Method and device for predicting diffusion range of carbon dioxide leakage gas cloud

Abstract

The embodiment of the invention relates to a method and device for predicting the gas cloud diffusion range of carbon dioxide leakage. The method comprises the steps that a carbon dioxide station yard leakage diffusion multiphase flow model is established; simulating the leakage diffusion multiphase flow model of the carbon dioxide station yard under different conditions, and determining characteristic data of a carbon dioxide diffusion leakage range; performing data fitting on the carbon dioxide diffusion leakage range characteristic data to obtain a carbon dioxide station leakage diffusion empirical formula; and predicting a carbon dioxide leakage gas cloud diffusion range of a target carbon dioxide station where carbon dioxide leakage occurs currently based on the carbon dioxide station leakage diffusion empirical formula. Therefore, the diffusion range of the carbon dioxide leakage gas cloud can be quickly predicted, and a certain basis is provided for formulating targeted emergency rescue measures for reducing accident injuries.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of calculating the hazard level and impact range of carbon dioxide, and particularly to a method and apparatus for predicting the diffusion range of carbon dioxide leak gas clouds. Background Technology

[0002] In recent years, CCUS technology has been widely applied. CO2 stations, as a crucial part of the entire CCUS process, are complex systems and are more prone to release accidents compared to long-distance pipelines. If CO2 release is not controlled in a timely manner, it can cause equipment damage, personal injury, and economic losses. Therefore, studying and analyzing the hazard levels and impact range of CO2 release processes is of significant guiding and reference value for CO2 release accident prevention and risk control.

[0003] CO2 storage tanks are the equipment in the station that stores the most CO2, and they also release the most CO2 in the event of an accident. Existing numerical calculation models show high accuracy in predicting CO2 tank leaks; however, in actual production environments, on-site personnel often lack the skills to operate specialized software, and model calculations are time-consuming. Therefore, numerical calculation models are not suitable for emergency evacuation decisions at leak sites. Thus, how to quickly determine the extent of CO2 gas cloud diffusion has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, in order to solve the above-mentioned technical problems or some of the technical problems, the present invention provides a method and apparatus for predicting the diffusion range of carbon dioxide leakage gas clouds.

[0005] In a first aspect, embodiments of the present invention provide a method for predicting the diffusion range of a carbon dioxide leak cloud, comprising:

[0006] Establish a multiphase flow model for leakage and diffusion at carbon dioxide stations;

[0007] Simulations were performed on the multiphase flow model of carbon dioxide leakage and diffusion at the carbon dioxide station under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range.

[0008] By fitting the data on the characteristics of carbon dioxide diffusion and leakage range, an empirical formula for carbon dioxide leakage and diffusion at carbon dioxide stations is obtained.

[0009] Based on the empirical formula for carbon dioxide station leakage diffusion, the diffusion range of the carbon dioxide leak gas cloud at the target carbon dioxide station where a carbon dioxide leak has occurred is predicted.

[0010] In one possible implementation, the method further includes:

[0011] Based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment within the target carbon dioxide station, a geometric model of the carbon dioxide station is established.

[0012] A multiphase flow model for carbon dioxide leakage diffusion was established based on the aforementioned carbon dioxide station geometric model and the location of carbon dioxide leakage.

[0013] In one possible implementation, the method further includes:

[0014] Using a preset safe carbon dioxide concentration threshold as the research object, the multiphase flow model of carbon dioxide station leakage and diffusion is simulated under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The different conditions include at least leakage amount, wind speed, leakage direction and ambient temperature.

[0015] In one possible implementation, the method further includes:

[0016] Based on the carbon dioxide diffusion and leakage range characteristic data, it was determined that the diffusion range of the carbon dioxide leaked gas cloud and the carbon dioxide diffusion and leakage range characteristic data showed different correlations.

[0017] The target carbon dioxide leakage range data is determined based on the correlation between the diffusion range of the carbon dioxide leak gas cloud and the characteristic data of the carbon dioxide diffusion and leakage range.

[0018] Based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide cloud as the dependent variable and the characteristics of the carbon dioxide diffusion and leakage range as the independent variable, the Cftool tool in Matlab was used to fit the data, and the empirical formula for carbon dioxide leakage and diffusion at the station corresponding to the target carbon dioxide leakage range data was obtained.

[0019] In one possible implementation, the method further includes:

[0020] Obtain the amount of carbon dioxide leakage at the target carbon dioxide station;

[0021] An empirical formula for determining the leakage and diffusion of target carbon dioxide stations based on the aforementioned carbon dioxide leakage amount;

[0022] Determine the current wind speed based on the current weather conditions;

[0023] By substituting the carbon dioxide leakage amount and the current wind speed into the empirical formula for leakage diffusion at the target carbon dioxide station, the diffusion range of the carbon dioxide leakage cloud can be obtained.

