CN113821989A - Emergency disposal simulation risk equipment modeling method and device and storage medium - Google Patents

Emergency disposal simulation risk equipment modeling method and device and storage medium Download PDF

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CN113821989A
CN113821989A CN202010561408.1A CN202010561408A CN113821989A CN 113821989 A CN113821989 A CN 113821989A CN 202010561408 A CN202010561408 A CN 202010561408A CN 113821989 A CN113821989 A CN 113821989A
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data
accident
disaster
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李磊
张卫华
夏涛
袁纪武
赵祥迪
王正
矫恒超
纪键锋
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China Petroleum and Chemical Corp
Beijing University of Chemical Technology
Sinopec Qingdao Safety Engineering Institute
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Beijing University of Chemical Technology
Sinopec Qingdao Safety Engineering Institute
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Abstract

The invention relates to the field of safety engineering technology and information technology, and provides a modeling method and device for emergency disposal simulation risk equipment and a storage medium. The method comprises the following steps: acquiring process data, accident data and disaster field data of equipment; constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data; when an accident phenomenon is caused by the ideal equipment model, constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model; and combining the ideal equipment model and the incident model to form a risk equipment model. The risk equipment model comprises an ideal equipment model and an accident model, wherein the ideal equipment model describes equipment from three levels of process data, accident data and disaster influence, and the accident model is independent from the ideal equipment model and can be reused, so that elements of safety simulation comprise not only the equipment and the accident, but also the disaster caused by the accident and the damage of the disaster to the equipment.

Description

Emergency disposal simulation risk equipment modeling method and device and storage medium
Technical Field
The invention relates to the field of safety engineering technology and information technology, in particular to a modeling method and device for emergency disposal simulation risk equipment and a storage medium.
Background
At present, in the industries of petroleum, chemical industry, metallurgy and the like, the construction process simulation system is more and more emphasized, and becomes an important component part in the industry safety engineering. The process equipment simulation modeling is a fundamental stone for constructing a process simulation system, and a simulation mathematical model (hereinafter referred to as an equipment model) for directly describing entity equipment is required to correspond to each appearing entity equipment.
However, in the current device modeling scheme, the parameter change condition of the device itself and the accident possibly caused by the device itself are often described only for each device, and the association between different devices and the association between the accidents caused by different devices are not considered. In an actual equipment operation scene, accidents often occur in domino, namely a series of accidents sequentially arranged in time sequence can occur, for example, one accident is a result of a previous accident, the occurrence of the accident can lead to the occurrence of a next accident, the accidents depend on one accident to form a series, just like a series of dominos which are close to and erected front and back, and the falling of a first domino can lead to the continuous falling of the whole series of dominos.
Therefore, the inventor of the application finds that new damage may be caused to the equipment due to the influence of accident domino phenomenon in the process of implementing the scheme of the invention, and the damaged condition of the equipment cannot be accurately described by the modeling scheme only considering the parameter change condition of the equipment.
Disclosure of Invention
The embodiment of the invention aims to provide a modeling method, a modeling device and a storage medium for emergency treatment simulation risk equipment, which are used for solving the problem that the existing equipment modeling scheme cannot accurately describe the damage of the equipment due to accident domino phenomenon.
In order to achieve the above object, an embodiment of the present invention provides an emergency treatment simulation risk device modeling method, including: acquiring process data of equipment, wherein the process data is used for describing the operation condition of materials involved in a dynamic process in the equipment; acquiring accident data of the equipment, wherein the accident data is used for describing the change condition of first process data after the equipment has an accident; acquiring disaster field data of the equipment, wherein the disaster field data is used for describing a second process data change condition of the equipment in a disaster field; constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data; when an accident phenomenon is caused by the ideal equipment model, constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model; and combining the ideal equipment model and the incident model to form a risk equipment model.
Optionally, the process data comprises any one or more of the following data in the plant: temperature, pressure, flow, level, and material information.
Optionally, the accident data includes process data corresponding to the equipment in any one or more of the following accident states: fire, explosion, leakage, plugging, lightning failure, material failure, strength failure, and structural failure.
Optionally, the disaster field data includes a disaster field type, disaster-related geographic information, and a disaster field change condition, and the acquiring the disaster field data of the device includes: determining a disaster field type according to the accident type, wherein the disaster field type comprises a temperature field corresponding to the fire accident, an energy field corresponding to the explosion accident and a toxic gas field corresponding to the toxic gas accident; acquiring disaster-related Geographic Information through a GIS (Geographic Information System), wherein the disaster-related Geographic Information comprises equipment position Information, equipment geometric dimensions and topographic and geomorphic Information of an accident occurrence place; and performing simulation calculation of the disaster scene by adopting a CFD (Computational Fluid Dynamics) simulation technology to obtain the change condition of the disaster field.
Optionally, the performing, by using a computational fluid dynamics CFD simulation technique, simulation calculation of a disaster scene includes: the method comprises the steps of carrying out grid division on a disaster scene, calculating the disaster scene by adopting a CFD simulation technology according to each grid, and simplifying a calculation result based on a preset calculation efficiency requirement so as to obtain a calculation result finally showing real-time change conditions of the disaster scene.
Optionally, the emergency treatment simulation risk device modeling method further includes: and acquiring environmental data of the equipment, and configuring the environmental data in the ideal equipment model.
Optionally, the emergency treatment simulation risk device modeling method further includes: and acquiring a simulation result of the risk equipment model responding to the current disaster field data to carry out disaster simulation, and determining the damage condition of the current disaster field to the equipment based on the simulation result, wherein the damage condition comprises a damage type, a damage area and a damage degree.
Optionally, the emergency treatment simulation risk device modeling method further includes: establishing a rescue model of the equipment based on corresponding rescue basic data of the equipment, wherein the rescue model is associated with the risk equipment model; and triggering the rescue model to carry out simulation so as to obtain corresponding rescue data, and updating the disaster field data based on the rescue data.
On the other hand, an embodiment of the present invention further provides an emergency treatment simulation risk device modeling apparatus, including: the device comprises a process data acquisition module, a data processing module and a data processing module, wherein the process data acquisition module is used for acquiring process data of equipment, and the process data is used for describing the running condition of materials involved in a dynamic process in the equipment; the accident data acquisition module is used for acquiring accident data of the equipment, wherein the accident data is used for describing the change condition of first process data after the equipment is in an accident; the disaster field data acquisition module is used for acquiring disaster field data of the equipment, wherein the disaster field data is used for describing the second process data change condition of the equipment in a disaster field; the first modeling module is used for constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data; the second modeling module is used for constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model when the accident phenomenon is caused by the ideal equipment model; and a third modeling module for combining the ideal equipment model and the incident model to form a risk equipment model.
Optionally, the process data comprises any one or more of the following data in the plant: temperature, pressure, flow, level, and material information.
Optionally, the accident data includes process data corresponding to the equipment in any one or more of the following accident states: fire, explosion, leakage, plugging, lightning failure, material failure, strength failure, and structural failure.
Optionally, the disaster field data includes a disaster field type, disaster-related geographic information, and a disaster field change condition, and the disaster field data obtaining module is configured to obtain the disaster field data of the device, and includes: determining a disaster field type according to the accident type, wherein the disaster field type comprises a temperature field corresponding to the fire accident, an energy field corresponding to the explosion accident and a toxic gas field corresponding to the toxic gas accident; acquiring disaster-related geographic information through a GIS, wherein the disaster-related geographic information comprises equipment position information, equipment geometric dimension and topographic and geomorphic information of an accident occurrence place; and performing simulation calculation on the disaster scene by adopting a CFD simulation technology to obtain the change condition of the disaster field.
Optionally, the performing, by using the CFD simulation technique, simulation calculation of the disaster scene includes: the method comprises the steps of carrying out grid division on a disaster scene, calculating the disaster scene by adopting a CFD simulation technology according to each grid, and simplifying a calculation result based on a preset calculation efficiency requirement so as to obtain a calculation result finally showing real-time change conditions of the disaster scene.
Optionally, the emergency treatment simulation risk device modeling apparatus further includes: and the environment data acquisition module is used for acquiring the environment data of the equipment and configuring the environment data in the ideal equipment model.
Optionally, the emergency treatment simulation risk device modeling apparatus further includes: and the damage determining module is used for acquiring a simulation result of the risk equipment model responding to the current disaster field data to carry out disaster simulation, and determining the damage condition of the current disaster field to the equipment based on the simulation result, wherein the damage condition comprises a damage type, a damage area and a damage degree.
Optionally, the emergency treatment simulation risk device modeling apparatus further includes: a rescue modeling module for establishing a rescue model of the device based on corresponding rescue basic data of the device, wherein the rescue model is associated with the risk device model; and the data updating module is used for triggering the rescue model to carry out simulation so as to obtain corresponding rescue data, and updating the disaster field data based on the rescue data.
In another aspect, the present disclosure provides a machine-readable storage medium having stored thereon instructions for causing a machine to perform the emergency treatment simulation risk device modeling method described above.
Through the technical scheme, the risk equipment model comprises an ideal equipment model and an accident model, wherein the ideal equipment model describes equipment from three levels of process data, accident data and disaster influence, the accident model is independent from the ideal equipment model and can be reused, and compared with the traditional equipment model, the risk equipment model enables the equipment to sense the damage of a disaster field caused by all accidents of the equipment or other equipment, so that the elements of safety simulation not only comprise the equipment and the accidents, but also comprise the damage of the disasters and the disasters caused by the accidents to the equipment, the elements of the safety simulation are perfected, the simulation is closer to the field, the accident reason can be analyzed, the emergency plan can be formulated, personnel training can be carried out, and the safety and the stability of equipment operation are improved.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 is a schematic flow chart of a first method for modeling emergency treatment simulation risk equipment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a modeling method for emergency treatment simulation risk equipment according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an emergency treatment simulation risk equipment modeling apparatus according to a third embodiment of the present invention; and
fig. 4 is a schematic structural diagram of a risk equipment model taking a storage tank as an example in the embodiment of the present invention.
Description of the reference numerals
310 process data acquisition module 320 accident data acquisition module
330 disaster site data acquisition module 340 first modeling module
350 second modeling Module 360 third modeling Module
370 environmental data acquisition module 380 injury determination module
390a rescue modeling module 390b data update module
410 storage tank ideal model 421 liquid pool model
422 conventional pool fire model 423 torch model
424 overpressure explosion model 425 damaged explosion model
426 residual liquid pool fire model
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
Example one
Fig. 1 is a schematic flow chart of a modeling method for emergency treatment simulation risk equipment according to an embodiment of the present invention, where the equipment may be each physical equipment present in petroleum, chemical and metallurgical installations. As shown in fig. 1, the emergency treatment simulation risk equipment modeling method may include the steps of:
and step S110, acquiring process data of the equipment.
The process data is used to describe the operation of the materials involved in the dynamic process in the equipment, and for example, the process data can be used to reflect the inflow, outflow and accumulation of the materials involved in the dynamic process in various equipment (such as heat exchangers, tanks, towers, reactors, etc.).
Preferably, the process data includes any one or more of the following data in the plant: temperature, pressure, flow, level, and material information.
And step S120, acquiring accident data of the equipment.
The accident is the change of the running state of the equipment caused by the risk of the equipment or the change of the external condition, and the accident data is used for describing the change situation of the first process data after the accident happens to the equipment.
Preferably, the accident data comprises process data corresponding to the equipment in any one or more of the following accident states: fire, explosion, leakage, plugging, lightning failure, material failure, strength failure, and structural failure. Based on these accident states, the accident data may also be understood to reflect accident phenomena that may be caused by the equipment.
And step S130, acquiring disaster field data of the equipment.
Wherein the disaster site data is used for describing the second process data change condition of the equipment in the disaster site. The "second" herein is intended to be distinguished from the "first process data variation" caused by the accident in step S120.
Preferably, the disaster scenario data comprises disaster scenario types, disaster-related geographical information and disaster scenario variations, which may also be understood as a description of the consequences of the accident phenomenon. Accordingly, in the embodiment of the invention, the introduction of disaster field data aims to deal with the accident domino phenomenon existing in the petroleum, chemical and metallurgical industries. For example, the final results of an accident include combustion, explosion, toxic gas (liquid) leakage, etc., so the consequences of the accident can be described as a "temperature field", an "energy field" and a "toxic gas mass", and the consequences of the accident can cause new damage to related equipment and field personnel, thereby forming an accident domino phenomenon.
In a preferred embodiment, the method of acquiring the disaster site data may include:
1) the disaster site type is determined according to the accident type, and includes, for example, a temperature field corresponding to a fire accident, an energy field corresponding to an explosion accident, and a toxic gas field corresponding to a toxic gas accident, etc. In addition, the disaster field type may also include a concentration field.
2) And acquiring disaster-related geographic information through the GIS, wherein the disaster-related geographic information comprises equipment position information, equipment geometric dimension, topographic and geomorphic information of an accident occurrence place and the like.
3) And (3) performing simulation calculation on the disaster scene by adopting a CFD simulation technology to obtain the change condition of the disaster scene.
In a more preferred embodiment, the performing of the simulation calculation of the disaster scenario by using the CFD simulation technique may include: the method comprises the steps of carrying out grid division on a disaster scene, calculating the disaster scene by adopting a CFD simulation technology according to each grid, and simplifying a calculation result based on a preset calculation efficiency requirement so as to obtain a calculation result finally showing real-time change conditions of the disaster scene. The smaller the grid is, the more accurate the calculation result is, but the calculation workload is large and the time consumption is longer, so that the calculation efficiency requirement can be preset to meet the real-time requirement or super real-time requirement of calculation.
And step S140, constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of the corresponding equipment based on the acquired technological data, accident data and disaster field data.
The ideal equipment model is a model for describing the running state of the entity equipment, and the described technological process, accident phenomenon and disaster field perception are used for reflecting the running state of the equipment.
The equipment modeling is a common simulation technology, and technicians in the related field can realize equipment modeling and model simplification by combining rigorous chemical engineering correlation theory, reliable numerical analysis and the like based on acquired process data, accident data, disaster field data and the like.
In a preferred embodiment, environmental data of the device may also be obtained and configured in the ideal device model. That is, the construction of the ideal equipment model is further refined based on the environmental data. Such as weather, temperature, humidity, etc. around the device.
And S150, when an accident phenomenon is caused by the ideal equipment model, constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model.
Specifically, the ideal equipment model can describe accident data, so that the accident itself can be simulated, but the accident simulation and the equipment simulation are combined in the same model, and the actual equipment and the accident phenomenon caused by the actual equipment are independent, so that the accident simulation is not consistent with the actual physical phenomenon, and the accident simulation cannot be independently reused by being separated from the equipment simulation. Therefore, in step S150, based on the accident data, after the equipment has a relevant accident, the accident phenomenon caused by the equipment is modeled independently, and the "equipment accident" is separated from the "accident modeling" so that the "accident" exists as an independent simulation module, which on one hand conforms to the actual physical phenomenon, and on the other hand, realizes the reuse of the "accident model".
It should be noted that the accident model simulation may further cause new accidents, and all the disasters caused by the accidents may have adverse effects on the operation of the physical equipment.
And step S160, combining the ideal equipment model and the accident model to form a risk equipment model.
The risk equipment model is a model which can describe the running state of the entity equipment and can also describe accidents caused by the equipment, and therefore the risk equipment model comprises an ideal equipment model and an accident model.
It should be noted that "ideal" in the ideal equipment model is mainly used to distinguish from "risk" in the risk equipment model, and both of them substantially represent one equipment model.
Preferably, combining the ideal equipment model and the accident model comprises: and configuring and connecting the ideal equipment model and the accident model, so that logistics and information flow can be transmitted between the ideal equipment model and the accident model.
For example, as shown in the above steps S110 to S140, the ideal equipment model considers the operation state of the equipment itself, and the model and the accident caused by the model only complete data interaction and does not calculate the relevant information of the accident. Based on the above, the embodiment of the invention rebuilds a separate simulation model, namely an accident model, for the material (liquid or gas) leaked out of the equipment after the accident happens to the ideal equipment model.
Accordingly, the simulation equipment model constructed in the steps S110 to S160 is a combination of "ideal equipment + accident model", and the combined ideal equipment model and accident model both keep operating independently, but perform dynamic data interaction between them, and are consistent with the operating situation of the physical equipment.
To sum up, the risk constructed in the embodiment of the invention separates an ideal equipment model from an accident model, wherein the ideal equipment model describes the technological process of the equipment based on technological data, realizes the calculation of the technological data of the equipment in an accident state based on accident data and realizes the calculation of the technological data of the equipment in a disaster field based on disaster field data, namely the ideal equipment model is equivalent to describing the equipment from three levels of technological data, accident data and disaster influence, compared with the traditional equipment model, the equipment can sense the damage of the accident disaster field of the equipment or other equipment, so that the elements of safety simulation not only comprise the equipment and the accident, but also comprise the damage of the accident and the disaster to the equipment, the elements of safety simulation are perfected, the simulation is closer to the scene, the analysis of accident reasons, the emergency plan, the personnel training and the like are facilitated, the safety and the stability of the equipment operation are improved.
Example two
Fig. 2 is a schematic flow chart of a modeling method for emergency handling simulation risk equipment according to a second embodiment of the present invention, where the method further includes, on the basis of steps S110 to S160 in the first embodiment: step S170, obtaining a simulation result of the risk equipment model performing disaster simulation in response to the current disaster field data, and determining the damage condition of the current disaster field to the equipment based on the simulation result.
The disaster field data comprises disaster field data of all accidents corresponding to the ideal equipment model and accident model simulation, and the damage conditions comprise damage types, damage areas and damage degrees.
In combination with the above, the existence of the accident domino phenomenon may cause some devices to be subjected to new damages caused by accidents caused by the devices or accidents caused by other devices, and the constructed risk device model may simulate disaster triggering, dynamic disaster evolution processes and damage conditions of the devices in the current disaster field after the accident occurs based on accident data and disaster field data. Wherein the accident model is also used for accident phenomena caused by injuries of a disaster site.
Therefore, the second embodiment of the invention determines the specific damage condition of the disaster site to the equipment based on the simulation result of the constructed risk equipment model. For example, the type of damage suffered can be determined according to the type of disaster field shown in the simulation result, such as damage suffered by a temperature field; determining damage areas, such as the positions of equipment damage, according to disaster-related geographic information shown in the simulation results; the damage degree of the equipment can be obtained according to the change situation of the disaster field calculated by CFD shown in the simulation result.
Therefore, the second embodiment of the present invention utilizes the constructed risk equipment model, so that the equipment can sense the damage condition of the disaster site caused by all accidents of the equipment or other equipment, which is equivalent to adding a damage sensing mechanism in the risk equipment model, thereby improving the simulation elements of the risk equipment model and further realizing the full-element simulation of the risk equipment model.
In addition, the occurrence and development process of 'accident domino' can be simulated by using the result of disaster perception and an accident model which operates independently. For example, for accident generation, it is based on the initial event. This initial event, also called a fuse event, is the first event (or accident) to occur, the so-called trigger event. If the accident caused by the accident model simulation is the initial accident of 'accident domino', an accident phenomenon, such as leakage, fire or explosion, may occur after the accident occurs, and the change of the equipment operation parameters may also be caused. After the initial event occurs, a certain accident phenomenon is generated, and then the calculation of a damage sensing mechanism in the equipment model of the peripheral equipment is triggered, so that the peripheral equipment enters an accident state, and a new accident phenomenon is generated. In this process, the events (or accidents) occurring in the field and nearby equipment and people around them, which are caused by the initial events through some energy diffusion or mass diffusion action, can be called secondary events. By analogy, one event depends on one event to form a series of accident models, so that the occurrence and development processes of accident domino are completely simulated.
EXAMPLE III
The third embodiment of the present invention further provides a modeling method for emergency treatment simulation risk equipment, which based on the first embodiment or the second embodiment, may further include: establishing a rescue model of the equipment based on corresponding rescue basic data of the equipment, wherein the rescue model is associated with the risk equipment model; triggering the rescue model to carry out simulation so as to obtain corresponding rescue data; and updating the disaster site data based on the rescue data.
Preferably, the rescue model can be integrated into the risk device model to complete the simulation elements of the risk device model to further enable full-element simulation.
Specifically, after a disaster, such as a fire, is found, the operator may operate the rescue model simulation to perform some rescue measures, such as simulation of fire extinguishment by fire extinguishers, so that it is known that rescue data generated by rescue of the rescuer may have an influence on the disaster site, such as reduction of flame temperature by fire extinguishment. Therefore, the third embodiment further updates and observes disaster site data in real time based on the rescue data to accurately reflect changes in the disaster site data.
