A comprehensive dynamic analysis system and method for leakage risk of a petrochemical enterprise

Abstract

The application provides a petrochemical enterprise leakage risk comprehensive dynamic analysis system and method, the system comprises: a data collection and processing module, an input file preparation module, a leakage diffusion operation module and a three-dimensional visualization output module; by obtaining and processing operation parameters related to leakage diffusion operation from different data sources, preparing diversified model input files based on the operation parameters, the leakage diffusion operation module uses the data interface to call the input files to realize dynamic operation of the diffusion concentration of different receptor layers in the leakage scene, forming a three-dimensional concentration field; then superimposed with the three-dimensional scene of the production site, the three-dimensional concentration field distribution and risk situation of the pollutants in the three-dimensional space of the plant area are analyzed and visualized; the scheme can overcome the problem that the prior art lacks support for mixed leakage gas and three-dimensional factors, realize dynamic simulation operation of the three-dimensional leakage scene gas diffusion concentration, and has high operation efficiency and good scene applicability.

Description

Technical Field

[0001] This invention relates to the field of petrochemical risk analysis technology, and in particular to a comprehensive dynamic analysis system and method for leakage risk in petrochemical enterprises. Background Technology

[0002] Hazardous chemical leaks are characterized by their suddenness, rapid spread of toxic gases, and wide range of hazards. Once a gas leak occurs in a petrochemical plant or pipeline, the toxic and harmful gases will move rapidly and be widely distributed under the influence of terrain and weather conditions, forming a large-scale hazard area in a short period of time, affecting the personal safety of production personnel and residents in the surrounding area.

[0003] By comprehensively assessing the leakage and diffusion distribution of hazardous substances, rapid estimation and real-time early warning of leakage risks can be achieved, which has significant technical guiding significance for leakage risk monitoring and early warning. Common computational analysis models, such as SLAB and ALOHA, can achieve rapid calculations, but they all assume flat terrain and do not consider complex terrain with undulating topography. For example, patent document CN104750949B provides a method for quantitative assessment and characterization of individual risk of gas leakage poisoning. Based on a constructed set of leakage scenarios, it uses CFD software to simulate the leakage scenarios realistically, establishes a CFD model of toxic gas leakage, and records the real-time concentration field of gas leakage diffusion at each location in different leakage scenarios. By determining the probability of death of people within the affected area in the poisoning accident scenario caused by the leakage accident, the individual risk of people within the affected area is determined, and a quantitative analysis of cumulative individual risk is performed. Combining the cumulative individual risk values ​​corresponding to each location point in each scenario, a risk cloud map is drawn for the accumulated individual risk, intuitively expressing the magnitude and distribution of individual risk values. This method utilizes CFD software to realistically simulate leak scenarios, but it is time-consuming and suitable for preventing personnel poisoning accidents, optimizing the placement of gas detectors, and optimizing the layout of factory facilities. However, it is not suitable for rapid early warning of leaks in petrochemical enterprises. Patent document CN108932394B provides a method for determining the hazard range of a toxic gas leak. Based on a Gaussian model, it proposes a method for determining the hazard range of a toxic gas leak, including acquiring environmental data of the toxic gas leak source; determining the diffusion type based on the gas leak type; calculating the toxic gas concentration at a determined point based on the diffusion type; determining the toxic gas diffusion boundary point in the coordinate system of the environmental data based on the toxic gas concentration; combining the environmental data and the toxic gas diffusion boundary point to obtain the toxic gas diffusion area and converting it to a latitude and longitude coordinate system. Simulations of toxic gas diffusion are implemented based on Gaussian plume and Gaussian cloud models to predict the hazard range caused by diffusion. In real-world scenarios, wind direction often changes with time and space, causing pollutants to be distributed along curves rather than a straight line. Furthermore, the calculated results represent the concentration distribution from the plume's diffusion to a steady state. Therefore, this method cannot calculate the pollutant concentration distribution at any given time. It also has inherent limitations in simulating air pollution diffusion under complex wind fields (such as sea breezes, valley breezes, etc.), leading to significant deviations between simulation results and actual conditions under complex near-surface wind fields. Additionally, while some commercial software, such as Fluent, can handle toxic gas diffusion well and be used for risk calculation and analysis, the numerical simulation process is too time-consuming, failing to meet the real-time requirements of leakage risk calculation.

[0004] On the other hand, considering actual hazardous chemical leak scenarios, since the leaked gases from petrochemical enterprises are mostly mixed gases, and the equipment and facilities are arranged in a multi-layered three-dimensional layout, existing research has not provided methods for calculating material parameters for mixed gas leaks. There is a lack of in-depth research on the parameter settings of gas diffusion models for three-dimensional leak scenario examples. The calculation results lack the spatiotemporal structure support required for simulating the impact range of multi-layered three-dimensional petrochemical equipment and facilities. The overall analysis results cannot meet the requirements for dynamic calculation of the three-dimensional concentration field of leaked substances and comprehensive risk assessment in petrochemical enterprise leak scenarios.

[0005] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a comprehensive dynamic risk assessment system for petrochemical enterprises. This system offers a method for obtaining material parameters of mixed gas leaks in petrochemical enterprises, overcoming the problems of large deviations in existing simulation results and lack of support for mixed leaked gases and three-dimensional factors. It achieves dynamic simulation calculations of gas diffusion concentrations in three-dimensional leak scenarios, and the simulation calculations are no longer limited to pure substances, effectively improving the model's adaptability and practicality, and demonstrating good scenario applicability. The system acquires and processes calculation parameters related to leak diffusion calculations from different data sources, including pollution leak parameters, meteorological monitoring data, leak location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data, and terrain file data. The leak diffusion calculation module uses a data interface to call the calculation parameters to dynamically calculate the diffusion concentration of different receptor layers in the leak scenario, forming a three-dimensional concentration field. This field is then overlaid with the three-dimensional scene of the production site to analyze the three-dimensional concentration field distribution of pollutants within the plant area. Based on the principle of classifying the degree of harm of toxic and harmful gases to on-site personnel, the affected area is risk-classified and dynamically displayed using a multi-color risk level map. Preferably, in one embodiment, the system includes: a data collection and processing module, an input file preparation module, a leakage diffusion calculation module, and a three-dimensional visualization output module;

[0007] The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0008] The input file preparation module is configured to prepare multiple input files for the leakage diffusion calculation model based on the collected and preprocessed data;

[0009] The leakage diffusion calculation module is configured to call the input file corresponding to the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0010] The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site, calculates the distribution of pollutants in the 3D concentration field of the factory area, and displays it in the 3D engine.

[0011] Furthermore, in one embodiment, the system further includes:

[0012] The leakage hazard risk analysis module is configured to consider the degree of harm that toxic and harmful gases may cause to the human body, and to classify and output the degree of harm of pollutants at different concentrations based on the set hazard level indicators.

[0013] In an optional embodiment, the data collection and processing module includes:

[0014] The data collection submodule is configured to directly collect pollution leakage parameters, meteorological monitoring data, and leakage location data through an interactive interface.

[0015] The data preprocessing submodule is configured to determine leakage-related data based on the location of the leak point, acquire meteorological monitoring data, acquire path information of DEM and LULC files, and store them in the database of the data collection and processing module.

[0016] Preferably, in one embodiment, the data preprocessing submodule further includes a data verification unit, which is configured to verify the integrity of meteorological data, determine whether the numerical range is normal, and check and determine the type and resolution of terrain data.

[0017] Furthermore, in one embodiment, the data preprocessing submodule further includes a geographic parameter conversion unit configured to convert the leak-related map data into UTM 6° projected coordinates using Gaussian forward and inverse calculations.

[0018] Optionally, in one embodiment, the input file preparation submodule includes a geographic data file preparation unit, which is used to determine the extent of the diffusion impact area and grid settings based on the location of the leak point, configure projection, grid resolution, and land use code parameters, and sequentially call the three preprocessors TERREL, CTGPROC, and MAKEGEO to generate the input geographic data for the leak diffusion calculation module.

[0019] In one embodiment, the input file preparation submodule includes a meteorological data file preparation unit, which extracts real-time wind speed and direction data based on meteorological observation data to generate an upper-air meteorological data file; and combines the cloud cover and cloud base height values ​​determined based on the meteorological observation data to generate a ground meteorological data file.

[0020] In a preferred embodiment, the leakage diffusion calculation model adopts the CALPUFF diffusion calculation model. For leakage scenarios of multi-layered three-dimensional petrochemical facilities, based on CALPUFF as the original calculation model, three-dimensional calculation parameters are set in the model according to the diffusion degree in the z-axis direction, and the calculation process is improved by combining pollution leakage parameters to carry out gas concentration calculation of multiple receptor layers, so as to obtain the layer-by-layer diffusion model results, and then merge them to generate overall three-dimensional concentration field time series data. The CALPUFF diffusion calculation model includes the meteorological calculation module CALMET, the diffusion calculation module CALPUFF, and the data post-processing module CALPOST.

[0021] Furthermore, in one embodiment, the meteorological calculation module CALMET generates a meteorological field corresponding to the leakage parameters based on the input geographic data, upper-air meteorological input file, and surface meteorological input file.

[0022] In an optional embodiment, the diffusion calculation module is configured to update the receptor layer parameters based on the meteorological field generated by the meteorological calculation module and the pollution leakage parameters, and to perform cyclic simulation calculations of the transport, transformation and removal processes of pollutants under meteorological conditions that change with time and space, so as to obtain the leakage diffusion concentration and dry and wet deposition flux at different receptor points and generate a gridded three-dimensional concentration field.

[0023] In one embodiment, the data post-processing module is configured to organize the generated three-dimensional concentration data into a formatted file so that it can be called by a web server.

[0024] Furthermore, in one embodiment, the number of receptor layers N is determined according to the following logic:

[0025]

[0026] in,

[0027]

[0028] In the formula, SLH max SLH min These represent the highest and lowest layer heights in the diffusion calculation along the z-axis, respectively. RD is the relative density of the leaking gas, and H... leak h is the height of the leak point from the ground. i The height of device i is determined by the downwind direction from the location of the leak.

[0029] In one optional embodiment, the pollution leakage parameters include not only the name, type, and molecular weight of the leaked substance, but also dry deposition, wet deposition, and chemical conversion parameters;

[0030] For a single target gas or a target gas mixture for which no parameters are recorded, the parameters of the target gas are calculated based on the parameters of a stable set gas, according to the following logic:

[0031]

[0032] in, To set the various parameters of gaseous CO, p k Let k be the parameter of the leaked gas. m is the quantity of the leaked gaseous component, M0 is the relative molecular weight of CO, and M j v j % represents the relative molecular weight and volume percentage of the j-th component in the leaked substance.

[0033] Furthermore, in one embodiment, the diffusion calculation module calculates the concentration contribution of a single smoke plume at a receptor point using the following formula:

[0034]

[0035]

[0036] In the formula, C represents the ground-level pollutant concentration at the receiver point; Q represents the mass of the pollutant in the plume; σ x σ y σ z d represents the standard deviation of the Gaussian distribution of pollutants in the X, Y, and Z directions, respectively; a d represents the distance from the center of the smoke plume to the receptor point in the X direction; c The distance from the center of the smoke plume to the receptor point in the Y direction is represented by g; g represents the vertical term of the Gaussian equation, characterizing multiple reflections between the mixing layer and the ground; H e represents the effective height of the smoke cloud center above the ground; h represents the height of the mixing layer.

[0037] Optionally, in one embodiment, the diffusion calculation module discretizes time by setting multiple time points, uses gas concentration information as attribute information, location information as spatial features, and time interval as temporal features, and combines attribute information and spatiotemporal features to form a spatiotemporal snapshot to describe the spatial state and diffusion distribution characteristics of geographic objects at different times.

[0038] In one embodiment, the leakage hazard risk analysis module classifies the degree of harm caused by different concentrations of pollutants according to the following logic:

[0039]

[0040] Here, HalHD represents the level of harm caused by the pollutant, C represents the concentration of the pollutant during diffusion, PC-STEL represents the short-term exposure allowable concentration, MAC represents the maximum allowable concentration, and LC0 represents the minimum lethal concentration.

[0041] Based on other aspects of the system described in any one or more of the above embodiments, the present invention also provides a comprehensive dynamic analysis method for leakage risks in petrochemical enterprises, which is applied to the system described in any one or more of the above embodiments.

[0042] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0043] This invention provides a comprehensive dynamic analysis system and method for leakage risk in petrochemical enterprises. The system acquires and processes computational parameters related to leakage diffusion calculations from different data sources, including pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data, and terrain file data. This invention not only considers pollution leakage parameters and leakage location information but also the spatiotemporal resolution requirements of the model for leakage scenario examples. It comprehensively considers the three-dimensional structural factors of the leakage scenario and meteorological data from different layers to provide input files for leakage diffusion calculations, providing a reliable foundation for obtaining three-dimensional diffusion concentration field data.

[0044] The leakage diffusion calculation module uses a data interface to call calculation parameters to realize the dynamic calculation of diffusion concentration in different receptor layers of the leakage scenario, forming a three-dimensional concentration field. Based on the set leakage diffusion calculation model, the present invention sets three-dimensional calculation parameters, improves the calculation process to carry out multi-layer calculation of gas concentration, obtains the layer-by-layer diffusion model results, integrates and generates a three-dimensional concentration field, and can take into account the influence of gas diffusion on dry and wet deposition and chemical conversion of the gas, ensuring calculation efficiency while realizing dynamic diffusion concentration analysis of leaked gas.

[0045] Furthermore, by overlaying the three-dimensional concentration field with the three-dimensional scene of the production site, the distribution of pollutants in the three-dimensional space of the plant area is analyzed and displayed. By overlaying the display with the three-dimensional structure of the enterprise's production site, users can more intuitively understand the three-dimensional distribution of diffusion data in the space of the leakage device, which is convenient for efficient recording and application in decision-making.

[0046] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0048] Figure 1 This is a schematic diagram of the three-dimensional diffusion structure of the comprehensive dynamic analysis system for leakage risk in petrochemical enterprises provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of the diffusion simulation data retrieval process of the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in this embodiment of the invention;

[0050] Figure 3 This is a schematic diagram of the three-dimensional concentration field calculation route based on CALPUFF for the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of the diffusion model interface setting principle of the leakage diffusion calculation module in the comprehensive dynamic analysis system for leakage risk in petrochemical enterprises provided by another embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the structure of the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in another embodiment of the present invention;

[0053] Figure 6 This is a schematic diagram of the system structure layout of the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in this embodiment of the invention. Detailed Implementation

[0054] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples. Those skilled in the art will then fully understand how the present invention uses technical means to solve technical problems and achieve technical effects, and will be able to implement the present invention specifically based on the above-described implementation process. It should be noted that, as long as there is no conflict, the various embodiments and features of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0055] Although the flowchart describes the operations as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. The order of the operations can be rearranged. A process can terminate when its operation is complete, but it may also have additional steps not included in the diagram. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0056] Computer equipment includes user equipment and network equipment. User equipment or clients include, but are not limited to, computers, smartphones, and PDAs (Personal Digital Assistants); network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Computer equipment can operate independently to implement this invention, or it can connect to a network and implement this invention through interaction with other computer devices within the network. The network in which the computer equipment resides includes, but is not limited to, the Internet, wide area networks (WANs), metropolitan area networks (MANs), local area networks (LANs), and VPN networks.

[0057] The terms “first,” “second,” etc., may be used herein to describe various units, but these units should not be limited by these terms; they are used merely to distinguish one unit from another. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items. When a unit is referred to as “connected” or “coupled” to another unit, it may be directly connected or coupled to said other unit, or there may be intermediate units present.

[0058] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0059] Hazardous chemical leaks are characterized by their suddenness, rapid spread of toxic gases, and wide-ranging hazards. Once a gas leak occurs in a petrochemical plant or pipeline, toxic and harmful gases will move rapidly and distribute widely under the influence of terrain and weather conditions, forming a large-scale hazard area within a short period of time, affecting the personal safety of surrounding production personnel and residents. Comprehensive assessment of the leakage and diffusion distribution of hazardous substances is crucial for rapid risk estimation and real-time early warning, providing significant technical guidance for leak risk monitoring and early warning.

[0060] Common computational analysis models, such as SLAB and ALOHA, while enabling rapid calculations, all assume flat terrain and fail to consider complex terrain with undulating features. For example, patent document CN104750949B provides a method for quantitative assessment and characterization of individual risk in gas leak poisoning. Based on a constructed set of leak scenarios, it uses CFD software to realistically simulate these scenarios, establishing a CFD model of toxic gas leaks and recording the real-time concentration field of gas leakage diffusion at various locations in different leak scenarios. By determining the probability of death of personnel within the affected area in a poisoning accident scenario caused by a leak, it determines the individual risk of personnel within the affected area and performs a quantitative analysis of cumulative individual risk. Combining the cumulative individual risk values ​​corresponding to each location point in each scenario, it plots a risk cloud map of the accumulated individual risk, visually representing the magnitude and distribution of individual risk values. This method utilizes CFD software for realistic leak simulation, which is time-consuming. It is suitable for the prevention of personnel poisoning accidents, optimization of gas detector placement, and optimization of factory facility layout, but not for rapid early warning of leak scenarios in petrochemical enterprises. Patent document CN108932394B provides a method for determining the hazard range of a toxic gas leak. Based on a Gaussian model, this method includes acquiring environmental data of the toxic gas leak source; determining the diffusion type based on the gas leak type; calculating the toxic gas concentration at a determined point based on the diffusion type; determining the toxic gas diffusion boundary point in the coordinate system of the environmental data based on the toxic gas concentration; and combining the environmental data and the toxic gas diffusion boundary point to obtain the toxic gas diffusion area and converting it to a latitude and longitude coordinate system. The method simulates toxic gas diffusion based on Gaussian plume and Gaussian cloud models to predict the hazard range caused by diffusion. However, in real-world scenarios, wind direction often changes with time and space, causing pollutants to be distributed along curves rather than a straight line. Furthermore, the calculated result represents the concentration distribution from plume diffusion to a steady state. Therefore, this method cannot calculate the pollutant concentration distribution at any given time and has inherent limitations in simulating air pollution diffusion under complex wind fields (such as sea breezes, valley breezes, etc.), leading to significant deviations between the simulation results and actual conditions under complex near-surface wind fields.

[0061] While some commercial software, such as Fluent, can handle the diffusion of toxic gases and be used for risk calculation and analysis well, the numerical simulation process is too time-consuming and cannot meet the real-time requirements of leakage risk calculation.

[0062] CALPUFF is a multi-layered, non-steady-state, multi-species Gaussian plume diffusion model that fully considers the influence of meteorological, topographical, and ground conditions. It can predict changes in the physicochemical properties of pollutants, including emissions, advection transport, diffusion, and wet / dry deposition. It can also handle continuous or indirect emission sources and effectively track the spatial and temporal variations of a specified point with respect to the airflow field, making it suitable for atmospheric diffusion studies at different regional scales. In practical applications, although the CALPUFF model itself provides a three-dimensional concentration field in the x, y, and z directions, according to atmospheric environmental guidelines, sampling grids in common environmental assessments and air pollution studies are usually fixed at the ground surface. Based on existing research, calculations using the CALPUFF model can only obtain concentration values ​​at various points on the ground, generating a two-dimensional ground-level gas diffusion concentration field.

[0063] In practical hazardous chemical leak scenarios, given the multi-layered, three-dimensional layout of petrochemical plants and facilities, and the rapid expansion of toxic and harmful gases in three-dimensional space, existing research applying gas diffusion models to leak risk calculations mostly adopts an environmental assessment approach. This approach fails to highlight the high requirements of leak scenario examples for model spatiotemporal resolution and computational speed, and lacks in-depth research on the parameter settings of gas diffusion models for leak scenario examples. Consequently, the calculation results lack the spatiotemporal structure support required for simulating the impact range of multi-layered, three-dimensional petrochemical plants and facilities. Overall, the analysis results cannot meet the requirements for dynamic calculation of the three-dimensional concentration field of leaked substances and comprehensive risk assessment in petrochemical enterprise leak scenarios.

[0064] To overcome the above shortcomings, this invention provides a comprehensive dynamic analysis system and method for leakage risks in petrochemical enterprises. Researchers working on this solution overcome technical obstacles to achieve high-quality and stable hazardous chemical leakage detection and analysis by focusing on the following different aspects:

[0065] 1. For leakage scenarios of petrochemical plants and facilities with multi-layer three-dimensional layout, CALPUFF is selected as the original calculation model. By setting three-dimensional calculation parameters in the model based on the diffusion degree in the z-axis direction, the calculation process is improved to carry out multi-layer calculation of gas concentration, obtain the layer-by-layer diffusion model results, and finally integrate them to generate a three-dimensional concentration field.

[0066] 2. The diffusion of different substances in gases is affected by their dry and wet deposition and chemical conversion. Therefore, in addition to setting calculation parameters such as the name, molecular weight, and type of the leaked substance, parameters such as dry deposition, wet deposition, and chemical conversion are also required. Leaked gases from petrochemical plants are mostly mixed gases, and their gas parameters are not found in existing standard gas parameter tables, requiring dynamic calculation to obtain them.

[0067] 3. Based on the characteristics of three-dimensional concentration field data, time is treated as an attribute of spatial geographic objects, and time is discretized and absolutized, and embedded into the spatial database of the system of this invention in the form of timestamps to describe the spatial state and characteristics of geographic objects at different times.

[0068] 4. Based on the three-dimensional concentration field analysis, the distribution and coverage of toxic and harmful gases are analyzed, a consequence calculation model is constructed, the degree of harm is classified, and the harm area is divided according to the degree of harm to achieve real-time early warning.

[0069] 5. Based on the above technologies, a rapid calculation system for gas leakage consequences is constructed to realize dynamic simulation calculation and risk warning of gas leakage risk in a three-dimensional concentration field, and to support playback of diffusion process and visualization query of leakage consequence level at any time.

[0070] The structural components, connection methods, and functional principles of the system according to embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Although the logical order of each operation is shown in the description of the system's structural operation, in some cases, the operations shown or described may be performed in a different order than that shown here.

[0071] Example 1

[0072] Leaked toxic and hazardous gases diffuse in three-dimensional space. Considering the numerous influencing factors, complex composition, and large scale of variation in the diffusion of toxic and hazardous gases at hazardous chemical leak sites, this invention, based on the CALPUFF model, calculates parameters such as the z-value height of the receptor point by setting three-dimensional calculation parameters in the model for the diffusion degree along the z-axis. Calculations are performed on the ground, intermediate, and highest layers of the model to obtain layer-by-layer diffusion model results. Two-dimensional calculations are converted to three-dimensional calculations, establishing a toxic and hazardous gas leakage diffusion model based on cross-scale calculations, and finally integrating and generating a three-dimensional concentration field. The effects of dry and wet deposition and chemical conversion of various components of the leaked substance are comprehensively considered to form a dynamic calculation method for leakage substance parameters in the diffusion model. For multi-layered, three-dimensional petrochemical plants and facilities, the distribution and coverage of toxic and hazardous gases in the plant area are analyzed based on the three-dimensional concentration field, and the leakage damage level is classified. The three-dimensional concentration field and leakage consequences are visualized. Based on the constructed spatiotemporal data model, the spatial characteristic state at a certain moment can be quickly determined, facilitating the characterization and querying of the spatial state at a specific moment. It supports playback of the diffusion process and visualization query of the leakage consequence level at any time, enabling comprehensive assessment of the leakage risk situation.

[0073] In this embodiment of the invention, the dynamic calculation process of overall leakage material parameters based on the diffusion model includes the input of controllable parameters to be calculated by the user and the final display of diffusion calculation data by a three-dimensional GIS (Geographic Information System).

[0074] Figure 1This diagram illustrates the structure of the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in Embodiment 1 of the present invention. (Refer to...) Figure 1 It can be seen that the system includes: a data collection and processing module, a leakage diffusion calculation module, an input file preparation module, and a three-dimensional visualization output module;

[0075] The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0076] The input file preparation module is configured to prepare multiple input files for the leakage diffusion calculation model based on the collected and preprocessed data;

[0077] The leakage diffusion calculation module is configured to call the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0078] The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site, calculates the distribution of pollutants in the 3D concentration field of the factory area, and displays it in the 3D engine.

[0079] In practical applications, upon receiving a gas leak alarm, the petrochemical enterprise leakage risk comprehensive dynamic analysis system of this embodiment of the invention is activated, and a diffusion simulation data retrieval process is initiated. In optional embodiments, alarms can be triggered by monitoring signals from gas monitoring equipment or by manually identified and recorded alarm signals.

[0080] For the data collection and processing module, the pollution leakage parameters, meteorological monitoring data, and leakage location data are collected and obtained through the user terminal interactive interface; therefore, in an optional embodiment, the data collection and processing module includes a data collection submodule, which is configured to directly collect pollution leakage parameters, meteorological monitoring data, and leakage location data through the interactive interface.

[0081] Specifically, pollution leakage parameters, meteorological monitoring data, and leakage location data are input by the user on the user terminal interface; specifically, in an optional embodiment, the interface input parameters include: pollution leakage parameters (gas type, leakage rate, and height of the leakage point above the ground), meteorological monitoring data (wind direction, wind speed, temperature, humidity, air pressure, precipitation, cloud cover, and cloud base height), and leakage location (using the latitude and longitude of the leakage accident point).

[0082] The remaining data in the other part is preprocessed data that needs to be prepared in advance. Different preprocessed data are obtained by the data collection and processing module from the matching data source system through the corresponding data interface.

[0083] In optional embodiments, the preprocessed data files include: geographic information files, upper-air meteorological data, terrain data, three-dimensional grid elevation data, etc.

[0084] Specifically, the process involves determining three-dimensional elevation data based on terrain data, combining two-dimensional horizontal grids with vertical coordinates to construct a three-dimensional grid system, extracting the elevation value corresponding to each grid cell from the preprocessed terrain data and assigning it to the corresponding grid cell, and processing and correcting missing and abnormal data to form three-dimensional grid elevation data. The three-dimensional grid elevation data is then organized into a file format that matches the CALPUFF model.

[0085] This invention implements model data preprocessing, calculates the input data of the computational model related to pollutant emissions, and processes various types of data into a standard format to further determine the model's technical parameters, pollutant types and properties, map projection, and chemical conversion parameters, thus preparing for calculation. Among them, pollutant types refer to the types of leaked substances, such as CO, H2S, or mixed gases.

[0086] In practical applications, the data preprocessing submodule of the data collection and processing module is configured to determine leakage-related data based on the location of the leakage point, acquire path information of meteorological monitoring data, digital elevation model (DEM) data files, and land use and land cover (LULC) data files, and store them in the database of the data collection and processing module.

[0087] The data preprocessing submodule includes a leakage-related data determination unit, which is configured to determine the location of the leakage point, and based on this, determine the type of leaked pollutants and leakage point parameters, including parameters such as leakage rate and the height of the leakage point above the ground. It also determines the accident process scale data through an expanded computational model library, including the spatial range of the simulated area, grid resolution, and time span.

[0088] The data preprocessing submodule also includes a data verification unit, which is configured to check whether the meteorological data (real-time monitoring data) is complete and within the normal range, and to check and determine the type and resolution of the terrain data.

[0089] The data preprocessing submodule also includes a geographic parameter conversion unit, which is configured to convert the leak-related map data into UTM 6° projected coordinates through Gaussian forward and inverse calculations.

[0090] Furthermore, the input file preparation submodule prepares various input files for the leakage diffusion calculation model based on the collected and preprocessed data.

[0091] The input file preparation submodule includes a geographic data file preparation unit, which is used to determine the scope of the study area (the scope of the diffusion impact area) and grid settings based on the location of the leak point, configure parameters such as projection, grid resolution, and land use code, and sequentially call the three preprocessors TERREL, CTGPROC, and MAKEGEO to generate the input geographic data GEO.DAT of the CALMET submodule of the leak diffusion calculation module.

[0092] The input file preparation submodule includes a meteorological data file preparation unit, which extracts real-time wind speed and direction data from meteorological observation data to generate upper-air meteorological data files; and combines the cloud cover and cloud base height values ​​determined from the meteorological observation data to generate ground meteorological data files.

[0093] The leakage diffusion calculation module is configured to call the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0094] This invention constructs a dynamic prediction function for leakage and diffusion data by combining a leakage and diffusion calculation module with a data collection and processing module. Based on the leakage and diffusion calculation module, a leakage and diffusion calculation model library interface is constructed to flexibly retrieve various required parameters and files from the database to realize the calculation of the three-dimensional concentration field of the model.

[0095] In a preferred embodiment, different input data and parameter update data interfaces are created for the leakage diffusion calculation model, mainly including initial parameter setting interface, UTM coordinate transformation interface, geographic data production interface, parameter and result file update interface, input parameter data creation, and emission data creation interface.

[0096] The initial parameter setting interface uses InitParameter, which allows for flexible access to basic collected data. It provides interface methods for data acquisition and preprocessing for the data collection submodule and the data preprocessing submodule, enabling the acquisition of corresponding leak point parameters, determination of time span, acquisition of meteorological monitoring data, and acquisition of the paths to DEM and LULC files.

[0097] The initial parameter setting interface is also functionally connected to the integrated setting data verification unit, and can call the following functions through the interface: check whether the meteorological data (real-time monitoring data) is complete and within the normal range, check and determine the type and resolution of the terrain data, etc.

[0098] The UTM coordinate transformation interface uses UTMCoordConvert, which can be used to call functions based on geographic parameter transformation units. The thematic map for calculating leakage diffusion concentration uses the WGS-84 geodetic coordinate system, while the terrain data of CALPUFF uses the UTM 6° zone projection coordinate system (WGS-84 geodetic datum). Coordinate transformation is performed based on the two through Gaussian forward and inverse calculations.

[0099] The geographic data production interface uses MakeGeoDATA. By calling the geographic parameter conversion unit through the geographic data production interface, the study area (diffusion impact area) and grid settings are determined according to the location of the leakage point. Parameters such as projection, grid resolution, and land use code are configured. Then, the three preprocessors TERREL, CTGPROC, and MAKEGEO are called in sequence to generate the input geographic data GEO.DAT of the CALMET submodule.

[0100] Upper-air meteorological data files and surface meteorological data files need to be generated based on their respective input parameters and processing methods. Therefore, they are calculated separately based on different processes. In practical applications, upper-air meteorological file interfaces and surface meteorological file interfaces are set separately.

[0101] Specifically, the upper-air meteorological file interface uses CreateUpDATA to generate the necessary input file UP.DAT for CALMET; through the parameter and result file update interface, it retrieves and matches historical meteorological observations from the database, and extracts low-level wind speed and direction data from real-time data to generate the necessary input file for the meteorological module CALMET: upper-air meteorological data UP.DAT;

[0102] This involves selecting basic data on the leakage source from a static database and obtaining real-time meteorological data from meteorological instruments near the leakage source.

[0103] The ground meteorological file interface is set to use CreateSurfDATA; the data generation interface extracts six monitoring parameters from real-time data: wind speed, wind direction, temperature, humidity, air pressure, and relative humidity.

[0104] And the values ​​for cloud cover and cloud base height determined based on historical observations.

[0105] The necessary input file for generating CALMET is the surface meteorological data file SURF.DAT.

[0106] For the original pollutant leakage data, it is necessary to generate the corresponding emission data file in accordance with the data specifications of the CALPUFF model, including files of main processing points, and leakage source location, height of the leakage point from the ground, leakage rate, gas type, emission time series related to area source leakage. The system of the present invention provides an emission data file generation interface CreateEmissionDATA to access each emission data file to the leakage diffusion calculation module.

[0107] Based on the obtained various input files, the present invention starts the leakage diffusion calculation module and calculates the dynamic leakage diffusion concentration results, wherein the leakage diffusion calculation module adopts the CALPUFF diffusion calculation model, and the CALPUFF diffusion calculation model comprises a meteorological calculation module CALMET, a diffusion calculation module CALPUFF and a data post-processing module CALPOST; the call flow of diffusion simulation data is as shown in Figure 2 below.

[0108] The meteorological calculation module CALMET generates the meteorological field corresponding to the leakage parameters based on the input geographic data, upper-air meteorological input files and surface meteorological input files.

[0109] The diffusion calculation module is configured to, according to the meteorological field generated by the meteorological calculation module in combination with pollution leakage parameters, update receptor layer parameters to cyclically simulate and calculate the transportation, transformation and removal processes of pollutants under meteorological conditions that vary with time and space, obtain the leakage diffusion concentration and dry and wet deposition fluxes at different receptor points, and generate a gridded three-dimensional concentration field.