[0024] In one possible implementation, the method further includes:

[0025] The error rate was obtained by comparing the diffusion range of the carbon dioxide leak gas cloud with the results of numerical simulation calculations.

[0026] The validity of the empirical formula for carbon dioxide station leakage and diffusion is determined based on the error rate.

[0027] In one possible implementation, the method further includes:

[0028] Accident rescue plans are developed based on the predicted diffusion range of the carbon dioxide leak cloud.

[0029] Secondly, embodiments of the present invention provide a device for predicting the diffusion range of a carbon dioxide leak cloud, comprising:

[0030] A module was established to create a multiphase flow model for leakage and diffusion at a carbon dioxide station.

[0031] The determination module is used to simulate the multiphase flow model of carbon dioxide leakage and diffusion under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range.

[0032] The fitting module is used to fit the carbon dioxide diffusion and leakage range characteristic data to obtain the empirical formula for carbon dioxide station leakage and diffusion.

[0033] The prediction module is used to predict the diffusion range of the carbon dioxide leak cloud at the target carbon dioxide station where a carbon dioxide leak has occurred, based on the empirical formula for carbon dioxide station leakage diffusion.

[0034] Thirdly, embodiments of the present invention provide a computer device, including: a processor and a memory, wherein the processor is configured to execute a prediction program for the diffusion range of a carbon dioxide leak cloud stored in the memory, so as to implement the prediction method for the diffusion range of a carbon dioxide leak cloud described in the first aspect above.

[0035] Fourthly, embodiments of the present invention provide a storage medium, comprising: the storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the method for predicting the diffusion range of carbon dioxide leak gas clouds as described in the first aspect above.

[0036] The carbon dioxide leak cloud diffusion range prediction scheme provided in this invention establishes a multiphase flow model for carbon dioxide station leakage diffusion; simulates the multiphase flow model under different conditions to determine the characteristic data of carbon dioxide diffusion leakage range; fits the characteristic data of carbon dioxide diffusion leakage range to obtain an empirical formula for carbon dioxide station leakage diffusion; and predicts the carbon dioxide leak cloud diffusion range of the target carbon dioxide station where a carbon dioxide leak has occurred based on the empirical formula. Compared with existing numerical calculation models, which lack professional personnel for predicting CO2 tank leaks and have long calculation times, making them unsuitable for guiding emergency evacuations, this scheme, by establishing a geometric model of the station and reconstructing the accident scene, summarizes and analyzes patterns based on a large amount of simulation data, and fits an empirical formula for CO2 station leakage diffusion. This allows for rapid prediction of the diffusion range of CO2 leak cloud, providing a basis for developing targeted emergency rescue measures to reduce accident damage. Attached Figure Description

[0037] Figure 1 A flowchart illustrating a method for predicting the diffusion range of a carbon dioxide leak cloud, provided in an embodiment of the present invention.

[0038] Figure 2 A flowchart illustrating another method for predicting the diffusion range of a carbon dioxide leak cloud provided in an embodiment of the present invention.

[0039] Figure 3 A graph showing the relationship between the farthest diffusion distance of a carbon dioxide leak cloud and the leakage amount is provided in an embodiment of the present invention.

[0040] Figure 4 A schematic diagram of data fitting results for a carbon dioxide leakage amount not exceeding 6000 kg, provided as an embodiment of the present invention;

[0041] Figure 5 A schematic diagram of data fitting results for a carbon dioxide leakage amount greater than 6000 kg and less than 25000 kg, provided as an embodiment of the present invention;

[0042] Figure 6 A schematic diagram of the structure of a device for predicting the diffusion range of a carbon dioxide leak cloud provided in an embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0046] Figure 1 A flowchart illustrating a method for predicting the diffusion range of a carbon dioxide leak cloud, as provided in an embodiment of the present invention, is shown below. Figure 2 As shown, the method specifically includes:

[0047] S11. Establish a multiphase flow model for leakage and diffusion at carbon dioxide stations.

[0048] The present invention provides a method for predicting the diffusion range of carbon dioxide leaked gas clouds, which can more quickly predict the farthest diffusion distance of carbon dioxide gas clouds leaking from storage tanks and calculate the farthest diffusion distance of carbon dioxide gas clouds at a safe concentration threshold (10,000 ppm concentration) under different wind speed conditions.

[0049] Specifically, a geometric model of the carbon dioxide station is established based on the geometric parameters of the equipment, the spacing between the equipment, and the surrounding environment. Then, a multiphase flow model of carbon dioxide leakage diffusion is established based on the geometric model of the carbon dioxide station and the location of the carbon dioxide leak.