Therefore, the embodiment of the invention further combines the rescue model, not only realizes rescue simulation, but also can ensure the accuracy of disaster field simulation, and also can provide rescue data support for formulating emergency plans, so that the elements of safety simulation can also comprise rescue elements, thereby promoting the realization of full-element simulation.
Example four
Fig. 3 is a schematic structural diagram of an emergency disposal simulation risk equipment modeling apparatus according to a fourth embodiment of the present invention, which is based on the same inventive concept as the emergency disposal simulation risk equipment modeling method. As shown in fig. 3, the emergency treatment simulation risk device modeling apparatus may include: a process data obtaining module 310, configured to obtain process data of a device, where the process data is used to describe an operation condition of a material involved in a dynamic process in the device; the accident data acquisition module 320 is configured to acquire accident data of the equipment, where the accident data is used to describe a first process data change situation after an accident occurs to the equipment; a disaster field data acquiring module 330, configured to acquire disaster field data of the equipment, where the disaster field data is used to describe a second process data change situation of the equipment in a disaster field; the first modeling module 340 is used for constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data; a second modeling module 350 for constructing an accident model for simulating an accident phenomenon caused by the ideal equipment model when the accident phenomenon is caused by the ideal equipment model; and a third modeling module 360 for combining the ideal equipment model and the incident model to form a risk equipment model.
In a preferred embodiment, the emergency treatment simulation risk device modeling apparatus further includes: an environment data obtaining module 370, configured to obtain environment data of the device, and configure the environment data in the ideal device model.
In a preferred embodiment, the emergency treatment simulation risk device modeling apparatus further includes: the damage determining module 380 is configured to obtain a simulation result of the risk equipment model performing disaster simulation in response to the current disaster field data, and determine a damage condition of the current disaster field to the equipment based on the simulation result, where the damage condition includes a damage type, a damage area, and a damage degree.
In a preferred embodiment, the emergency treatment simulation risk device modeling apparatus further includes: a rescue modeling module 390a, configured to build a rescue model of the device based on rescue basic data corresponding to the device, where the rescue model is associated with the risk device model; and a data updating module 390b, configured to trigger the rescue model to perform simulation to obtain corresponding rescue data, and update the disaster field data based on the rescue data.
For details and effects of the modeling apparatus for emergency disposal simulation risk equipment, reference may be made to the first to third embodiments of the modeling method for emergency disposal simulation risk equipment, which are not described herein again.
In a preferred embodiment, the emergency treatment simulation risk equipment modeling apparatus may include a processor and a memory, the process data acquisition module 310 to the data update module 390b are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to one or more, and the device modeling is realized by adjusting the kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
EXAMPLE five
The fifth embodiment is an application example. An application example of the emergency treatment simulation risk equipment modeling method and device according to the embodiment of the invention is described below with reference to a specific scenario, and the equipment related to the application example takes a storage tank as an example.
Fig. 4 is a schematic diagram of an ideal equipment model constructed by the emergency treatment simulation risk equipment modeling method according to the embodiment of the invention in an application example of the invention.
Fig. 4 is a schematic diagram of an application example of the storage tank in the embodiment of the present invention. As shown in FIG. 4, a tank ideal model 410 and, independently thereof, a plurality of accident models are established, including: a liquid pool model 421, a conventional pool fire model 422, a torch model 423, an overpressure explosion model 424, a damaged explosion model 425, a residual liquid pool fire model 426 and the like. With reference to fig. 4 and the accident domino theory, the following two types of accidents may be involved in the present application:
(1) risk accident
The risk accident is an accident caused by the equipment, and can also comprise the following two types of accidents:
(a) leakage at the bottom of the tank
When tank bottom leakage occurs, the leakage amount is injected into the liquid pool model 421, and the liquid pool model 421 calculates the condition that the surface area of the liquid pool is gradually enlarged according to the components and the state of the material.
After the materials in the liquid pool are combusted, the liquid pool can transmit the fuel gasification amount to the conventional pool fire model 422, and the conventional pool fire model 422 calculates the related data of the flame.
(b) Leakage at the top of the tank
When a tank top leak occurs, if the leak is combustible gas, the leak amount is injected into the torch model 423, and the relevant data is calculated by the torch model 423.
This risk incident is understood to be the initial event mentioned above.
(2) Accident of disaster site
That is, the tank has triggered a new secondary event (or incident) based on the initial event (or incident) that has been initiated, creating a disaster site that may affect the tank itself or other equipment.
(a) Explosion in a tank
When a fire disaster occurs near the storage tank, the storage tank is in a temperature field, the radiant heat can cause the evaporation capacity of a liquid phase in the tank to increase, the liquid phase transfers mass to a gas phase, the molar concentration of the gas phase increases, the temperature rises, and further the pressure of the gas phase rises. When the gas phase pressure exceeds a certain range, an explosion is formed. This explosion model uses an overpressure explosion model 424 in the tank, the input of which is a parameter of the gas fraction in the tank.
(b) Explosion of tank
After an explosion occurs in the tank, the data related to the energy field of the explosion can only be sensed by the tank, the explosion equivalent obtained by the injury sensing calculation part of the tank model triggers the damaged explosion model 425 to operate, and the explosion equivalent is used as an input, and the information of the explosion equivalent and the tank fragments is calculated by the damaged explosion model 425.