[0110] The diffusion of leaked substances is affected by dry-wet deposition and chemical conversion, and the set pollution leakage parameters include not only the name, type and molecular weight of the leaked substance, but also parameters of dry deposition, wet deposition and chemical conversion; in addition to the name, molecular weight and type of the leaked substance, relevant parameters such as dry deposition parameters, dry deposition parameter-particulate matter parameters and wet deposition parameters are also required for calculation of leaked substance parameters.

[0111] For mixed gas leaked from petrochemical enterprises, the parameters of the leaked gas are calculated based on various parameters of CO with stable properties that are already known;

[0112] The calculation method for the k-th parameter of the leaked gas is as follows:

[0113]

[0114] where m is the number of gas components in the leaked substance, M0 is the relative molecular weight of CO, M j , v j % are respectively the relative molecular weight and volume proportion of the j-th component in the leaked substance, and 0<k≤10. It is assumed herein that each component of the leaked substance is physically stable, chemically stable and has no chemical conversion.

[0115] In this embodiment of the invention, the meteorological module CALMET and the diffusion module CALPUFF are run sequentially to obtain the concentration results.

[0116] When running the CALPUFF submodule, the meteorological field generated by CALMET and the pollution leakage parameters input by the user are read in. The height of the receptor layer (the point where the concentration value needs to be calculated) in the control file CALPUFF.INP is modified in a loop. The concentration and dry and wet deposition flux at the receptor point in the layer are calculated and output to the CONC.DAT file. After the loop is completed, a gridded three-dimensional concentration field is obtained.

[0117] Dry and wet deposition are important factors affecting the distribution of pollutant concentrations. The CALPUFF model in this invention, by considering the dry and wet deposition process, can more accurately simulate changes in atmospheric pollutant concentrations, providing support for air quality monitoring and early warning.

[0118] Specifically, the CALMET process is first invoked for calculation. The input files include: pollutant emission data file, geographic data file GEO.DAT, surface meteorological data file SURF.DAT, upper-air meteorological data file UP.DAT, precipitation data file PRECIP.DAT, topographic weight factor data file WT.DAT, etc. Combined with the corresponding running configuration file, the CALMET result file is calculated and given.

[0119] Then, the CALPUFF process is invoked for calculation. In this program, the user specifies the gas type, leakage rate, and height of the leakage point above the ground. The above parameters and the calmet.dat file generated in the previous step are input into the CALPUFF module to calculate and generate a three-dimensional concentration field. The results are written to the conc.dat file.

[0120] In this embodiment of the invention, the CALPUFF leakage diffusion calculation module performs automatic calculations through the interface program chain entry point, and generates a three-dimensional concentration field based on the spatiotemporal model.

[0121] Most existing Calpuff simulations are designed for pure gas leaks. This invention can simulate leaks of both pure and mixed gases, solving the problem that mixed gases cannot be simulated.

[0122] The CALPUFF model used in this embodiment of the invention includes several procedures for preprocessing geographic and meteorological data. It can predict the physicochemical changes of pollutants such as emission, advection transport, diffusion, and dry and wet deposition. It can also handle continuous emission sources or indirect emission sources and track the spatial and temporal changes of a specified point with the air flow field.

[0123] In its calculation, the basic equation for the concentration contribution of a single smoke plume at a certain receptor point is:

[0124]

[0125] In the formula: C represents the ground-level pollutant concentration at the receiver point, in g / m³. 3 Q represents the mass of pollutants in the smoke plume, in grams; σ x σ y σ z Let m and d represent the standard deviations of the Gaussian distributions of pollutants in the C, Y, and Z directions, respectively. a d represents the distance from the center of the smoke plume to the receptor point in the X direction, in meters (m); c The distance from the center of the smoke cloud to the receptor point in the Y direction is represented by m; g represents the perpendicular term of the Gaussian equation, also in m; H e σ represents the effective height of the smoke cloud center above the ground, in meters; h represents the height of the mixing layer, in meters. The vertical term g explains the multiple reflections between the mixing layer and the ground. If σ z >1.6h, g will simplify to 1 / h. Generally, smoke plumes within the convective boundary layer satisfy this condition several hours after release.

[0126] By using the CALPUFF model in conjunction with meteorological, geographical, and pollution source emission data of the affected area, numerical methods can effectively simulate the transport, transformation, and removal of pollutants under meteorological conditions that vary arbitrarily in time and space, and output hourly pollutant concentration predictions.

[0127] Specifically, based on the CALPUFF model, three-dimensional calculation parameters are set for the degree of diffusion in the z-axis direction to obtain the layer-by-layer diffusion model results.

[0128] To determine the diffusion extent along the z-axis, sampling points were set at a series of air layers at a specified height above the ground. Concentration calculations were then performed at these specified layers, taking into account parameters such as gas type, leakage rate, and the height of the leakage point above the ground, to obtain the results of the layer-by-layer diffusion model.

[0129] The final result is a three-dimensional concentration field time series file, which provides basic data for technicians to analyze the leakage situation and calculate subsequent leakage risks.

[0130] Define SLH max SLH min These represent the highest and lowest layer heights in the diffusion calculation along the z-axis, respectively. RD is the relative density of the leaking gas, and H... leak Given the height of the leak point above the ground, obtain the height h of the device located downwind of the leak location. i (i>0), then:

[0131]

[0132] Given a receptor layer height deltaH, the number of receptor layers is:

[0133]

[0134] A schematic diagram of the three-dimensional concentration field calculation route based on CALPUFF in this embodiment of the invention is shown below. Figure 3 As shown.

[0135] Since a single calculation produces a single result file, and due to the time requirements of user input parameters and the need for multi-layered display in three-dimensional space, the actual calculation will update the time parameters and spatial height parameters and repeatedly call the CLAPUFF calculation module to calculate and generate more calculation result files for displaying the trend changes of diffusion over a period of time.

[0136] Furthermore, the data post-processing module is configured to organize the generated three-dimensional concentration data into a formatted requirement file.

[0137] The data post-processing module mainly calls the CALPOST calculation function to convert the data generated by the CALMET and LACPUFF modules, and inputs the generated conc.dat into the CALPOST module to organize the results into a formatted grd file.

[0138] In practical applications, the CALPUFF leakage diffusion calculation model first calls the InitParameter interface to obtain static and dynamic data for preprocessing. Then, it calls four file creation class interfaces to generate the data files and data chains (Grid, TimeSpan) required by CALPUFF. Finally, it calls the RunCALPUFF interface to calculate the results and calls the ConcToRaster class to perform result transformation, such as... Figure 4 As shown.

[0139] In an optional embodiment, folders are created layer by layer in the user-specified output path to store the time-series results of gas concentration for each layer. Within each layer's folder, text files are created sequentially at intervals of t seconds from the start of the gas leak, satisfying the requirements for structured storage of spatiotemporal data.

[0140] Based on the above calculations, in practical applications, this manifests as creating a folder named "cFieldLayer_LayerNo" with layerNo≥1 in the user-specified output path to store the gas concentration time series results for each layer.

[0141] Within each folder, text files are created sequentially at intervals of t minutes, starting from the moment the gas leak began, to achieve structured storage of spatiotemporal data. The method is as follows:

[0142] The input gridded hourly requirement files include: meteorological field file CALMET.DAT, CALPUFF control file CALPUFF.INP, CALPOST control file CALPOST.INP, receptor layer height deltaH, and the number of receptor layers N is calculated.

[0143] Calculate the receptor height n*deltaH for each layer in a loop, perform simulation calculations, and output the three-dimensional gas concentration field to folders cFieldLayer_0 to cFieldLayer_(N-1).

[0144] This invention provides a three-dimensional visualization output module that overlays and couples the generated three-dimensional concentration field with the three-dimensional scene of the enterprise's production site to calculate the distribution of pollutants in the three-dimensional space of the factory area. The visualization is then displayed in a three-dimensional engine. The three-dimensional scene of the enterprise's production site can be obtained by requesting data from the server through a data interface.

[0145] By overlaying the generated 3D concentration field onto a 3D scene of the enterprise's production site, the three-dimensional distribution of toxic and harmful gases within the plant area can be calculated. Overlaying this data with the 3D structure of the production site allows users to more intuitively understand the three-dimensional distribution of diffusion data within the leak device space, facilitating efficient recording and application in decision-making.

[0146] In practical applications, for single-layer devices, the ground concentration within the affected area is taken; for multi-layer devices, the concentration distribution within the affected area of ​​each layer must be obtained separately.

