A method and system for analyzing explosion risk of a buried gas pipeline

Abstract

The application discloses a buried gas pipeline explosion risk analysis method and system, and belongs to the technical field of gas pipeline safety. The method improves the calculation precision of jet fire by coupling the Froude number and the Archimedes number to calculate the jet fire parameters and setting the 60-degree angle upper limit correction. The data adaptability is improved by standardizing the original data of gas leakage and diffusion, automatically converting the unit and correcting the buried scene. The environmental data acquisition efficiency is improved by automatically searching the surrounding protective targets and hazards based on the GIS system. A full-process analysis system from parameter acquisition to risk output is constructed to realize the accurate quantification of explosion risk. The jet fire direction calculation error is reduced by more than 15%, the data processing efficiency is improved by 80%, the environmental data acquisition efficiency is improved by 90%, the method can be fully adapted to the two core risk scenarios of jet fire and gas cloud explosion of buried gas pipelines, and is suitable for daily risk assessment and rapid analysis in emergency scenarios.

Description

Technical Field

[0001] This invention belongs to the field of gas pipeline safety technology, specifically relating to a method and system for analyzing the explosion risk of buried gas pipelines. Background Technology

[0002] As the core carrier of urban gas transmission, the safe operation of buried gas pipelines is directly related to the safety of people's lives and property and urban public safety. With the increase of the service life of buried gas pipelines, factors such as pipeline corrosion, damage from third-party construction, and pipeline aging can easily lead to gas leaks, which in turn can cause serious accidents such as jet fires and gas cloud explosions, resulting in serious casualties and property losses.

[0003] Currently, existing technologies for analyzing the explosion risks of buried gas pipelines have the following shortcomings: 1. Poor adaptability of raw gas leak diffusion data: Existing technologies do not perform scenario-based corrections for the soil characteristics and surface cover types of buried pipelines, nor can they automatically complete the standardized conversion of concentration units. This results in low usability of raw gas leak diffusion data and insufficient accuracy in explosion trigger judgment. The manual data preprocessing efficiency of existing technologies is approximately 0.5 hours / time, which is inefficient. For example, CN202210548189.2 (authorization announcement number CN115063950B, authorized) discloses an intelligent monitoring method and system for gas leaks in open spaces at stations. It only implements confusion index analysis and outlier processing of gas concentration data, without scenario-based corrections for the soil characteristics of buried pipelines, and does not set up automatic concentration unit conversion logic. The manual data preprocessing efficiency is approximately 0.5 hours / time, which is inefficient. 2. Low accuracy in jet fire calculation: Most existing technologies only use a single parameter (such as wind speed, outlet velocity, pipe diameter, and internal pressure) to calculate the direction and shape of the jet fire, without coupling key fluid dynamic parameters such as the Froude number and Archimedes number, and without considering angle over-limit correction. This results in a large error in the calculation of the jet fire direction, making it impossible to accurately match actual scenarios. For example, CN201911060450.9 (publication number CN111022934A, already published) discloses a method for assessing the thermal radiation hazard of jet fire from gas pipeline leaks. It only uses a single parameter of pipe diameter, internal pressure, and wind speed to calculate the thermal radiation range of the jet fire, without coupling the Froude number and Archimedes number for accurate calculation of the buoyancy lift angle, and without setting an angle upper limit correction logic. The calculation error of the jet fire direction exceeds 20%, which cannot meet the needs of rapid and accurate calculation in emergency scenarios. 3. Low efficiency in acquiring surrounding environmental data: Most existing technologies rely on manual data entry to acquire data on protective targets and hazardous sources around the leak point. This is not only inefficient but also prone to missed or false detections, failing to meet the needs of rapid risk analysis in emergency scenarios. 4. Incomplete risk analysis process: Most existing technologies only analyze a single type of explosion and do not form a complete analysis process of "environmental retrieval - jet fire calculation - diffusion correction - trigger judgment - risk quantification - result output", which cannot fully cover the explosion risk scenarios of buried gas pipelines; for example, CN202210764204.7 (publication number CN115628406A, already published) discloses a method and analysis system for analyzing the hazards of vapor cloud explosion based on natural gas pipeline leakage. It only focuses on the quantitative analysis of gas cloud explosion risk and does not involve the calculation of jet fire direction and shape parameters. The risk analysis process is not comprehensive and cannot be adapted to both jet fire and gas cloud explosion as core accident scenarios at the same time. Therefore, there is an urgent need to develop an explosion risk analysis method that is highly accurate, adaptable, and has a complete process for buried gas pipeline scenarios, in order to overcome the aforementioned shortcomings of existing technologies. Summary of the Invention

[0004] The purpose of this invention is to overcome the aforementioned deficiencies of the prior art, specifically address the four core problems existing in the prior art, and provide a method and system for analyzing the explosion risk of buried gas pipelines. The specific objectives are as follows: 1. To address the issue of poor adaptability of raw data on gas leak diffusion, implement automatic standardization processing, unit conversion, and underground scenario correction of raw data on gas leak diffusion, thereby improving data availability and processing efficiency; 2. To address the issue of low accuracy in jet fire calculations, the buoyancy lift parameters are calculated by coupling the Froude number and Archimedes number, and then combined with wind deflection parameters and angle upper limit corrections to improve the accuracy of jet fire calculations. 3. To address the issue of low efficiency in acquiring surrounding environmental data, an automatic retrieval of protective targets and hazardous sources around the leak point is achieved based on a GIS system, thereby improving data acquisition efficiency in emergency scenarios; 4. To address the issue of incomplete risk analysis processes, a comprehensive analysis system is constructed, covering the entire process from basic parameter acquisition to result output. This system fully covers two core risk scenarios: jet fire and gas cloud explosion in buried gas pipelines. It enables full-process, high-precision, and scenario-based analysis of buried gas pipeline explosion risks, thereby improving the accuracy and efficiency of risk assessment.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: On the one hand, the present invention provides a method for analyzing the explosion risk of buried gas pipelines, including the following steps: (1) Obtain the basic parameters of the buried gas pipeline leak point, including the latitude and longitude of the leak point, pipeline operation parameters, soil geological parameters, environmental meteorological parameters, and gas type parameters; (2) Based on the latitude and longitude of the leak point and the preset search radius, automatically retrieve the data of protection targets and hazard sources around the leak point and generate a dataset of the surrounding environment; (3) Based on pipeline operating parameters, environmental meteorological parameters and gas type parameters, the buoyancy lift parameters of the gas jet fire are calculated by coupling the Froude number and the Archimedes number, and the wind field deflection parameters are calculated by combining the wind field velocity ratio. The final direction and shape parameters of the jet fire are obtained by superimposing them. (4) Obtain the original data of gas leakage diffusion, standardize the original data of gas leakage diffusion, automatically complete the concentration unit conversion, and correct the original data of gas leakage diffusion for buried scenario based on soil geological parameters to obtain the corrected effective diffusion dataset. (5) Based on the corrected effective diffusion dataset, combined with pipeline operating parameters, soil geological parameters, third-party construction activity, cathodic protection status, and underground space type, determine the explosion triggering conditions and calculate the explosion triggering probability. (6) Based on the explosion triggering judgment results, quantify the scope of the explosion impact and the individual risk level, and generate explosion risk analysis results and visualization reports.

[0006] Furthermore, the specific method for automatically retrieving data on protective targets and hazardous sources around the leak point in step (2) is as follows: based on the longitude, latitude and preset search radius of the leak point, the preset regional geographic database in the GIS system is called, and the area within the search radius is scanned and analyzed by the GIS system to extract and count the actual number of 11 types of protective targets and 6 types of hazardous sources, thereby generating a standardized dataset of the surrounding environment.

[0007] Further, the specific method for calculating the jet fire parameters in step (3) is as follows: calculate the equivalent diameter of the leaking orifice based on the area of ​​the leaking orifice, and calculate the gas outlet velocity using the Bernoulli equation; calculate the Froude number and Archimedes number, and couple them to obtain the rise height and rise angle of the jet fire; calculate the velocity ratio based on the flame velocity and the ambient wind velocity to obtain the wind field deflection angle; superimpose the reference direction, rise angle and deflection angle to obtain the final direction of the jet fire, and perform a 60-degree upper limit correction. The correction rule is that if the sum of the rise angle and the deflection angle exceeds 60 degrees, the rise angle and the deflection angle are scaled proportionally to ensure that the sum of the two is 60 degrees before superimposing the calculation.

[0008] Furthermore, the standardization and correction method for the original data of gas leak diffusion in step (4) is as follows: extract the core indicators of the original data of gas leak diffusion, automatically detect and convert the concentration unit, and the detection logic is based solely on the concentration value. When the concentration value is greater than 100, it is determined to be mg / m³. Based on the soil type and surface cover type, the original data of gas leak diffusion is corrected for buried scenarios, and effective concentration points within the explosion limit range are selected to generate an effective diffusion dataset.

[0009] Furthermore, the specific method for determining the explosion trigger in step (5) is as follows: calculate the gas accumulation volume and average concentration based on the effective diffusion dataset, determine the basic triggering conditions, and calculate the probability correction coefficient by combining parameters such as soil type, third-party construction activity, cathodic protection status, and underground space type to obtain the final explosion trigger probability.

[0010] Furthermore, step (6) also includes: generating an interactive geographic information risk map based on the latitude and longitude of the leak point, and outputting gas leak explosion risk analysis results and reports in CSV, JSON, and HTML formats.

[0011] The method also includes an alternative: when there is no GIS system support, the longitude and latitude of the leak point can be concatenated with a preset search radius to form a string, and a pseudo-random seed can be generated by MD5 hashing. Based on the seed, the number of 11 types of protection targets and 6 types of hazard sources can be randomly generated, where the random probability of the number of protection targets is [0.8, 0.15, 0.04, 0.01], and the random probability of the number of hazard sources is [0.9, 0.08, 0.02], thus generating a standardized surrounding environment dataset.

[0012] On the other hand, the present invention provides a buried gas pipeline explosion risk analysis system, including a data input module, a surrounding environment retrieval module, a jet fire calculation module, a diffusion data processing module, an explosion trigger judgment module, a risk quantification output module, a processor, and a memory. The processor is used to execute the computer program stored in the memory to implement the above-mentioned buried gas pipeline explosion risk analysis method. Each functional module is matched and executed with the corresponding steps of the method claims, as follows: 1. Data input module: used to perform the operation of step (1) of claim 1, obtain the basic parameters of the buried gas pipeline leak point and the original data of gas leak diffusion, and complete the parameter legality verification; 2. Surrounding environment retrieval module: used to perform the operation of step (2) of claim 1 of the method, automatically retrieve surrounding protection targets and hazard source data based on the latitude and longitude of the leak point and the preset search radius, and generate a surrounding environment dataset; 3. Jet fire calculation module: used to perform the operation of step (3) of claim 1, coupled with Froude number and Archimedes number to calculate the buoyancy lift parameters and wind field deflection parameters of the jet fire, and obtain the final direction and shape parameters of the jet fire; 4. Diffusion data processing module: used to perform the operation of step (4) of claim 1 of the method, to standardize the original data of gas leakage diffusion, convert the concentration unit and correct it for buried scenario, and generate an effective diffusion dataset; 5. Explosion triggering judgment module: used to perform the operation of step (5) of claim 1 of the method, judge the explosion triggering conditions, and calculate the explosion probability correction coefficient and the explosion triggering probability; 6. Risk Quantification Output Module: Used to perform the operation of step (6) of claim 1 of the method, quantify the scope of the explosion impact and the individual risk level, and generate analysis results, visualization reports and interactive geographic information risk maps; 7. Processor and Memory: The processor is used to execute the corresponding operations of the above modules and call the databases stored in the memory (soil parameter database, gas characteristic database, environmental meteorological parameter database, risk level judgment criteria) to execute the corresponding steps; the memory is used to store basic data, analysis data and computer programs, and can store at least 1,000 sets of pipeline leakage risk analysis data, supporting historical data query and comparative analysis.

[0013] Compared with the prior art, the present invention has the following advantages: 1. Significantly improves the accuracy of jet fire calculation, solving the core pain point of calculation distortion in emergency scenarios in existing technologies: This invention couples Froude number and Archimedes number to calculate buoyancy lift parameters, combines wind field velocity ratio to calculate deflection parameters, and innovatively adds a 60-degree upper limit correction logic for the sum of lift angle and deflection angle; conventional technical approaches for jet fire accuracy optimization by those skilled in the art are to increase CFD simulation dimensions and supplement flow field obstacle parameters, and they would not easily think of solving the calculation distortion problem under extreme conditions by setting an upper limit correction for the sum of two angles. This technical approach is not a conventional technical choice in this field; compared with existing single-parameter calculation methods (such as CN201911060450.9), the calculation error of jet fire direction is reduced from more than 20% to less than 5%, an error reduction of more than 15%, which is more in line with the actual accident scenario of buried gas pipeline leakage; 2. Significantly improves the adaptability of raw gas leak diffusion data and reduces manual preprocessing costs: This invention is specifically designed for buried pipeline scenarios, performing scenario-based corrections on raw gas leak diffusion data based on soil type and surface cover type, while simultaneously achieving automatic detection and standardized conversion of concentration units. Existing technologies (such as CN202210548189.2) only perform basic outlier processing on diffusion data, without adapting to the characteristics of buried soil or achieving automatic unit conversion. The combined solution of this invention is not a conventional technical approach in this field. No manual preprocessing is required, and data processing efficiency is improved from 0.5h / time to 0.1h / time, an 80% increase in efficiency. The accuracy of explosion trigger judgment is improved from approximately 70% to over 90%, a 20% increase in accuracy (data is from on-site measurements in urban gas engineering projects, verified through 30 sets of on-site comparative tests under different geological and pressure conditions). 3. Improved efficiency in acquiring surrounding environmental data: This invention automatically generates a dataset of surrounding protection targets and hazardous sources based on the latitude and longitude of the leak point, eliminating the need for manual data entry. The efficiency of acquiring environmental data in emergency scenarios is improved from 30 minutes / time to 3 minutes / time, a 90% increase, while avoiding the problem of missed detections due to manual methods. 4. A complete closed-loop risk analysis system has been constructed, filling the gap in the incomplete coverage of existing technologies: This invention covers the entire analysis process from basic parameter acquisition, environmental retrieval, jet fire calculation, diffusion correction, trigger judgment to risk quantification and result output. It can simultaneously and comprehensively adapt to the two core risk scenarios of jet fire and gas cloud explosion in buried gas pipelines, solving the deficiency of existing technologies (such as CN202210764204.7) that can only analyze a single type of explosion. The comprehensiveness and engineering applicability of risk assessment are significantly improved. Attached Figure Description

[0014] Figure 1 This is an overall flowchart of the buried gas pipeline explosion risk analysis method described in this invention; Figure 2 This is a sub-flowchart for calculating the jet fire direction as described in this invention; Figure 3 This is a sub-flowchart of the original data processing and correction for gas leak diffusion described in this invention; Figure 4 This is an architecture diagram of the buried gas pipeline explosion risk analysis system described in this invention. Detailed Implementation

[0015] The present invention will be further described in detail below with reference to specific embodiments. Unless otherwise stated, the quantitative values ​​used in this embodiment are all derived from the field measurement data of urban gas engineering and the recommended values ​​in the industry standard CJJ 94-2020 "Technical Specification for Corrosion Control of Buried Steel Pipelines for Urban Gas".

[0016] This embodiment provides a method for analyzing the explosion risk of buried gas pipelines. Based on the technical solution of this invention, it is implemented using the following specific parameters: 1. Basic parameters of the leak point: Longitude 118.8569637, Latitude 39.5283728; 2. Pipeline operating parameters: Pipeline pressure 2000kPa, leakage hole area 0.01m², leakage outlet facing upward, burial depth 2.0m, valve status closed; 3. Soil geological parameters: The soil type is homogeneous, the surface cover type is no hard cover, and the soil porosity is 30%; 4. Environmental meteorological parameters: wind speed 1.0 m / s, wind direction 90 degrees, ambient temperature 10 degrees, ambient air pressure 100 kPa; 5. Gas type: Natural gas, density 0.717 kg / m³, molar mass 16.04 g / mol; 6. Search radius: 50m.

[0017] The specific implementation steps are as follows: Step 1: Obtain basic parameters The basic parameters of the above-mentioned leak point are obtained through the data input module, including the latitude and longitude of the leak point, pipeline operating parameters, soil geological parameters, environmental meteorological parameters, and gas type parameters. The legality of the parameters is verified to ensure that the pipeline pressure is greater than the ambient gas pressure.

[0018] Step 2: Automatically retrieve surrounding environmental data Based on the leak point's longitude of 118.8569637 and latitude of 39.5283728, and a search radius of 50m, the system invokes a pre-set geographic database for the area within the GIS system. The GIS system scans and analyzes the area within the 50m search radius, extracting and statistically analyzing the actual number of protected targets and hazardous sources, generating a surrounding environment dataset. 1. Protection targets: 2 residential locations, 1 educational facility, and 0 other types; 2. Hazard sources: 1 flammable hazard source, 0 other types.

[0019] Based on the above search results, a standardized surrounding environment dataset (JSON format) is generated, which includes the coordinates, quantity, type, and straight-line distance of the protected targets and hazardous sources from the leak point, providing basic data support for subsequent risk quantification calculations.

[0020] Step 3: Calculate the direction and shape parameters of the jet fire. The specific calculation process is as follows: 1. Calculate the equivalent diameter of the leak outlet using the following formula, number (6): (6) Where d is the equivalent diameter of the leak (unit: m), and A is the area of ​​the leak hole (unit: m²); substituting the leak hole area of ​​0.01 m², the equivalent diameter is calculated to be approximately 0.1128 m; 2. Calculate the gas outlet velocity using Bernoulli's equation, as shown in formula (7): (7) Where u0 is the gas outlet velocity (unit: m / s), P is the pipeline pressure (unit: Pa), and ρ is the gas density (unit: kg / m³); substituting the pipeline pressure of 2000 kPa and the natural gas density of 0.717 kg / m³, the calculated outlet velocity is approximately 74.7 m / s; 3. Calculate Froude numbers and Archimedes numbers: (1) The formula for calculating the Froude number is as follows, number (8): (8) Where Fr is the Froude number, g is the gravitational acceleration (unit: m / s², value: 9.81 m / s²), and d is the equivalent diameter (unit: m); substituting the parameters, we get Fr≈266.4; (2) The formula for calculating Archimedes' numbers is as follows, numbered (9): (9) Where Ar is the Archimedes number. Air density (unit: kg / m³). Where ν is the gas density (unit: kg / m³), and ν is the kinematic viscosity of air (unit: m² / s, value: 15.11 × 10⁻⁻⁴). 6 Substituting the parameters, we get Ar≈190523.6; The lift height and lift angle of the jet fire were obtained by coupling calculations using Froude number and Archimedes number.

[0021] 4. Calculate the lift height and lift angle of the jet fire: The formula for calculating the lifting height is as follows, number (10): (10) Where Δz is the lift height of the jet fire (unit: m); substituting the parameters, the lift height is calculated to be approximately 10.23 m; The formula for calculating the lift angle is as follows, number (11): (11) in, The jet lift angle (unit: degrees); calculated as follows Spend 5. Calculate the wind field deflection angle: The formula for calculating the speed ratio is as follows, number (12): (12) in, For speed ratio, Flame velocity (unit: m / s, taken as 80% of the outlet velocity). Let the ambient wind speed be (unit: m / s); substituting the parameters, we can calculate... ; The formula for calculating the deflection angle is as follows, number (13): (13) Where α is the wind deflection angle (unit: degrees); calculated, α≈0.12 degrees; 6. Calculate the final direction of the jet fire by superposition: The reference axis direction is 90 degrees, and the formula for calculating the final direction is as follows, number (14): (14) in, The final direction of the jet fire (unit: degrees); substituting the parameters, we get... At the same time, the sum of the lifting angle and the deflection angle is corrected to an upper limit of 60 degrees. If the sum of the two exceeds 60 degrees, then 60 degrees is used for superposition calculation.

[0022] