from the grid center point to the risk source, m; l' is the maximum value of the influence radius of the heavy injury area; l is the maximum impact radius value; wherein r is0P is the probability of an accident and C is the consequence of an accident.
In computing environmental risks, l' and r0It cannot be estimated accurately because l and l' are always directly related to the sum of the leakage of the hazardous material. Furthermore, l' and r0The value of (c) is variable in each environmental incident. It is therefore proposed that the affected radius can be calculated from the average leakage on a same industry scale.
And (3) estimating and determining the final influence radius of the risk accident according to the availability of the existing data and the hazard of taking the ratio of the material stock of the risk material to the critical value (namely the Q value) as a risk source. The Q value is a main factor affecting the diffusion radius of the risk source, and is mainly shown in the following aspects.
First, it is calculated that the primary source of risk in the campus is from businesses that have hazardous chemical storage volumes that exceed a threshold. Matching the case inauguration enterprises with inauguration enterprises in an Environmental Statistics Database (ESD) based on the current statistical data. The case data of enterprises with few risk substance stocks, enterprises without risk substances, cancelled enterprises and the like are all excluded. From the final matching results, it can be found that as the Q value increases, the risk spread radius of the enterprise increases.
Secondly, the Q value is an important influencing variable for the occurrence of an accident. If Q > 1.0, the source of risk must be further evaluated. In addition, the existing research has carried out the risk assessment work of the national region range according to the Q value, and shows that the Q value data can be applied to the assessment of the risks of environmental events in the Yangtze river economic zone and all places in China.
In summary, the Q value is closely related to the threshold. Therefore, matching can be carried out according to the Q value of the enterprise, and finally the diffusion radius is determined. While taking into account the result of the diffusion radius of the information diffusion method. For example, businesses are classified into three categories according to Q: q > 100, Q < 10 < 100, Q < 10, and then a lethal concentration range of 123 m to 4198 m was calculated based on the threshold pacs-3. Finally, the diffusion radius, the radius classification range and the standard are set according to the Q value in a partition mode.
TABLE 2 partitioning criteria and settings results for Q values, l' and l
In many case calculation cases, r0 and r can be calculated according to the average risk value of risk sources with the same property at home and abroad. This example calculates atmospheric and aquatic environment risk values for the risk of Natech with Q values as the vulnerability of risk binding receptors of risk sources. Q value and threshold number of risk substances refer to the grading standard method provided by the ministry of ecology: enterprise environmental accident risk classification method (HJ941-2018) (MEP, 2018).
The environmental risk values for the Natech risk include atmospheric environmental risk values and water environmental risk values.
And analyzing the atmospheric vulnerability based on the population density of the buffer area, and calculating the atmospheric environment risk value of the Natech risk. The calculation formula of the atmospheric environment value of the Natech risk is as follows:
V＝3.14×l2×d×50％
in the formula (10), d represents the population density in the different diffusion buffers, and 50% indicates that LD is used50Or LC50As a basis for calculating mortality, V represents the atmospheric environment receptor vulnerability index at risk of Natech.
And analyzing the vulnerability of the water environment based on the water body attribute indexes, and calculating a risk value of the Natech risk water environment. The water environment receptor vulnerability index S at the risk of Natech is determined by referring to related research results, the vulnerability index S is shown in a formula (11), and S represents the water environment receptor vulnerability index at the risk of Natech.
As shown in the table, the water environment risk value for the natach risk is calculated as follows:
in formula (11), S represents the water environment receptor vulnerability index at risk of Natech.
TABLE 3 Water environmental Risk vulnerability index for Natech Risk
The risk value of each point in the information matrix is added to represent the risk value of each grid, i.e.
The resulting risk is superimposed and displayed in a matrix in equation (12).
In the prior art, when dangerous substances have certain influence on the public, the average value of the highest acceptable level recommended by the Danish environmental protection agency, the Swedish environmental protection agency and the Netherlands construction environmental protection agency is 1.0 multiplied by 10-6. Wherein the minimum value of the unacceptable risk level which is more commonly used in China is 1.0 x 10-5. The embodiment integrates the above achievements, and finally divides the environmental risk into 5 grades with high risk (R is more than or equal to 10)-3) Relatively high risk (10)-4≤R＜10-3) Intermediate risk (10)-5≤R＜10-4) Relatively low risk (10)-6≤R＜10-5) Low risk (10)-8≤R＜10-6)。
And step 3: and visualizing the calculation result, drawing and analyzing the risk space distribution of the Natech.
Fig. 2 and fig. 3 show the spatial distribution of atmospheric and aquatic environment risk levels, respectively, for flood induced risk of Natech under scenario a. Overall, the spatial distribution of atmospheric and aquatic environment risks are similar. Taking the economic zone of the Yangtze river as an example, the distribution in high-risk areas of Shanghai, Su southwest and Wan southeast is relatively large; secondly, high risk areas are concentrated in the east of Hubei, the middle of Chongqing, the north of Zhejiang and other Yangtze areas. The overall comparison shows that the high risk level of atmospheric risk is about 2.60 times higher than the overall risk level of the aqueous environment. Wherein, in the atmospheric environment risk profile: the high risk area is 77174 square kilometers (3.69%); the relatively high risk area is 15100 square kilometers (0.70%); the area of the risk zone in and below the middle is 362416 square kilometers (17.37%); the area unaffected by the risk of Natech is 1632038 square kilometers (78.21%). In the water environment risk profile: the high risk area is 29605 square kilometers (1.42%); the higher risk area is 15100 square kilometers (2.49%); the area of the risk zone in and below the middle is 315750 square kilometers (15.13%); the area of the risk zone for the unaffected area Natech is 1689320 square kilometers (80.96%). Generally, in relatively high risk areas, the atmospheric risk is about 2/3 lower than the water risk. The areas of the intermediate and sub-intermediate risk regions are approximately the same. On the other hand, compared with the atmospheric and water environment risk level distribution results of the scene b and the scene c, the risk distribution range of the scene a and the scene b is not greatly different, and the high risk area of the scene c is relatively less. In scenario c, the area of the atmospheric environmental risk high risk area is 55943 square kilometers (2.68%), and the area of the environmental risk high risk area is 1097 square kilometers (0.05%). It can be concluded that the depth effect is greater than the velocity effect in flood induced Natech risk.
Example 2
This example is essentially the same as example 1, except that it calculates the risk of inducing Natech by an earthquake.
When the earthquake disaster probability is calculated in step 1.1, the earthquake frequency is calculated and determined (unit: times/year) mainly according to the statistics of the number of earthquake disasters occurring in China and surrounding areas from 1908 to 2019. Estimating the probability of the earthquake occurrence by adopting an information diffusion method according to the earthquake occurrence frequency, wherein the calculation formula is as follows:
sample value: y ═ Y1，y2，...，ym}；yjIs an watchMeasuring sample points, wherein m is the number of samples;
setting a disaster index discourse domain: u ═ u1，u2，...，unIn the formula, u1，u2，...，unAs a control point, uiRepresenting a region [ u ]1，un]The internal fixed interval is dispersed to obtain any discrete real value, and n represents the total number of discrete points.
Observing each single value in sample value set Y according to formula (13) to obtain sample YjThe carried information is spread to all points in the disaster indicator domain U.
In formula (13), i is 1, 2, and n, j is 1, 2, and m; h is the information diffusion coefficient and is,
in formula (14), b is max (y)j，j＝1，2，...，m)，a＝min(yjJ 1, 2,.. said, m), a, b being the minimum and maximum values, respectively, of the set of sample values (Y), m being the number of samples, the label
j 1, 2,.. m, then sample yjCan be expressed as a membership function of the corresponding fuzzy subset:
Equation (16) shows that if the observed value can only be selected as { u }1，u2，...，unOne of the values in (f), then the observed value is uiThe number of samples of (b) is q (u)i) Observation set by information diffusion { y1，y2，...，ym}. Using yjAll values of (a) as representative samples, it is clear that q (u)i) Usually not a positive integer but certainly a number not less than zero.
Suppose that
In the formula (17), Q is the number of samples Q (u)i) Although Q is theoretically m, Q and m are slightly different from each other because of an error in calculation.
Calculate the sample falling at u by equation (18)iThe frequency value of (b) as an estimate of the probability.
For disaster indicator X ═ { X1，x2，x13，...，xnB, usually take X as the disaster index universe, XiTaken as an element u in the theory domainiSurpass uiIs shown in equation (19):
p(ui) Is an estimate of the risk required.
According to the step 1.2, when the failure probability of equipment under natural disasters of Natech risks induced by earthquakes is calculated, the data analysis of industrial accidents induced by the earthquakes is carried out, and the major industrial accidents are more likely to be caused by the damaged storage tank. Campedel et al, statistically reported 78 Natech events induced by earthquakes, found that the atmospheric tank accounts for the highest percentage of all damaged equipment (80.3%). Based on the existing research results, the present embodiment mainly studies the atmospheric storage tank, and considers two cases of arbitrary filling degree and filling degree exceeding 50%, and the scenario setup is shown in table 4. In addition, the damage of the earthquake-induced device is closely related to magnitude and intensity, and the Peak Ground Acceleration (PGA) is closely related to earthquake intensity, so the embodiment mainly uses the PGA as a main parameter for calculating the failure probability of the earthquake trigger device.
Table 4. vulnerability and Probit coefficient (Y ═ k) of atmospheric storage tanks under earthquake action1+k2 ln(102PGA))
According to the regulations of the Chinese seismic intensity table (GB/T17742-2020), the average values of PGA corresponding to the intensities I-XII are respectively 0.0018g, 0.00369g, 0.00757g, 0.0155g, 0.0319g, 0.0653g, 0.135g, 0.279g, 0.577g, 1.19g, 2.47g and 3.55 g. And (3) adopting a Probit model to represent the failure probability of the storage tank under the earthquake disaster. Among them, PGA is used to measure the severity of earthquakes. PGA is related to the probability of failure of a device in a given limit state DS (damage state) or RS (risk state), and the vulnerability curve F available is shown in equation (20):
in equation (20), F is the cumulative value of the lognormal distribution F, μ is the mean, β is the standard deviation, α is a value exceeding a given DS or RS, and F is linearized with the Probit function to obtain the vulnerability model as follows:
Yi，j＝k1，i，j+k2，i，j ln(PGA) (21)
in the formula (21), Yi，jRepresents the Probit intermediate variable, where k1，i，jAnd k2，i，jIs a model coefficient related to device type i and damage state j, where k is related to1，i，jAnd k2，i，jThe calculation is mainly obtained by observing the development of the earthquake vulnerability relation according to a large amount of historical data sets. Coefficient k in the present embodiment1，i，jAnd k2，i，jAnd obtaining the calculation result through the storage tank damage condition in a large amount of seismic data. The PGA is a part of the gravitational constant, and the unit is g. Probit function variable Yi，jAssociated with vulnerability. The actual probability P (V) can be determined by comparing the variable Yi，jThe integral is calculated as shown in equation (22):
in equation (22), V ═ PGA, and the probability of damage is related to container loss or structural damage. RS is 1, which means that the earthquake has slight influence on the structure of the storage tank, and the loss of the container can be ignored; RS ═ 2 denotes structural damage to the housing or auxiliary equipment, resulting in "slight losses"; RS-3 represents an expansive or catastrophic failure of the storage tank, resulting in rapid complete loss of the containment. In addition, similar to the calculation of the failure probability of the equipment under the action of flood, the aggregation coefficient W is used for refining and optimizing the failure probability of the equipment under the influence of earthquake in the area.
In summary, the probability calculation formula of the earthquake-induced risk of Natech is as follows.
In the formula (23), PeIs the probability of earthquake, efProbability of failure of equipment under the influence of earthquake, WeIs the concentration factor.
Fig. 4 and 5 show the spatial distribution of atmospheric and aquatic environment risk levels, respectively, at the risk of earthquake-induced Natech in scenario a. From the distribution result graph, it can be found that high-risk and relatively high-risk regions are mainly distributed in the eastern region of Sichuan, the northern region of Yunnan and the southwest region of Chongqing. In comprehensive comparison, the high risk level of the atmospheric environmental risk is about 8.0 times higher than the overall risk level of the water environment. Wherein, in the atmospheric environmental risk distribution: the high risk area is 6615 square kilometers (0.32%); the relatively high risk area is 8138 square kilometers (0.39%); the area of the risk area under and above is 118243 square kilometers (5.67%); and an area unaffected by the risk of Natech of 1953732 square kilometers (93.63%). In the water environment risk distribution: the high risk area is 800 square kilometers (0.04%); the higher risk area is 2806 square kilometers (0.13%); the risk area of medium and below medium is 91222 square kilometers (4.37%); the area of the unaffected natach risk zone is 1991900 square kilometers (95.46%). In general, the atmospheric and aquatic environment distributions result in approximately the same area in the moderate and sub-moderate risk regions. On the other hand, the comparison of the atmospheric environmental risk levels in different scenes shows that the high risk region ratio in scene a (0.32%) and scene c (0.60%) is greater than that in scene b (0.04%) and scene d (0.08%). The comparison result of the water environment risk grades shows that the proportion of high risk areas under the scenes a (0.04%) and c (0.08%) is greater than that under the scenes b (0.01%) and d (0.01%). It can be seen that although the Natech risk level due to earthquake is low, it is greatly affected by the risk condition and filling degree. However, the risk distribution trend of each scene is approximately the same, and the proportion of the regions not affected by the risk of Natech in the four scenes is more than 93%.
Example 3
This example is essentially the same as example 2, except that it calculates the risk of typhoon-induced Natech.
When the typhoon disaster probability is calculated through the step 1.1, the typhoon frequency is mainly calculated according to the following two aspects, namely the typhoon frequency is calculated according to western pacific typhoon path statistical data, namely the typhoon path data from 1951 to 2018; the range (unit: times/year) affected by typhoon is obtained by taking the seven-grade wind circle radius of about 350 kilometers as a buffer area. The probability of typhoon occurrence is estimated by adopting an information diffusion method, which is the same as the calculation method of earthquake occurrence frequency.
According to the step 1.2, the probability of equipment failure under typhoon-induced Natech risk natural disaster is calculated, and researches show that during the period of the Richardy hurricane, the bending of the shell of the storage tank is mainly caused by strong wind rather than flood. Here, for strong winds, the influence of the wind during the probability of a typhoon-induced Natech risk is mainly considered. Generally, The Information of industrial Accidents caused by different natural disasters can be obtained by statistical Analysis of historical Data of some databases, such as ARIA (Analysis, Research and Information on accounts), FACTS (failure and accounts Technical Information System), MHIDAS (major hazardous indexes Data service), MARS (major Accident Reporting System) and ICHEME (TAD of Accident Database, organization of Chemical Engineers) and other databases.
The wind information for different loads provided in table 5 summarizes the fault probability for each fault type associated with high wind loads. The failure probability results of the faults of different types of storage tanks are calculated and shown in a table, according to the results, the leakage accidents caused by the damage of the storage tanks are found to be the main reasons of the fault types, the failure probability of the shell layer breakage is selected as the main influence probability during risk calculation, and the failure probability under the action of wind power is calculated according to the current typhoon data. Similar to the calculation of the failure probability of equipment under the influence of flood and earthquake, the concentration coefficient W is usedtThe equipment fault probability under the influence of the typhoon in the area is refined and optimized, and the Natech risk probability caused by the typhoon is calculated by the formula (24).
TABLE 5 wind disaster characterization based on Saffir/Simpson ratings
TABLE 6 calculation of failure probability for different types of tanks
Therefore, the probability calculation formula of the risk of typhoon-induced Natech is as follows
Nt＝Pt×tf (24)
tf＝Pw×Wt
In the formula (24), PtProbability of typhoon, tfFor the probability of failure of the apparatus under the influence of typhoons, PwIs the probability of failure under the action of wind force, WtIs the aggregation coefficient.
Fig. 6 and 7 show the risk spatial distribution of atmospheric and aquatic environment risk classes for typhoon-induced Natech risk. Wherein, the high-risk and relatively high-risk areas are mainly distributed in the east part of the Changjiang river economic zone, and are mainly distributed in the Changtriangle, the central and south part of Hunan, the Guizhou in the west of Jiang, the east part of Yunnan and the east part of Hubei. Overall, the spatial distribution of atmospheric and aquatic environment risks are similar. The overall comparison shows that the high risk level of atmospheric risk is about 1.6 times higher than the overall risk level of the aqueous environment. Wherein, in the atmospheric environmental risk distribution: the high risk area is 59536 square kilometers (2.85%); the relatively high risk area is 27096 square kilometers (1.29%); the area of the risk area under and above is 251181 square kilometers (12.04%); the area unaffected by the risk of Natech is 1748915 square kilometers (83.81%). Distribution of water environment risks: high risk area 36197 square kilometers (1.73%); the higher risk zone 30558 square kilometer (1.46%); risk zone 240145 square kilometer (11.51%) mid and below; the area unaffected by the risk of Natech is 1779828 square kilometers (85.29%). Generally, in relatively high risk areas, the atmospheric risk is about 1/5 lower than the water risk, and the areas of the medium and sub-medium risk regions are about the same.
The Yangtze river economic zone is one of the national strategic economic development areas. The industrial distribution is dense, and natural disasters frequently occur. In the research of various disaster risks in the prior art, systematic analysis and research on the risk of the Yangtze river economic zone Natech are lacked. The invention innovatively provides a grid Natech risk calculation method by coupling a probability model with an information diffusion method, and the calculation results show that the highest percentage of high risk areas of Natech induced by flood, earthquake and typhoon in the economic zone of Yangtze river respectively reaches 3.69%, 0.32% and 2.85%. Once the risk of Natech occurs, the economic environmental losses caused by these areas will be severe. Further, by combining enterprise comprehensive analysis, the Changjiang river economic zone is about 64136 risk enterprises, and the situation that the Risk is distributed around rivers and earthquake zones exists, so that the Natech risk prevention and control difficulty is high.
The invention provides a grid Natech risk assessment method by coupling a probability model and an information diffusion method, which aims at solving the problem that the current calculation model about the Natech risk probability is mostly concentrated on a specific enterprise or equipment and cannot be applied to area scale risk assessment. The method realizes the calculation of the Natech risk probability and the consequence of the region range by coupling a probability model and an information diffusion method. Different from the application of an information diffusion method in the prior art, the prior art is mainly applied to regional gridding environment risk assessment, and generally does not consider the cause of natural disasters, so that the method cannot be used for regional Natech risk assessment.
On the basis of the prior art, the natural disaster probability model is coupled to the risk calculation system so as to realize the application of the information diffusion method to the Natech risk assessment. Wherein, there is no fixed calculation standard about the risk diffusion radius in carrying on the Natech risk calculation, according to the experimental result of limited times, the calculation method of the invention finally overcomes the difficulty in estimating and confirming the final influence radius of the risk accident by introducing the ratio (namely Q value) of the material stock of the risk substance and the critical value as the hazard of the risk source; and the information diffusion method in consequence calculation is not suitable for specific reference of the Natech risk, and the calculation difficulty of the atmospheric environment receptor vulnerability and the water environment receptor vulnerability index in the Natech risk is overcome by introducing the buffer area population density and the water body attribute index.
In addition, currently, in large-scale regional risk assessment, assessment work is carried out on the basis of administrative regions in most of research, an index method and the like are mainly adopted, systematic and high-precision research is still lacked, and hot spots in high-risk regions cannot be refined. The invention innovatively provides a grid Natech risk assessment method combining a probability model and an information diffusion method, and in the process, high-precision risk assessment is carried out by taking 1km multiplied by 1km as a unit, and the precision is higher than that of a district level and a county level. In the current Natech risk assessment research, the problems that risk sources and receptors are not sufficiently considered, assessment factors and assumptions are single, risk types are single and the like exist, assessment results are incomplete, the risk types of hot spot areas cannot be accurately identified, and the difficulty of Natech risk management is increased by the factors. The calculation model comprehensively considers the relationship among the risk source, the probability and the vulnerability, and can effectively identify the risk hotspots under different disaster types.
The invention provides a grid Natech risk assessment method for coupling a probability model and an information diffusion method. Flood, earthquake and typhoon induced Natech risks were evaluated with a spatial resolution of 1km x 1km, identifying and analyzing high risk areas. The method makes up the problem of low evaluation precision of large-scale areas, is beneficial to identifying high-risk hot areas, realizes preferential management of the Natech risk, and provides a direction for reducing the Natech risk. Due to the limited availability of data, the risk Q value used in the natach risk spread study instead of the concentration of the risk substance may lead to some uncertainty in the risk assessment. On the other hand, in calculating the risk probability of Natech, the scenario assumption is used for flood and earthquake, possibly with uncertainty. To address this problem as much as possible, setting other scenarios as a control group for sensitivity analysis reduces the uncertainty of the calculation.
Different risk management and control points can be made for different types of Natech risks, and reference is provided for avoiding unreasonable industrial structures. For example, in fig. 4 and 5, the natach risk in the vicinity of the seismic zone of the sichuan section is the most serious area in the entire economic zone of the Yangtze river, and the unreasonable industrial structure will exacerbate the occurrence of the natach risk. And the industrial layout is recommended to be adjusted according to different types of the Natech risks, so that the risk level of the environmental events of the Yangtze river economic zone is reduced. Finally, support is provided for further improving a risk management system of the Yangtze river economic zone and strengthening risk control of multiple disaster species, and reference is hoped to be provided for adding Natech risk management into the management system in the future.
The invention and its embodiments have been described above schematically, without limitation, and the invention can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiment shown in the drawings is only one of the embodiments of the invention, the actual structure is not limited to the embodiment, and any reference signs in the claims shall not limit the claims. Therefore, if a person skilled in the art receives the teachings of the present invention, without inventive design, a similar structure and an embodiment to the above technical solution should be covered by the protection scope of the present patent.
Claims (8)
1. A Natech risk calculation method of a coupling probability model and an information diffusion method is characterized in that a Natech risk probability is calculated based on a grid information diffusion method, a calculation result is visualized, and a Natech risk space distribution map is drawn;
the Natech risk probability is calculated through natural disaster probability and equipment failure probability under natural disasters, and the Natech risk calculation formula is as follows:
Natech risk＝P(NH)×P(release|NH)×Consequence
wherein P (NH) represents a natural disaster probability, P (release | NH) represents a conditional probability of hazardous substance release under a natural disaster, and sequence represents a Natech risk result, the Natech risk including an atmospheric environmental risk and a water environmental risk;
respectively constructing sub-risk information matrixes for each environmental risk source, namely dividing a risk calculation area into 1km multiplied by 1km grids which are expressed by m multiplied by n matrixes, and forming elements q in the matrixesijRepresenting information of a corresponding grid area in space, and representing a matrix expression formula for a calculation area as follows:
the information diffusion influence range calculation formula is as follows:
wherein r is a risk value calculated at a central point of a certain grid, r0An environmental risk value that is a source of risk; x is the distance from the central point of the grid to the risk source, and the unit is m; l' is the maximum value of the influence radius of the heavy injury area; l is the maximum impact radius value; wherein r is0P × C, P is the probability of an accident and C is the consequence of an accident; determining the influence radius of the risk accident according to the hazard of the risk source which is the ratio of the material stock of the risk material to the critical value;
the calculation formula of the atmospheric environment value of the Natech risk is as follows:
r0＝P×C，
V＝3.14×l2×d×50％
the water environment risk value of the Natech risk is calculated as follows:
r0＝P×C，
S＝S1×W1+S2×W2+S3×W3；
wherein Q represents the ratio of the material stock of the risk material to the critical value, V represents the atmospheric environment receptor vulnerability index, S represents the water environment receptor vulnerability index, d represents the population density in different diffusion buffer zones, and 50% indicates that LD is used50Or LC50As a basis for calculating mortality, W1, W2 and W3 are index weights, and S1, S2 and S3 are index scores.
2. The Natech risk calculation method by coupling the probability model with the information diffusion method according to claim 1, wherein the risk calculation models are respectively constructed according to different Natech risk inducing factors of flood, earthquake or typhoon.
3. The method for calculating Natech risk by coupling a probability model with an information diffusion method according to claim 2, wherein for the Natech risk induced by flood, the flood probability is calculated using the flood recurrence period as a parameter;
when the equipment failure probability model under the action of flood disasters is constructed, the flood scenes are firstly classified according to the water depth and the speed, the storage tank leakage model under the action of flood is constructed according to the volume, the diameter, the tank length and the wall thickness of the cylinder body of the storage tank,
the leakage model expression under the action of the flood of the vertical storage tank is as follows:
wherein CFL1At the critical fill level, pwsIs flood hydrostatic pressure, pwdKinetic pressure of flood water, pcrCritical pressure of the vessel, pfIs the internal pressure of the container, g is the acceleration of gravity, H is the height of the storage container,
at the point of the maximum fill level, the fill level,
at minimum filling level, Ψ1The conditional probability of leakage of the vertical storage tank;
the leakage model expression under the action of the flood of the horizontal storage tank is as follows:
wherein, CFL2At a critical filling level, prefDensity of a reference substance for defining a correlation of CFLs, A 'being a modified A coefficient of the generic storage substance, B' being a modified B coefficient of the generic storage substance, Ψ2The conditional probability of a leakage from a horizontal tank,
at the point of the maximum filling level,
at a minimum fill level;
and matching the storage tank leakage condition probabilities under each scene according to the enterprise industry type and the enterprise scale, sequencing all enterprises, and distributing according to the probability percentile to obtain the failure probability of the equipment under the flood disaster.
4. The Natech risk calculation method by coupling the probabilistic model with the information diffusion method according to claim 2, wherein for the Natech risk induced by the earthquake, the earthquake frequency is calculated from the number of the historical earthquake disasters, and the probability of the earthquake occurrence is calculated by the information diffusion method according to the earthquake occurrence frequency;
calculating the failure probability of equipment under the earthquake disaster according to the vulnerability and the Probit coefficient of the equipment under the earthquake action, wherein the Probit model represents the failure probability of the storage tank under the earthquake disaster, and a vulnerability model is constructed according to the equipment type and the damage state, and the vulnerability curve F is as follows:
wherein F is the cumulative value of lognormal distribution F, mu is the mean value, beta is the standard deviation, alpha is the value exceeding given DS or RS, PGA represents the earthquake peak ground acceleration, DS represents the damage state, RS represents the risk state, F is linearized by the Probit function, and the vulnerability model is obtained as follows:
Yi，j＝k1，i，j+k2，i，jln(PGA)
Yi,jrepresents the Probit intermediate variable, where k1,i,jAnd k2,i,jIs a model coefficient related to the device type i and damage state j by fitting the variable Yi,jAnd integrating to calculate the failure probability of the equipment, wherein the calculation formula is as follows:
where V ═ PGA.
5. The Natech risk calculation method by coupling a probability model with an information diffusion method according to claim 2, wherein for a typhoon-induced Natech risk, a typhoon frequency is calculated from typhoon path data of time and area, and a probability of occurrence of a typhoon is calculated by an information diffusion method from the frequency of occurrence of a typhoon;
and calculating the failure probability of the equipment under the action of the typhoon disaster according to the failure probability of the shell layer breakage under the action of the typhoon disaster and the failure probability under the action of the wind.
6. The method for calculating the risk of Natech by coupling the probability model with the information diffusion method according to claim 3, 4 or 5, wherein the concentration is calculated according to the enterprise distribution, and the concentration coefficient W is calculated by the formula:
wherein N isdistrictThe number of enterprises in the county of the grid is shown, and N is the total number of enterprises in the risk calculation area.
7. A Natech risk calculation system that couples a probability model with an information diffusion method, characterized in that the Natech risk calculation method that couples a probability model with an information diffusion method according to any one of claims 1 to 6 is used, the system including a data acquisition unit, a data storage unit, a risk calculation unit, and a visualization unit;
the data acquisition unit is used for acquiring the Natech risk related data in the calculation area, the data storage unit is used for storing the Natech risk related data acquired by the data acquisition unit, the risk calculation unit performs Natech risk calculation according to the Natech risk related data acquired by the data acquisition unit, and the visualization unit generates a Natech risk map according to the calculation result of the risk calculation unit and displays the Natech risk in a visualization mode.
8. The Natech risk calculation system coupling the probability model and the information diffusion method according to claim 7, wherein the risk calculation unit comprises a natural disaster probability calculation module, a natural disaster lower equipment failure probability calculation module and an information diffusion calculation module,
the natural disaster probability calculating module calculates the natural disaster probability; the natural disaster equipment failure probability calculation module is used for constructing an equipment failure probability model under the action of natural disasters and calculating the equipment failure probability under the natural disasters; the information diffusion module is used for performing information diffusion on the Natech risk probability calculated by the natural disaster probability calculation module and the equipment failure probability calculation module under the natural disaster, and calculating the Natech risk probability.
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