[0147] The gas 3D concentration field data, formatted after CALPOST post-processing, is visualized in a 3D engine. In an optional embodiment, a particle structure variable `ParticInst` is created in the system program to represent a particle set; each grid point in the gas diffusion model concentration field data is set as a particle, with the concentration value of each grid point serving as an attribute value. The particles move randomly within the grid. Images from different frames are displayed continuously at certain time intervals, achieving a dynamic display of the diffusion simulation. When each frame is updated, all particle instances are traversed, thereby refreshing the attributes of each particle.

[0148] We convert the calculation results into a mesh data file that can be called by the web server, thereby realizing a 3D visualization display. Considering the high time and cost of model calculation, in an optional embodiment, the accuracy display can be processed according to the calculation results, and the mesh data file can be reasonably added by applying interpolation algorithms to make the 3D interface display denser.

[0149] When implementing 3D visualization, X3D and WEBGIS are used to call files for visualization. WEBGIS directly calls and parses the transformed grid data file results, and combining this with X3D enables faster display of the result files.

[0150] In practical applications, layered color schemes can be configured based on the concentration data distribution to dynamically display the spatiotemporal distribution of concentration in each frame.

[0151] In practical applications, based on the map data conversion function of the geographic parameter conversion unit, the embodiments of the present invention can effectively combine the three-dimensional scene of the enterprise production site to realize the three-dimensional visualization of diffusion concentration data, which makes it easy for users to intuitively view the layered distribution of the three-dimensional concentration field in the three-dimensional scene and provide data support for leakage risk calculation.

[0152] In optional embodiments, the present invention stores the dynamically calculated three-dimensional concentration field results and three-dimensional visualization results in real time, supporting playback of the diffusion process and visualization query of the leakage consequence level at any time.

[0153] Example 2

[0154] The petrochemical enterprise leakage risk comprehensive dynamic analysis system provided in Embodiment 2 of the present invention includes: a data collection and processing module, an input file preparation module, a leakage diffusion calculation module, and a three-dimensional visualization output module;

[0155] The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0156] The leakage diffusion calculation module is configured to call the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0157] The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site to calculate the distribution of pollutants in the 3D concentration field within the factory area, and then visualizes it in the 3D engine. Example 2 is a variation of the scheme in Example 1 above; therefore, the technical features that are the same as or corresponding to those in Example 1 will not be repeated. The following only describes the distinguishing technical features of this example.

[0158] Preferably, in one embodiment, the leakage diffusion calculation module discretizes time into n time points according to the characteristics of the three-dimensional concentration field data, uses the time points as attribute information of spatial objects, and forms a spatiotemporal snapshot with the spatial features as the spatiotemporal state of the entire spatial features. Finally, the snapshot is output and expressed according to time T.

[0159] Based on the requirements of spatial, attribute, and temporal characteristics, the model calculation results are stored in the computer as a spatiotemporal data model and a spatiotemporal data model. Spatial information refers to the location information (x, y, z) of the gas with specific concentrations in three-dimensional space; attribute information refers to the gas concentration information (C); and temporal characteristics refer to key information such as the time interval (T_interval). These three elements constitute snapshot information of the gas dynamic diffusion, which is saved to the spatial database of the rapid leakage risk calculation system to describe the spatial state and characteristics of geographical objects at different times. Each snapshot information represents the spatiotemporal state of the leaked gas at a certain time t, and the snapshot information is output with a time interval (T_interval) as the step size.

[0160] Starting from the moment the gas leak begins, result files are created sequentially at specified time intervals to achieve structured storage of spatiotemporal data and save the time-series results of gas concentration at each layer.

[0161] In a preferred embodiment, a 5-tuple (x,y,z,C,T_interval) is used to represent snapshot information of gas dynamic diffusion, which is used to describe the spatial state and characteristics of a point in the three-dimensional concentration field at different times.

[0162] Each snapshot represents the spatiotemporal state of the leaked gas at a certain moment t, and the snapshot information is output with a time interval T_interval as the step size.

[0163] Then, in the user-specified output path, folders are created layer by layer to save the time-series gas concentration results in snapshot form for each layer. Within each layer's folder, text files are created sequentially at intervals of t seconds from the start of the gas leak, meeting the requirements for structured storage of spatiotemporal data.

[0164] Example 3

[0165] The comprehensive dynamic analysis system for leakage risk in petrochemical enterprises provided in Embodiment 3 of this invention includes: a data collection and processing module, an input file preparation module, a leakage diffusion calculation module, and a three-dimensional visualization output module;

[0166] The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0167] The leakage diffusion calculation module is configured to call the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0168] The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site to calculate the distribution of pollutants in the 3D concentration field within the factory area, and then visualizes it in the 3D engine. Example 3 is a variation of the solutions in Example 1 or Example 2 above. Therefore, the same or corresponding technical features in this part will not be repeated. The following only describes the distinguishing technical features of this example.

[0169] Furthermore, in a preferred embodiment, the system further includes:

[0170] The leakage hazard risk analysis module is configured to consider the degree of harm that toxic and harmful gases may cause to the human body. Based on set hazard level indicators, it classifies and outputs the degree of harm caused by different concentrations of pollutants, such as... Figure 5 As shown.

[0171] Considering the health effects, bodily damage, and even life-threatening consequences of toxic and harmful gases, the degree of harm to on-site personnel from toxic and harmful gases is classified into four levels based on the short-term exposure limit (PC-STEL), maximum allowable concentration (MAC), and minimum lethal concentration (LC0):

[0172]

[0173] Specifically, in an optional embodiment, contour lines can be drawn on each floor of the equipment and facilities within the plant area based on the concentration values ​​corresponding to the above four levels. The diffusion influence area of ​​each floor is divided into four parts, and the four areas are distinguished and marked with four colors: red, orange, yellow, and blue, so as to achieve real-time early warning and reminder.

[0174] Based on the above operations, the embodiments of the present invention can visualize the three-dimensional concentration data and risk level diagram information by combining them with a map of the three-dimensional leakage scenario of on-site equipment and facilities, allowing technicians to intuitively see the distribution information of leakage locations, leakage concentration information (including dry and wet deposition data), and risk level information of different pollution leakage sources.

[0175] On the other hand, in an optional embodiment, the petrochemical enterprise leakage risk comprehensive dynamic analysis system of this invention adopts a B / S structure, which is divided into three layers, such as... Figure 6 As shown.

[0176] (1) Data layer

[0177] The data collection and processing module is located in the data layer. This data layer primarily consists of preprocessed data files, gas properties, diffusion model calculation result files, and scene X3D (*.x3d) 3D model files, used by the service layer's embedded gas diffusion model encapsulation program for invocation. Data storage employs both relational database and disk file storage. Business data resides in the relational database; diffusion-related data files and result files are saved and retrieved as disk files, mainly containing information about the source, receptor, meteorological data, geographic data, and model control parameters from a series of input files.

[0178] (2) Service Layer

[0179] The leakage and diffusion calculation module is located in the service layer. Based on this, the service layer provides gas diffusion model services, risk calculation services, and access control. This layer accepts data parameter requests from clients, extracts 3D data from scene files, and combines it with preprocessed data files to perform gas leakage and diffusion simulation calculations based on an improved diffusion model. The results are then returned to the presentation layer for the X3D engine to display. The access control component primarily controls system access permissions and data encryption.

[0180] (3) Presentation layer

[0181] It supports dynamically loading 3D models of the plant area. Users can set parameters such as wind direction, wind speed, temperature, humidity, air pressure, precipitation, cloud cover, cloud base height, and diffusion time on the client side, and interact with the service layer through a WEBAPI interface. It also supports dynamic display of the 3D gas leak impact range and consequences in a 4-color map.

[0182] In practical applications, users with viewing permissions and requirements can set specific parameters such as wind direction, wind speed, temperature, humidity, air pressure, precipitation, cloud cover, cloud base height, and diffusion time via the client. These parameters are then sent to the server in XML format to request the download of the plant's 3D scene file. A 3D engine plugin embedded in the browser is used to display the 3D scene. The improved leakage diffusion calculation model is embedded in the 3D system to obtain 3D concentration field data. Based on this, the consequences of leakage risks are determined, and the 3D concentration field and leakage risk consequences are visualized in 3D.

[0183] This invention can be applied to the comprehensive assessment of leakage risk in petrochemical enterprises. It effectively simulates various leakage types, including small-diameter leaks, large-diameter leaks, and leaks from completely fractured pipelines. It can create different pollution source emission files for different leakage scenarios and is suitable for simulation areas with rugged terrain, complex topography, significant elevation differences, and high difficulty in predicting diffusion ranges. By intersecting the generated three-dimensional concentration field with the three-dimensional scene of the petrochemical enterprise production site, the three-dimensional distribution of toxic and harmful gases within the plant area can be quickly obtained: for single-layer facilities, the ground concentration within the affected area can be obtained; for multi-layer facilities, the concentration distribution within the affected area of ​​each layer can be obtained separately. Furthermore, the severity of harm to on-site personnel can be dynamically classified and represented using a four-color graph. This method has broad application prospects in the comprehensive assessment of toxic gas leakage risk in petrochemical enterprises.

[0184] In this specification, the steps described in the flowcharts include not only processes executed sequentially in the stated order, but also processes executed in parallel or individually, rather than necessarily sequentially. Furthermore, even within steps involving sequential processing, it goes without saying that the order can be appropriately altered. All descriptions above are merely embodiments of the invention, and the scope of protection of the invention is not limited thereto. Those skilled in the art can readily make any changes or substitutions. Therefore, the scope of protection of the invention should be defined by the scope of the claims.

[0185] In the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises provided in this embodiment of the invention, each module or unit structure can operate independently or in combination according to actual parameter processing requirements and three-dimensional calculation requirements to achieve the corresponding technical effects.

[0186] Example 4

[0187] The above-described embodiments of the present invention have provided a detailed description of the system. Based on other aspects of the system described in any one or more of the above embodiments, the present invention also provides a comprehensive dynamic analysis method for leakage risks in petrochemical enterprises. This method is applied to the comprehensive dynamic analysis system for leakage risks in petrochemical enterprises described in any one or more of the above embodiments. Specific embodiments are given below for detailed description.

[0188] Specifically, the comprehensive dynamic analysis method for leakage risk in petrochemical enterprises provided in this embodiment of the invention includes:

[0189] Data collection and processing steps: Obtain and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0190] Input file preparation steps: It is configured to prepare multiple input files for the leakage diffusion calculation model based on the collected and preprocessed data;

[0191] The leakage diffusion calculation steps are as follows: by calling the input file corresponding to the calculation parameters through the matching data interface, the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario is realized based on the set leakage diffusion calculation model, forming a three-dimensional concentration field;

[0192] 3D visualization output steps: Overlay the generated 3D concentration field with the 3D scene of the enterprise's production site, calculate the distribution of pollutants in the 3D concentration field of the factory area, and visualize it in the 3D engine.

[0193] Furthermore, in one embodiment, the method further includes:

[0194] The steps of the leak hazard risk analysis consider the degree of harm that toxic and harmful gases may cause to the human body. Based on the set hazard level index, the degree of harm caused by different concentrations of pollutants is classified, characterized, and output.

[0195] The method is applied to the comprehensive dynamic analysis system for leakage risk in petrochemical enterprises provided in this embodiment of the invention. The system includes: a data collection and processing module, an input file preparation module, a leakage diffusion calculation module, and a three-dimensional visualization output module.

[0196] The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data;

[0197] The input file preparation module is configured to prepare multiple input files for the leakage diffusion calculation model based on the collected and preprocessed data;

[0198] The leakage diffusion calculation module is configured to call the input file corresponding to the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field.

[0199] The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site, calculates the distribution of pollutants in the 3D concentration field of the factory area, and displays it in the 3D engine.

[0200] Furthermore, in one embodiment, the system further includes:

[0201] The leakage hazard risk analysis module is configured to consider the degree of harm that toxic and harmful gases may cause to the human body, and to classify and output the degree of harm of pollutants at different concentrations based on the set hazard level indicators.

[0202] In an optional embodiment, the data collection and processing module includes:

[0203] The data collection submodule is configured to directly collect pollution leakage parameters, meteorological monitoring data, and leakage location data through an interactive interface.

[0204] The data preprocessing submodule is configured to determine leakage-related data based on the location of the leak point, acquire meteorological monitoring data, acquire path information of DEM and LULC files, and store them in the database of the data collection and processing module.

[0205] Preferably, in one embodiment, the data preprocessing submodule further includes a data verification unit, which is configured to verify the integrity of meteorological data, determine whether the numerical range is normal, and check and determine the type and resolution of terrain data.

[0206] Furthermore, in one embodiment, the data preprocessing submodule further includes a geographic parameter conversion unit configured to convert the leak-related map data into UTM 6° projected coordinates using Gaussian forward and inverse calculations.

[0207] Optionally, in one embodiment, the input file preparation submodule includes a geographic data file preparation unit, which is used to determine the extent of the diffusion impact area and grid settings based on the location of the leak point, configure projection, grid resolution, and land use code parameters, and sequentially call the three preprocessors TERREL, CTGPROC, and MAKEGEO to generate the input geographic data for the leak diffusion calculation module.

[0208] In one embodiment, the input file preparation submodule includes a meteorological data file preparation unit, which extracts real-time wind speed and direction data based on meteorological observation data to generate an upper-air meteorological data file; and combines the cloud cover and cloud base height values ​​determined based on the meteorological observation data to generate a ground meteorological data file.

[0209] In a preferred embodiment, the leakage diffusion calculation model adopts the CALPUFF diffusion calculation model. For leakage scenarios of multi-layered three-dimensional petrochemical facilities, based on CALPUFF as the original calculation model, three-dimensional calculation parameters are set in the model according to the diffusion degree in the z-axis direction, and the calculation process is improved by combining pollution leakage parameters to carry out gas concentration calculation of multiple receptor layers, so as to obtain the layer-by-layer diffusion model results, and then merge them to generate overall three-dimensional concentration field time series data. The CALPUFF diffusion calculation model includes the meteorological calculation module CALMET, the diffusion calculation module CALPUFF, and the data post-processing module CALPOST.

[0210] Furthermore, in one embodiment, the meteorological calculation module CALMET generates a meteorological field corresponding to the leakage parameters based on the input geographic data, upper-air meteorological input file, and surface meteorological input file.

[0211] In an optional embodiment, the diffusion calculation module is configured to update the receptor layer parameters based on the meteorological field generated by the meteorological calculation module and the pollution leakage parameters, and to perform cyclic simulation calculations of the transport, transformation and removal processes of pollutants under meteorological conditions that change with time and space, so as to obtain the leakage diffusion concentration and dry and wet deposition flux at different receptor points and generate a gridded three-dimensional concentration field.

[0212] In one embodiment, the data post-processing module is configured to organize the generated three-dimensional concentration data into a formatted file so that it can be called by a web server.

[0213] Furthermore, in one embodiment, the number of receptor layers N is determined according to the following logic:

[0214]

[0215] in,

[0216]

[0217] In the formula, SLH max SLH min These represent the highest and lowest layer heights in the diffusion calculation along the z-axis, respectively. RD is the relative density of the leaking gas, and H... leak h is the height of the leak point from the ground. i The height of device i is determined by the downwind direction from the location of the leak.

[0218] In one optional embodiment, the pollution leakage parameters include not only the name, type, and molecular weight of the leaked substance, but also dry deposition, wet deposition, and chemical conversion parameters;

[0219] For a single target gas or a target gas mixture for which no parameters are recorded, the parameters of the target gas are calculated based on the parameters of a stable set gas, according to the following logic:

[0220]

[0221] in, To set the various parameters of gaseous CO, p k Let k be the parameter of the leaked gas. m is the quantity of the leaked gaseous component, M0 is the relative molecular weight of CO, and M j v j % represents the relative molecular weight and volume percentage of the j-th component in the leaked substance.

[0222] Furthermore, in one embodiment, the diffusion calculation module calculates the concentration contribution of a single smoke plume at a receptor point using the following formula:

[0223]

[0224] In the formula, C represents the ground-level pollutant concentration at the receiver point; Q represents the mass of the pollutant in the plume; σ x σ y σ z d represents the standard deviation of the Gaussian distribution of pollutants in the X, Y, and Z directions, respectively; a d represents the distance from the center of the smoke plume to the receptor point in the X direction; c The distance from the center of the smoke plume to the receptor point in the Y direction is represented by g; g represents the vertical term of the Gaussian equation, characterizing multiple reflections between the mixing layer and the ground; H e represents the effective height of the smoke cloud center above the ground; h represents the height of the mixing layer.