(c) Can body residue
When the storage tank explodes, the residual part of the storage tank becomes a liquid pool, and the liquid pool can be set to trigger a pool fire, so that the related data of the liquid pool is connected with the related data of another pool fire model (a residual pool fire model 426 in the figure).
Taking the example of the liquid pool initiating the pool fire, the damage sensing of the storage tank can be described as the following process:
1) the flange of the storage tank leaks, and the leaked liquid forms a cofferdam-free liquid pool.
2) As the amount of leakage increases, the pool area gradually expands. Wherein, the thickness of the liquid pool can be determined according to the physical properties of the materials in the pool, and then the area of the liquid pool is obtained.
3) If the material in the liquid pool is combustible and the temperature is above the ignition point, pool fire is formed, and the area, the flame height and the flame temperature of the pool fire are determined according to the physical properties of the pool fire.
4) And determining the distribution of the temperature field around the pool fire according to the area of the pool fire, the height of the flame of the pool fire and the temperature of the flame.
5) The distance of the different devices from the pool fire is determined. Specifically, according to the heat transfer calculation correlation formula, the calculation formula of the radiation intensity of the equipment at a certain distance from the flame of the pool fire is obtained as follows:
Figure BDA0002546224060000151
in the formula, AfRepresenting the radiation source surface area/flame surface areaWherein the radiation source refers to the flame center of the pool fire; a. thexRepresents the area through which all radiation energy passes at a distance x from the radiation source; exRepresenting the intensity of radiation at a distance x from the radiation source, in W/m2(ii) a E is the radiation intensity of the flame surface, with the unit of W/m 2; epsilon is the flame radiation emissivity; delta is Stefin-Boltzmann constant, 1.380649 x 10-23J/K；TfIs the flame temperature in K.
The radiation energy Q absorbed by the radiation-absorbing device over a given surface area can be calculated using equation (1) abovex,aComprises the following steps:
Qx，a＝FExAa (2)
in the formula, AaDenotes a certain surface area of the irradiated object, in m2(ii) a F is an angular coefficient.
It can be seen from above formula (2) that for the same temperature field, each equipment can calculate different absorbed heat according to the difference of the self-received radiation area and the angle coefficient, and the different absorbed heat inevitably makes the damage that each equipment receives different again to the different damage condition of disaster field to equipment has accurately been reflected.
The five different accident states have different triggering mechanisms, and the 'tank bottom leakage' and 'tank top leakage' accidents of the storage tank are triggered by an operation accident model of an operator, while the other three accidents are triggered by the damage perception of each device to a disaster field.
Therefore, through the scheme of the embodiment of the invention, the risk equipment model established by the embodiment of the invention can well demonstrate the occurrence and development process of the accident domino of the storage tank, and compared with the original scheme which only can simulate equipment and accidents, the scheme increases the simulation of a disaster field and perfects the simulation elements of the storage tank.
The embodiment of the invention also provides a storage medium, wherein a program is stored on the storage medium, and when the program is executed by a processor, the emergency treatment simulation risk equipment modeling method is realized.
The embodiment of the invention provides a processor, which is used for running a program, wherein the emergency treatment simulation risk equipment modeling method is executed when the program runs.
The embodiment of the invention provides a computing device, which comprises a processor, a memory and a program stored on the memory and capable of running on the processor, wherein the steps of the emergency treatment simulation risk device modeling method are realized when the processor executes the program. In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The computing device herein may be a server, PC, PAD, cell phone, etc.
Embodiments of the present invention also provide a computer program product adapted to perform a program of initializing method steps of the method for modeling an emergency treatment simulation risk device as described above, when executed on a data processing device.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present invention and are not intended to limit the scope of the present invention. Various modifications and alterations to the embodiments of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention should be included in the scope of claims of the embodiments of the present invention.

Claims (15)

1. An emergency disposition simulation risk equipment modeling method, characterized by comprising:
acquiring process data of equipment, wherein the process data is used for describing the operation condition of materials involved in a dynamic process in the equipment;
acquiring accident data of the equipment, wherein the accident data is used for describing the change condition of first process data after the equipment has an accident;
acquiring disaster field data of the equipment, wherein the disaster field data is used for describing a second process data change condition of the equipment in a disaster field; and
constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data;
when an accident phenomenon is caused by the ideal equipment model, constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model; and
combining the ideal equipment model and the incident model to form a risk equipment model.
2. The emergency treatment simulation risk equipment modeling method of claim 1, wherein the process data comprises any one or more of the following data in the equipment: temperature, pressure, flow, liquid level and material information; and/or
The accident data comprises process data corresponding to the equipment in any one or more of the following accident states: fire, explosion, leakage, plugging, lightning failure, material failure, strength failure, and structural failure.
3. The modeling method of emergency treatment simulation risk equipment according to claim 1, wherein the disaster scenario data includes disaster scenario type, disaster-related geographic information, and disaster scenario variation, and the obtaining disaster scenario data of the equipment comprises:
determining a disaster field type according to the accident type, wherein the disaster field type comprises a temperature field corresponding to the fire accident, an energy field corresponding to the explosion accident and a toxic gas field corresponding to the toxic gas accident;
acquiring disaster-related geographic information through a Geographic Information System (GIS), wherein the disaster-related geographic information comprises equipment position information, equipment geometric dimensions and topographic and geomorphic information of an accident occurrence place; and
and (3) performing simulation calculation on the disaster scene by adopting a Computational Fluid Dynamics (CFD) simulation technology to obtain the change condition of the disaster field.
4. The modeling method of emergency treatment simulation risk equipment according to claim 3, wherein the performing simulation calculation of a disaster scenario using Computational Fluid Dynamics (CFD) simulation technique comprises:
the method comprises the steps of carrying out grid division on a disaster scene, calculating the disaster scene by adopting a CFD simulation technology according to each grid, and simplifying a calculation result based on a preset calculation efficiency requirement so as to obtain a calculation result finally showing real-time change conditions of the disaster scene.
5. The emergency treatment simulation risk device modeling method of claim 1, further comprising:
and acquiring environmental data of the equipment, and configuring the environmental data in the ideal equipment model.
6. The emergency treatment simulation risk device modeling method of claim 1, further comprising:
and acquiring a simulation result of the risk equipment model responding to the current disaster field data to carry out disaster simulation, and determining the damage condition of the current disaster field to the equipment based on the simulation result, wherein the damage condition comprises a damage type, a damage area and a damage degree.
7. The emergency treatment simulation risk device modeling method of claim 1, further comprising:
establishing a rescue model of the equipment based on corresponding rescue basic data of the equipment, wherein the rescue model is associated with the risk equipment model; and
and triggering the rescue model to carry out simulation so as to obtain corresponding rescue data, and updating the disaster field data based on the rescue data.
8. An emergency treatment simulation risk equipment modeling apparatus, comprising:
the device comprises a process data acquisition module, a data processing module and a data processing module, wherein the process data acquisition module is used for acquiring process data of equipment, and the process data is used for describing the running condition of materials involved in a dynamic process in the equipment;
the accident data acquisition module is used for acquiring accident data of the equipment, wherein the accident data is used for describing the change condition of first process data after the equipment is in an accident;
the disaster field data acquisition module is used for acquiring disaster field data of the equipment, wherein the disaster field data is used for describing the second process data change condition of the equipment in a disaster field;
the first modeling module is used for constructing an ideal equipment model for describing the technological process, accident phenomenon and disaster field perception of corresponding equipment based on the acquired technological data, accident data and disaster field data;
the second modeling module is used for constructing an accident model for simulating the accident phenomenon caused by the ideal equipment model when the accident phenomenon is caused by the ideal equipment model; and
a third modeling module to combine the ideal equipment model and the incident model to form a risk equipment model.
9. The emergency treatment simulation risk equipment modeling apparatus of claim 8, wherein the process data comprises any one or more of the following data in the equipment: temperature, pressure, flow, liquid level and material information; and/or
The accident data comprises process data corresponding to the equipment in any one or more of the following accident states: fire, explosion, leakage, plugging, lightning failure, material failure, strength failure, and structural failure.
10. The modeling apparatus for emergency treatment simulation risk equipment according to claim 8, wherein the disaster field data includes disaster field type, disaster-related geographic information and disaster field variation, and the disaster field data obtaining module is configured to obtain the disaster field data of the equipment including:
determining a disaster field type according to the accident type, wherein the disaster field type comprises a temperature field corresponding to the fire accident, an energy field corresponding to the explosion accident and a toxic gas field corresponding to the toxic gas accident;
acquiring disaster-related geographic information through a Geographic Information System (GIS), wherein the disaster-related geographic information comprises equipment position information, equipment geometric dimensions and topographic and geomorphic information of an accident occurrence place; and
and (3) performing simulation calculation on the disaster scene by adopting a Computational Fluid Dynamics (CFD) simulation technology to obtain the change condition of the disaster field.
11. The modeling apparatus for emergency treatment simulation risk equipment according to claim 10, wherein the performing simulation calculation of disaster scenario using computational fluid dynamics CFD simulation technique comprises:
the method comprises the steps of carrying out grid division on a disaster scene, calculating the disaster scene by adopting a CFD simulation technology according to each grid, and simplifying a calculation result based on a preset calculation efficiency requirement so as to obtain a calculation result finally showing real-time change conditions of the disaster scene.
12. The emergency treatment simulation risk equipment modeling apparatus of claim 10, further comprising:
and the environment data acquisition module is used for acquiring the environment data of the equipment and configuring the environment data in the ideal equipment model.
13. The emergency treatment simulation risk equipment modeling apparatus of claim 8, further comprising:
and the damage determining module is used for acquiring a simulation result of the risk equipment model responding to the current disaster field data to carry out disaster simulation, and determining the damage condition of the current disaster field to the equipment based on the simulation result, wherein the damage condition comprises a damage type, a damage area and a damage degree.
14. The emergency treatment simulation risk equipment modeling apparatus of claim 8, further comprising:
a rescue modeling module for establishing a rescue model of the device based on corresponding rescue basic data of the device, wherein the rescue model is associated with the risk device model; and
and the data updating module is used for triggering the rescue model to carry out simulation so as to obtain corresponding rescue data, and updating the disaster field data based on the rescue data.
15. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the emergency treatment simulation risk device modeling method of any of claims 1-7.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113821993A (en) * 2020-06-18 2021-12-21 中国石油化工股份有限公司 Method and device for sensing damage of equipment and storage medium
CN113821988A (en) * 2020-06-18 2021-12-21 中国石油化工股份有限公司 Emergency disposal simulation ideal equipment modeling method and device and storage medium
CN114840584A (en) * 2022-07-06 2022-08-02 中国矿业大学(北京) Method and system for monitoring accident disaster information in real time and reconstructing area

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005327214A (en) * 2004-05-17 2005-11-24 Mitsui Sumitomo Insurance Co Ltd Disaster occurrence frequency estimation device, method, software and recording medium, and disaster event occurrence frequency estimation system
CN103927410A (en) * 2014-03-26 2014-07-16 中国石油化工股份有限公司 System and method for dynamically deducing and simulating emergency plans for chemical accidents
CN104317848A (en) * 2014-10-14 2015-01-28 上海市安全生产科学研究所 GIS (Geographic Information System) overlay analysis-based domino accident influence probability analysis method
CN105787677A (en) * 2016-03-31 2016-07-20 交通运输部水运科学研究所 Petrochemical port area accident risk area quantitative assessment method
CN106021687A (en) * 2016-05-13 2016-10-12 中国石油大学(华东) Planar arrangement method for marine modular LNG receiving terminal
CN106710356A (en) * 2017-03-22 2017-05-24 交通运输部水运科学研究所 Oil spill accident simulation training simulation method
CN108171413A (en) * 2017-12-26 2018-06-15 杭州电子科技大学 A kind of chemical industrial park emergency resources method for optimizing configuration
CN109543919A (en) * 2018-12-03 2019-03-29 公安部天津消防研究所 A kind of fire-fighting dynamic Decision System of Emergency and its implementation to be developed based on accident
CN110008618A (en) * 2019-04-15 2019-07-12 华夏天信（北京）智能低碳技术研究院有限公司 A kind of emergency aided decision system based on GIS and BIM
KR20200043718A (en) * 2018-10-18 2020-04-28 주식회사 열린기술 Risk evaluation system of plant operators using radiant heat of fire model

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005327214A (en) * 2004-05-17 2005-11-24 Mitsui Sumitomo Insurance Co Ltd Disaster occurrence frequency estimation device, method, software and recording medium, and disaster event occurrence frequency estimation system
CN103927410A (en) * 2014-03-26 2014-07-16 中国石油化工股份有限公司 System and method for dynamically deducing and simulating emergency plans for chemical accidents
CN104317848A (en) * 2014-10-14 2015-01-28 上海市安全生产科学研究所 GIS (Geographic Information System) overlay analysis-based domino accident influence probability analysis method
CN105787677A (en) * 2016-03-31 2016-07-20 交通运输部水运科学研究所 Petrochemical port area accident risk area quantitative assessment method
CN106021687A (en) * 2016-05-13 2016-10-12 中国石油大学(华东) Planar arrangement method for marine modular LNG receiving terminal
CN106710356A (en) * 2017-03-22 2017-05-24 交通运输部水运科学研究所 Oil spill accident simulation training simulation method
CN108171413A (en) * 2017-12-26 2018-06-15 杭州电子科技大学 A kind of chemical industrial park emergency resources method for optimizing configuration
KR20200043718A (en) * 2018-10-18 2020-04-28 주식회사 열린기술 Risk evaluation system of plant operators using radiant heat of fire model
CN109543919A (en) * 2018-12-03 2019-03-29 公安部天津消防研究所 A kind of fire-fighting dynamic Decision System of Emergency and its implementation to be developed based on accident
CN110008618A (en) * 2019-04-15 2019-07-12 华夏天信（北京）智能低碳技术研究院有限公司 A kind of emergency aided decision system based on GIS and BIM

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
AHMED MEBARKI ET AL.: "Explosions and structural fragments as industrial hazard: domino effect and risks", 2012 INTERNATIONAL SYMPOSIUM ON SAFETY SCIENCE AND TECHNOLOGY, 26 October 2012 (2012-10-26) *
易涛: "化工灾害应急演练与控制关键技术研究", 中国博士论文电子期刊, no. 08, 15 August 2015 (2015-08-15) *
殷志明;张红生;周建良;李迅科;: "深水钻井井喷事故情景构建及应急能力评估", 石油钻采工艺, no. 01, 20 January 2015 (2015-01-20) *
褚家成;徐连胜;蒋平昌;俞维纫;胡燕飞;: "港口石油化工码头及其库区灾害事故应急系统研究", 中国安全科学学报, no. 01, 30 January 2007 (2007-01-30) *
许祺等: "石油罐区应急操作仿真系统设计", 化工自动化及仪表, vol. 47, no. 06, 20 November 2020 (2020-11-20) *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113821993A (en) * 2020-06-18 2021-12-21 中国石油化工股份有限公司 Method and device for sensing damage of equipment and storage medium
CN113821988A (en) * 2020-06-18 2021-12-21 中国石油化工股份有限公司 Emergency disposal simulation ideal equipment modeling method and device and storage medium
CN114840584A (en) * 2022-07-06 2022-08-02 中国矿业大学(北京) Method and system for monitoring accident disaster information in real time and reconstructing area

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