[0050] S12. Simulate the carbon dioxide station leakage and diffusion multiphase flow model under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range.

[0051] Using a preset safe carbon dioxide concentration threshold as the research object, the multiphase flow model of carbon dioxide leakage and diffusion at a carbon dioxide station was simulated under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The different conditions include at least leakage amount, wind speed, leakage direction and ambient temperature.

[0052] The Chinese national standard GB / T 6052-2011, "Industrial Liquid Carbon Dioxide," clearly states that the occupational exposure limit (MAC) in China is 18,000 mg·m⁻³ (10,000 ppm). Therefore, without considering the exposure time, the safe concentration threshold of 10,000 ppm is used as the minimum concentration for judging carbon dioxide poisoning and asphyxiation. Using the safe concentration threshold of 10,000 ppm as the research object, the effects of four factors—leakage amount, wind speed, leakage direction, and ambient temperature—on the diffusion of a carbon dioxide cloud at a concentration of 10,000 ppm are studied. It is found that leakage amount and wind speed are the two factors with the greatest impact on the diffusion range of carbon dioxide leaks.

[0053] S13. Perform data fitting on the carbon dioxide diffusion and leakage range characteristic data to obtain the empirical formula for carbon dioxide station leakage and diffusion.

[0054] Based on the characteristics of carbon dioxide diffusion and leakage range, it was determined that the diffusion range of the carbon dioxide leaking gas cloud and the characteristics of carbon dioxide diffusion and leakage range exhibit different correlations. Based on the correlation between the diffusion range of the carbon dioxide leaking gas cloud and the characteristics of carbon dioxide diffusion and leakage range, the target carbon dioxide leakage range data was determined. Based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide gas cloud as the dependent variable and the characteristics of carbon dioxide diffusion and leakage range as the independent variable, the Cftool tool in Matlab was used to fit the data, and the empirical formula for carbon dioxide leakage and diffusion at the carbon dioxide station corresponding to the target carbon dioxide leakage range data was obtained.

[0055] S14. Based on the empirical formula for carbon dioxide station leakage diffusion, predict the diffusion range of the carbon dioxide leak cloud at the target carbon dioxide station where a carbon dioxide leak has occurred.

[0056] Obtain the carbon dioxide leakage amount of the target carbon dioxide station; determine the empirical formula for leakage diffusion of the target carbon dioxide station based on the carbon dioxide leakage amount; determine the current wind speed based on the current meteorological conditions; substitute the carbon dioxide leakage amount and the current wind speed into the empirical formula for leakage diffusion of the target carbon dioxide station to obtain the diffusion range of the carbon dioxide leakage cloud.

[0057] Optionally, to ensure the validity of the empirical formula, the predicted results are compared with the results of numerical simulations, and the error rate between the two is calculated. It can be seen that, in most cases, the error rate between the fitted empirical formula and the numerical simulation is within ±10%. Since the far-field diffusion of carbon dioxide leaks is affected by numerous factors, a 10% error rate is acceptable in engineering practice. However, since the equipment and processes are the same across different stations, the calculated empirical formula for carbon dioxide leak diffusion has broad applicability.

[0058] The method for predicting the diffusion range of carbon dioxide leak clouds provided in this invention establishes a multiphase flow model for carbon dioxide leakage diffusion at a storage station; simulates the multiphase flow model under different conditions to determine the characteristic data of carbon dioxide diffusion leakage range; fits the characteristic data of carbon dioxide diffusion leakage range to obtain an empirical formula for carbon dioxide leakage diffusion at the storage station; and predicts the diffusion range of carbon dioxide leak clouds at the target carbon dioxide storage station where a carbon dioxide leak has occurred based on the empirical formula. Compared to existing numerical calculation models, which lack skilled personnel for predicting carbon dioxide tank leaks and have long calculation times, making them unsuitable for guiding emergency evacuations, this method, by establishing a geometric model of the storage station and reconstructing the accident scene, summarizes and analyzes patterns based on a large amount of simulation data, and fits an empirical formula for carbon dioxide leakage diffusion at the storage station. This allows for rapid prediction of the diffusion range of carbon dioxide leak clouds, providing a basis for developing targeted emergency rescue measures to reduce accident damage.

[0059] Figure 2 A flowchart illustrating another method for predicting the diffusion range of a carbon dioxide leak cloud provided in an embodiment of the present invention is shown below. Figure 2 As shown, the method specifically includes:

[0060] First, let's introduce the application scenario of this method: With the development of CCUS technology, increasing emphasis is being placed on the safety of carbon dioxide storage and use. From the perspective of emergency rescue and mitigating the consequences of accidents, it is essential to conduct accident simulation. The carbon dioxide leakage range prediction formula based on numerical simulation designed in this embodiment of the invention is a convenient method for quickly and accurately predicting the diffusion range of carbon dioxide clouds after a carbon dioxide leak occurs in a station. It has important guiding and reference significance for the prevention of carbon dioxide release accidents, risk control, emergency rescue, and proper response during accidents, and has broad application prospects.