[0225] Optionally, in one embodiment, the diffusion calculation module discretizes time by setting multiple time points, uses gas concentration information as attribute information, location information as spatial features, and time interval as temporal features, and combines attribute information and spatiotemporal features to form a spatiotemporal snapshot to describe the spatial state and diffusion distribution characteristics of geographic objects at different times.

[0226] In one embodiment, the leakage hazard risk analysis module classifies the degree of harm caused by different concentrations of pollutants according to the following logic:

[0227]

[0228] Here, HalHD represents the level of harm caused by the pollutant, C represents the concentration of the pollutant during diffusion, PC-STEL represents the short-term exposure allowable concentration, MAC represents the maximum allowable concentration, and LC0 represents the minimum lethal concentration.

[0229] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0230] It should be noted that, in other embodiments of the present invention, the method can also combine one or more of the above embodiments to obtain a new comprehensive dynamic analysis method for leakage risks in petrochemical enterprises, so as to achieve dynamic and high-precision monitoring of the leakage risks of hazardous chemicals in petrochemical enterprises.

[0231] Example 5

[0232] It should be noted that, based on the methods in any one or more embodiments of the present invention described above, the present invention also provides a storage medium storing program code that can implement the methods described in any one or more embodiments. When the program code is executed by the operating system, it can implement the comprehensive dynamic analysis method for leakage risks in petrochemical enterprises as described above.

[0233] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0234] The phrase "an embodiment" in the specification means that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0235] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A comprehensive dynamic analysis system for leakage risks in petrochemical enterprises, characterized in that, The system includes: a data collection and processing module, an input file preparation module, a leakage diffusion calculation module, and a three-dimensional visualization output module; The data collection and processing module is configured to acquire and process the calculation parameters required for leakage diffusion calculation from different data sources and store them in the database; the calculation parameters include pollution leakage parameters, meteorological monitoring data, leakage location data, geographic information files, upper-air meteorological data, three-dimensional grid elevation data and terrain file data; The input file preparation module is configured to prepare multiple input files for the leakage diffusion calculation model based on the collected and preprocessed data; The leakage diffusion calculation module is configured to call the input file corresponding to the calculation parameters through a matching data interface to realize the dynamic calculation of diffusion concentration of different three-dimensional receptor layers in the leakage scenario based on the set leakage diffusion calculation model, thereby forming a three-dimensional concentration field. The 3D visualization output module overlays the generated 3D concentration field with the 3D scene of the enterprise's production site, calculates the distribution of pollutants in the 3D concentration field of the factory area, and displays it in the 3D engine.

2. The system according to claim 1, characterized in that, The system also includes: The leakage hazard risk analysis module is configured to consider the degree of harm that toxic and harmful gases may cause to the human body, and to classify and output the degree of harm of pollutants at different concentrations based on the set hazard level indicators.

3. The system according to claim 1, characterized in that, The data collection and processing module includes: The data collection submodule is configured to directly collect pollution leakage parameters, meteorological monitoring data, and leakage location data through an interactive interface. The data preprocessing submodule is configured to determine leakage-related data based on the location of the leak point, acquire meteorological monitoring data, acquire path information of DEM and LULC files, and store them in the database of the data collection and processing module.

4. The system according to claim 3, characterized in that, The data preprocessing submodule also includes a data verification unit, which is configured to verify the integrity of meteorological data, determine whether the numerical range is normal, and check and determine the type and resolution of terrain data.

5. The system according to claim 3, characterized in that, The data preprocessing submodule also includes a geographic parameter conversion unit, which is configured to convert the leak-related map data into UTM 6° projected coordinates through Gaussian forward and inverse calculations, so as to facilitate the visualization of three-dimensional coordinates.

6. The system according to claim 1, characterized in that, The input file preparation submodule includes a geographic data file preparation unit, which is used to determine the extent of the diffusion impact area and grid settings based on the location of the leak point, configure projection, grid resolution, and land use code parameters, and sequentially call the three preprocessors TERREL, CTGPROC, and MAKEGEO to generate the input geographic data for the leak diffusion calculation module.

7. The system according to claim 1, characterized in that, The input file preparation submodule includes a meteorological data file preparation unit, which extracts real-time wind speed and direction data from meteorological observation data to generate upper-air meteorological data files; and combines the cloud cover and cloud base height values ​​determined from the meteorological observation data to generate ground meteorological data files.

8. The system according to claim 1, characterized in that, The leakage diffusion calculation model adopts the CALPUFF diffusion calculation model. For leakage scenarios of multi-layer three-dimensional petrochemical facilities, based on CALPUFF as the original calculation model, three-dimensional calculation parameters are set in the model by considering the diffusion degree in the z-axis direction. The calculation process is improved by combining pollution leakage parameters to carry out gas concentration calculation of multiple receptor layers, obtaining layer-by-layer diffusion model results, and then merging to generate overall three-dimensional concentration field time series data. The CALPUFF diffusion calculation model includes the meteorological calculation module CALMET, the diffusion calculation module CALPUFF, and the data post-processing module CALPOST.

9. The system according to claim 8, characterized in that, The meteorological calculation module CALMET generates a meteorological field corresponding to the leakage parameters based on the input geographic data, upper-air meteorological input file, and surface meteorological input file.

10. The system according to claim 8, characterized in that, The diffusion calculation module is configured to update the receptor layer parameters based on the meteorological field generated by the meteorological calculation module and the pollution leakage parameters, and to perform cyclic simulation calculations on the transport, transformation and removal processes of pollutants under meteorological conditions that change with time and space, so as to obtain the leakage diffusion concentration and dry and wet deposition flux at different receptor points and generate a gridded three-dimensional concentration field.

11. The system according to claim 8, characterized in that, The data post-processing module is configured to organize the generated three-dimensional concentration data into a formatted file so that it can be called by the web server.

12. The system according to claim 8, characterized in that, The number of receptor layers N is determined according to the following logic: in, In the formula, SLH max SLH min These represent the highest and lowest layer heights in the diffusion calculation along the z-axis, respectively. RD is the relative density of the leaking gas, and H... leak h is the height of the leak point from the ground. i The height of device i is determined by the downwind direction from the leak location.

13. The system according to claim 8, characterized in that, The pollution leakage parameters include not only the name, type and molecular weight of the leaked substance, but also dry deposition, wet deposition and chemical conversion parameters. For a single target gas or a target gas mixture for which no parameters are recorded, the parameters of the target gas are calculated based on the parameters of a stable set gas, according to the following logic: in, To set the various parameters of gaseous CO, p k Let k be the parameter of the leaked gas. m is the quantity of the leaked gaseous component, M0 is the relative molecular weight of CO, and M j v j % represents the relative molecular weight and volume percentage of the j-th component in the leaked substance.

14. The system according to claim 8, characterized in that, The diffusion calculation module calculates the concentration contribution of a single smoke plume at a receiver point using the following formula: In the formula, C represents the ground-level pollutant concentration at the receiver point; Q represents the mass of the pollutant in the plume; σ x σ y σ z d represents the standard deviation of the Gaussian distribution of pollutants in the X, Y, and Z directions, respectively; a d represents the distance from the center of the smoke plume to the receptor point in the X direction; c The distance from the center of the smoke plume to the receptor point in the Y direction is represented by g; g represents the vertical term of the Gaussian equation, characterizing multiple reflections between the mixing layer and the ground; H e represents the effective height of the smoke cloud center above the ground; h represents the height of the mixing layer.

15. The system according to claim 9, characterized in that, The diffusion calculation module discretizes time by setting multiple time points, uses gas concentration information as attribute information, location information as spatial features, and time interval as temporal features, and combines attribute information and spatiotemporal features to form a spatiotemporal snapshot to describe the spatial state and diffusion distribution characteristics of geographic objects at different times.

16. The system according to claim 2, characterized in that, The leakage hazard risk analysis module classifies the degree of harm caused by different concentrations of pollutants according to the following logic: Here, HalHD represents the level of harm caused by the pollutant, C represents the concentration of the pollutant during diffusion, PC-STEL represents the short-term exposure allowable concentration, MAC represents the maximum allowable concentration, and LC0 represents the minimum lethal concentration.

17. A comprehensive dynamic analysis method for leakage risk in petrochemical enterprises, characterized in that, The method is applied to the system described in any one of claims 1 to 16.

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