[0061] S21. Based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment within the target carbon dioxide station, establish a geometric model of the carbon dioxide station.

[0062] Taking a carbon dioxide station as an example, a geometric model of the carbon dioxide station is established based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment, according to the on-site survey.

[0063] S22. Based on the geometric model of the carbon dioxide station and the location of the carbon dioxide leak, establish a multiphase flow model for the leakage and diffusion of carbon dioxide at the carbon dioxide station.

[0064] During equipment operation at the station, the pressure inside the pipeline surged due to the continuous vaporization of high-pressure, low-temperature liquid carbon dioxide by the cryogenic liquefaction vaporizer. This led to a rupture at a pipe bend, releasing a large amount of liquid carbon dioxide from the storage tank into the atmosphere. This leak location was selected as the research object, and a far-field diffusion multiphase flow model of carbon dioxide leakage was established.

[0065] S23. Using the preset carbon dioxide safe concentration threshold as the research object, simulate the carbon dioxide station leakage diffusion multiphase flow model under different conditions to determine the carbon dioxide diffusion leakage range characteristic data.

[0066] The Chinese national standard GB / T 6052-2011, "Industrial Liquid Carbon Dioxide," clearly states that the occupational exposure limit (MAC) in China is 18,000 mg·m⁻³ (10,000 ppm). Therefore, without considering the exposure time, the safe concentration threshold of 10,000 ppm is used as the minimum concentration for judging carbon dioxide poisoning and asphyxiation. Using the safe concentration threshold of 10,000 ppm as the research object, the effects of four factors—leakage amount, wind speed, leakage direction, and ambient temperature—on the diffusion of a carbon dioxide cloud at a concentration of 10,000 ppm are studied. It is found that leakage amount and wind speed are the two factors with the greatest impact on the diffusion range of carbon dioxide leaks.

[0067] S24. Based on the carbon dioxide diffusion and leakage range characteristic data, it is determined that the carbon dioxide leakage gas cloud diffusion range and the carbon dioxide diffusion and leakage range characteristic data show different correlations.

[0068] Simulations of the far-field diffusion model of carbon dioxide leakage at a gas station were conducted under different conditions. The resulting graphs show the relationship between the furthest diffusion distance of a 10000 ppm carbon dioxide cloud and the leakage amount under different wind speeds. Figure 3 As shown. Figure 3 The graph showing the relationship between the farthest diffusion distance of a carbon dioxide leak cloud and the leakage amount is provided in an embodiment of the present invention. Before and after the leakage amount of 6000 kg, the farthest diffusion distance of the carbon dioxide cloud shows different correlations with the leakage amount and wind speed.

[0069] 1. When the leakage amount does not exceed 6000 kg, the greater the wind speed, the farther the cloud spreads.

[0070] 2. When the leakage exceeds 6000 kg, the gas cloud continues to spread forward under low wind speed conditions. Under high wind speed conditions, due to the dilution of the carbon dioxide leakage gas cloud by the wind speed, the gas cloud spreads to the farthest distance and then decreases. As the leakage continues, the gas cloud diffusion range tends to stabilize.

[0071] S25. Determine the target carbon dioxide leakage range data based on the correlation between the carbon dioxide leakage cloud diffusion range and the carbon dioxide diffusion leakage range characteristic data.

[0072] The farthest diffusion distance of the carbon dioxide cloud before and after a leakage of 6000 kg showed different correlations with the leakage amount and wind speed. Therefore, data from two intervals of leakage amount (0, 6000) and (0, 25000) were selected. The farthest diffusion distance X of the carbon dioxide cloud was used as the dependent variable, and the leakage amount Q and V were used as independent variables. The Cftool tool in Matlab was used to fit the data.

[0073] S26. Based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide cloud as the dependent variable and the carbon dioxide diffusion leakage range characteristic data as the independent variable, the Cftool tool in Matlab is used to fit the data to obtain the empirical formula for carbon dioxide leakage diffusion at the carbon dioxide station corresponding to the target carbon dioxide leakage range data.

[0074] like Figure 4 The fitting results are for carbon dioxide leakage amounts not exceeding 6000 kg. As can be seen from the figure, when the leakage amount is less than 6000 kg, the diffusion distance of a carbon dioxide cloud with a concentration of 10000 ppm shows a certain pattern with respect to the leakage time and leakage amount. The fitting result is Equation 1, and the R2 value is 0.9953.

[0075] X = (0.0681 + 0.0423V)·Q 0.8908 Formula 1

[0076] Where X is the farthest diffusion distance, Q is the leakage amount, V is the wind speed, 0.5 m·s⁻¹ ≤ V ≤ 6.7 m·s⁻¹, 0 kg <Q≤6000kg。

[0077] like Figure 5 The fitting graph is for leakage amounts greater than 6000 kg and less than 25000 kg. The fitting result is Equation 2, and the R2 value is 0.9025.

[0078] X=-154.8821+0.0307Q+521.1531V-0.0160QV

[0079] -107.0801V 2 +0.0017QV 2 +5.9979V 3 Formula 2

[0080] Where X is the farthest diffusion distance, Q is the leakage amount, V is the wind speed, 0.5 m·s⁻¹ ≤ V ≤ 6.7 m·s⁻¹, 6000 kg <Q≤25000kg。

[0081] S27. Obtain the carbon dioxide leakage amount of the target carbon dioxide station.

[0082] S28. Determine the empirical formula for leakage and diffusion of the target carbon dioxide station based on the amount of carbon dioxide leakage.

[0083] S29. Determine the current wind speed based on the current meteorological conditions.

[0084] S210. Substitute the carbon dioxide leakage amount and the current wind speed into the empirical formula for leakage diffusion at the target carbon dioxide station to obtain the diffusion range of the carbon dioxide leakage cloud.

[0085] The following provides a unified explanation of S27-S210:

[0086] Taking a certain carbon dioxide station (the target carbon dioxide station) as an example, calculate the diffusion range of the carbon dioxide leak cloud under different conditions:

[0087] First, the carbon dioxide leakage rate at the target carbon dioxide station can be determined using existing carbon dioxide leakage measurement devices. Then, an empirical formula for leakage diffusion at the target carbon dioxide station can be determined based on the carbon dioxide leakage rate.

[0088] For example, if the leakage amount does not exceed 6000 kg, such as a leakage amount Q of 4500 kg, the wind speed V at the time of leakage can be determined to be 4.4 m / s based on meteorological conditions. Substituting the wind speed V and leakage amount Q into the fitting formula X = (0.0681 + 0.0423V)·Q 0.8908 The maximum diffusion distance X can be calculated to be 457m.

[0089] Optionally, if the leakage amount is greater than 6000 kg but less than 25000 kg, for example, if the leakage amount Q is 12500 kg, the wind speed V at the time of leakage can be determined to be 1.5 m / s based on meteorological conditions. Substituting the wind speed V and the leakage amount Q into the fitting formula... The maximum diffusion distance X can be calculated to be 538m.

[0090] To ensure the validity of the empirical formula, the predicted results were compared with those calculated using numerical simulations, and the error rate between the two was calculated. It was found that, in most cases, the error rate between the fitted empirical formula and the numerical simulation is within ±10%. Since the far-field diffusion of carbon dioxide leaks is affected by numerous factors, a 10% error rate is acceptable in engineering practice. However, since the equipment and processes are the same across different stations, the calculated empirical formula for carbon dioxide leak diffusion has broad applicability.

[0091] This invention provides a method for predicting the diffusion range of a carbon dioxide leak cloud, solving the problem of the time-consuming process of using numerical calculation models to predict the diffusion range of a carbon dioxide leak cloud from a storage tank. By fitting an empirical formula for the diffusion impact range of a carbon dioxide leak, the maximum distance of the cloud diffusion during a leak can be quickly predicted, guiding emergency evacuation decisions and rescue efforts at the leak site. This empirical formula has significant guiding and reference value in accident prevention, risk control, emergency rescue, and proper response during accidents.

[0092] The method for predicting the diffusion range of carbon dioxide leak clouds provided in this invention establishes a multiphase flow model for carbon dioxide leakage diffusion at a storage station; simulates the multiphase flow model under different conditions to determine the characteristic data of carbon dioxide diffusion leakage range; fits the characteristic data of carbon dioxide diffusion leakage range to obtain an empirical formula for carbon dioxide leakage diffusion at the storage station; and predicts the diffusion range of carbon dioxide leak clouds at the target carbon dioxide storage station where a carbon dioxide leak has occurred based on the empirical formula. Compared to existing numerical calculation models, which lack skilled personnel for predicting carbon dioxide tank leaks and have long calculation times, making them unsuitable for guiding emergency evacuations, this method, by establishing a geometric model of the storage station and reconstructing the accident scene, summarizes and analyzes patterns based on a large amount of simulation data, and fits an empirical formula for carbon dioxide leakage diffusion at the storage station. This allows for rapid prediction of the diffusion range of carbon dioxide leak clouds, providing a basis for developing targeted emergency rescue measures to reduce accident damage.

[0093] Figure 6 A schematic diagram of a device for predicting the diffusion range of a carbon dioxide leak cloud provided in an embodiment of the present invention, specifically including:

[0094] Module 601 is used to establish a multiphase flow model for leakage and diffusion at a carbon dioxide station. For detailed explanations, please refer to the relevant descriptions in the above method embodiments; they will not be repeated here.

[0095] The determination module 602 is used to simulate the multiphase flow model of carbon dioxide leakage and diffusion at the carbon dioxide station under different conditions to determine the characteristic data of the carbon dioxide diffusion and leakage range. For detailed explanations, please refer to the relevant descriptions in the above method embodiments; they will not be repeated here.

[0096] The fitting module 603 is used to fit the carbon dioxide diffusion and leakage range characteristic data to obtain an empirical formula for carbon dioxide station leakage and diffusion. For detailed explanations, please refer to the relevant descriptions in the above method embodiments; they will not be repeated here.

[0097] The prediction module 604 is used to predict the diffusion range of the carbon dioxide leak cloud at the target carbon dioxide station where a carbon dioxide leak has occurred, based on the empirical formula for carbon dioxide station leakage diffusion. For detailed explanation, please refer to the relevant descriptions in the above method embodiments; they will not be repeated here.

[0098] The device for predicting the diffusion range of carbon dioxide leak clouds provided in this embodiment can be as follows: Figure 6 The device shown in the diagram for predicting the diffusion range of a carbon dioxide leak cloud can perform actions such as... Figure 1-2 All steps of the method for predicting the diffusion range of carbon dioxide leakage gas clouds in China, thereby achieving... Figure 1-2 For details on the technical effectiveness of the method for predicting the diffusion range of carbon dioxide leak gas clouds, please refer to [link / reference needed]. Figure 1-2 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0099] Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 7 The computer device 700 shown includes at least one processor 701, a memory 702, at least one network interface 704, and other user interfaces 703. The various components in the computer device 700 are coupled together via a bus system 705. It is understood that the bus system 705 is used to implement communication between these components. In addition to a data bus, the bus system 705 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 7 The general labeled all buses as Bus System 705.

[0100] The user interface 703 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0101] It is understood that the memory 702 in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 702 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0102] In some implementations, memory 702 stores elements, executable units or data structures, or subsets thereof, or extended sets thereof: operating system 7021 and application program 7022.

[0103] The operating system 7021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 7022 includes various applications, such as a media player and a browser, used to implement various application functions. The program implementing the method of this embodiment can be included in the application program 7022.

[0104] In this embodiment of the invention, by calling the program or instructions stored in the memory 702, specifically the program or instructions stored in the application program 7022, the processor 701 executes the method steps provided in each method embodiment, including, for example:

[0105] A multiphase flow model for carbon dioxide leakage and diffusion at a carbon dioxide station is established; simulations of the multiphase flow model under different conditions are performed to determine the characteristic data of carbon dioxide diffusion and leakage range; the characteristic data of carbon dioxide diffusion and leakage range are fitted to obtain an empirical formula for carbon dioxide leakage and diffusion at a carbon dioxide station; based on the empirical formula for carbon dioxide leakage and diffusion at a carbon dioxide station, the diffusion range of the carbon dioxide leak gas cloud at the target carbon dioxide station where a carbon dioxide leak has occurred is predicted.

[0106] In one possible implementation, a geometric model of the carbon dioxide station is established based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment within the target carbon dioxide station; a multiphase flow model of carbon dioxide station leakage diffusion is then established based on the carbon dioxide station geometric model and the location of the carbon dioxide leak.

[0107] In one possible implementation, a preset safe carbon dioxide concentration threshold is used as the research object, and the multiphase flow model of carbon dioxide leakage and diffusion at the carbon dioxide station is simulated under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The different conditions include at least leakage amount, wind speed, leakage direction and ambient temperature.

[0108] In one possible implementation, based on the carbon dioxide diffusion and leakage range characteristic data, it is determined that the diffusion range of the carbon dioxide leaking gas cloud exhibits different correlations with the carbon dioxide diffusion and leakage range characteristic data; based on the correlations exhibited between the carbon dioxide leaking gas cloud diffusion range and the carbon dioxide diffusion and leakage range characteristic data, a target carbon dioxide leakage range data is determined; based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide gas cloud as the dependent variable and the carbon dioxide diffusion and leakage range characteristic data as the independent variable, the Cftool tool in Matlab is used to fit the data, thereby obtaining an empirical formula for carbon dioxide station leakage and diffusion corresponding to the target carbon dioxide leakage range data.

[0109] In one possible implementation, the carbon dioxide leakage amount of the target carbon dioxide station is obtained; an empirical formula for leakage diffusion of the target carbon dioxide station is determined based on the carbon dioxide leakage amount; the current wind speed is determined based on the current meteorological conditions; and the carbon dioxide leakage amount and the current wind speed are substituted into the empirical formula for leakage diffusion of the target carbon dioxide station to obtain the diffusion range of the carbon dioxide leakage cloud.

[0110] In one possible implementation, the diffusion range of the carbon dioxide leak cloud is compared with the results of numerical simulation to obtain an error rate; the validity of the empirical formula for carbon dioxide station leakage diffusion is then determined based on the error rate.

[0111] In one possible implementation, an accident rescue plan is developed based on the predicted diffusion range of the carbon dioxide leak cloud.

[0112] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in software form. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software units in the decoding processor. The software units may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 702. Processor 701 reads the information in memory 702 and, in conjunction with its hardware, completes the steps of the above method.

[0113] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0114] For software implementation, the techniques described herein can be implemented by units that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0115] The computer device provided in this embodiment may be as follows: Figure 7 The computer device shown can perform, for example Figure 1-2 All steps of the method for predicting the diffusion range of carbon dioxide leakage gas clouds in China, thereby achieving... Figure 1-2 For details on the technical effectiveness of the method for predicting the diffusion range of carbon dioxide leak gas clouds, please refer to [link / reference needed]. Figure 1-2 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0116] This invention also provides a storage medium (computer-readable storage medium). This storage medium stores one or more programs. The storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive; the memory may also include combinations of the above types of memory.

[0117] When one or more programs in the storage medium can be executed by one or more processors to implement the above-mentioned method for predicting the diffusion range of carbon dioxide leak gas clouds executed on the computer device side.

[0118] The processor is used to execute a prediction program for the diffusion range of a carbon dioxide leak cloud stored in memory, to implement the following steps of a method for predicting the diffusion range of a carbon dioxide leak cloud executed on the computer device side:

[0119] A multiphase flow model for carbon dioxide leakage and diffusion at a carbon dioxide station is established; simulations of the multiphase flow model under different conditions are performed to determine the characteristic data of carbon dioxide diffusion and leakage range; the characteristic data of carbon dioxide diffusion and leakage range are fitted to obtain an empirical formula for carbon dioxide leakage and diffusion at a carbon dioxide station; based on the empirical formula for carbon dioxide leakage and diffusion at a carbon dioxide station, the diffusion range of the carbon dioxide leak gas cloud at the target carbon dioxide station where a carbon dioxide leak has occurred is predicted.

[0120] In one possible implementation, a geometric model of the carbon dioxide station is established based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment within the target carbon dioxide station; a multiphase flow model of carbon dioxide station leakage diffusion is then established based on the carbon dioxide station geometric model and the location of the carbon dioxide leak.

[0121] In one possible implementation, a preset safe carbon dioxide concentration threshold is used as the research object, and the multiphase flow model of carbon dioxide leakage and diffusion at the carbon dioxide station is simulated under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The different conditions include at least leakage amount, wind speed, leakage direction and ambient temperature.

[0122] In one possible implementation, based on the carbon dioxide diffusion and leakage range characteristic data, it is determined that the diffusion range of the carbon dioxide leaking gas cloud exhibits different correlations with the carbon dioxide diffusion and leakage range characteristic data; based on the correlations exhibited between the carbon dioxide leaking gas cloud diffusion range and the carbon dioxide diffusion and leakage range characteristic data, a target carbon dioxide leakage range data is determined; based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide gas cloud as the dependent variable and the carbon dioxide diffusion and leakage range characteristic data as the independent variable, the Cftool tool in Matlab is used to fit the data, thereby obtaining an empirical formula for carbon dioxide station leakage and diffusion corresponding to the target carbon dioxide leakage range data.

[0123] In one possible implementation, the carbon dioxide leakage amount of the target carbon dioxide station is obtained; an empirical formula for leakage diffusion of the target carbon dioxide station is determined based on the carbon dioxide leakage amount; the current wind speed is determined based on the current meteorological conditions; and the carbon dioxide leakage amount and the current wind speed are substituted into the empirical formula for leakage diffusion of the target carbon dioxide station to obtain the diffusion range of the carbon dioxide leakage cloud.

[0124] In one possible implementation, the diffusion range of the carbon dioxide leak cloud is compared with the results of numerical simulation to obtain an error rate; the validity of the empirical formula for carbon dioxide station leakage diffusion is then determined based on the error rate.

[0125] In one possible implementation, an accident rescue plan is developed based on the predicted diffusion range of the carbon dioxide leak cloud.

[0126] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0127] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0128] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting the diffusion range of a carbon dioxide leak cloud, characterized in that, include: Establish a multiphase flow model for leakage and diffusion at carbon dioxide stations; Simulations were performed on the multiphase flow model of carbon dioxide leakage and diffusion at the carbon dioxide station under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. By fitting the data on the characteristics of carbon dioxide diffusion and leakage range, an empirical formula for carbon dioxide leakage and diffusion at carbon dioxide stations is obtained. Based on the empirical formula for carbon dioxide station leakage diffusion, the diffusion range of the carbon dioxide leak gas cloud at the target carbon dioxide station where a carbon dioxide leak has occurred is predicted.

2. The method according to claim 1, characterized in that, The establishment of the multiphase flow model for carbon dioxide station leakage and diffusion includes: Based on the geometric parameters of the equipment, the equipment spacing, and the surrounding environment within the target carbon dioxide station, a geometric model of the carbon dioxide station is established. A multiphase flow model for carbon dioxide leakage diffusion was established based on the aforementioned carbon dioxide station geometric model and the location of carbon dioxide leakage.

3. The method according to claim 2, characterized in that, The simulation of the carbon dioxide leakage and diffusion multiphase flow model at the carbon dioxide station under different conditions, to determine the characteristic data of the carbon dioxide diffusion and leakage range, includes: Using a preset safe carbon dioxide concentration threshold as the research object, the multiphase flow model of carbon dioxide station leakage and diffusion is simulated under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The different conditions include at least leakage amount, wind speed, leakage direction and ambient temperature.

4. The method according to claim 3, characterized in that, The process of fitting the data on the characteristics of the carbon dioxide diffusion and leakage range to obtain an empirical formula for carbon dioxide station leakage and diffusion includes: Based on the carbon dioxide diffusion and leakage range characteristic data, it was determined that the diffusion range of the carbon dioxide leaked gas cloud and the carbon dioxide diffusion and leakage range characteristic data showed different correlations. The target carbon dioxide leakage range data is determined based on the correlation between the diffusion range of the carbon dioxide leak gas cloud and the characteristic data of the carbon dioxide diffusion and leakage range. Based on the target carbon dioxide leakage range data, with the farthest diffusion distance of the carbon dioxide cloud as the dependent variable and the characteristics of the carbon dioxide diffusion and leakage range as the independent variable, the Cftool tool in Matlab was used to fit the data, and the empirical formula for carbon dioxide leakage and diffusion at the station corresponding to the target carbon dioxide leakage range data was obtained.

5. The method according to claim 4, characterized in that, The prediction of the carbon dioxide leak cloud diffusion range of the target carbon dioxide station currently experiencing a carbon dioxide leak, based on the empirical formula for carbon dioxide station leak diffusion, includes: Obtain the amount of carbon dioxide leakage at the target carbon dioxide station; An empirical formula for determining the leakage and diffusion of target carbon dioxide stations based on the aforementioned carbon dioxide leakage amount; Determine the current wind speed based on the current weather conditions; By substituting the carbon dioxide leakage amount and the current wind speed into the empirical formula for leakage diffusion at the target carbon dioxide station, the diffusion range of the carbon dioxide leakage cloud can be obtained.

6. The method according to claim 5, characterized in that, The method further includes: The error rate was obtained by comparing the diffusion range of the carbon dioxide leak gas cloud with the results of numerical simulation calculations. The validity of the empirical formula for carbon dioxide station leakage and diffusion is determined based on the error rate.

7. The method according to claim 1, characterized in that, The method further includes: Accident rescue plans are developed based on the predicted diffusion range of the carbon dioxide leak cloud.

8. A device for predicting the diffusion range of a carbon dioxide leak cloud, characterized in that, include: A module was established to create a multiphase flow model for leakage and diffusion at a carbon dioxide station. The determination module is used to simulate the multiphase flow model of carbon dioxide leakage and diffusion under different conditions to determine the characteristic data of carbon dioxide diffusion and leakage range. The fitting module is used to fit the carbon dioxide diffusion and leakage range characteristic data to obtain the empirical formula for carbon dioxide station leakage and diffusion. The prediction module is used to predict the diffusion range of the carbon dioxide leak cloud at the target carbon dioxide station where a carbon dioxide leak has occurred, based on the empirical formula for carbon dioxide station leakage diffusion.

9. A computer device, characterized in that, include: A processor and a memory, the processor being configured to execute a prediction program for the diffusion range of a carbon dioxide leak cloud stored in the memory, to implement the prediction method for the diffusion range of a carbon dioxide leak cloud according to any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the method for predicting the diffusion range of carbon dioxide leak gas clouds according to any one of claims 1 to 7.

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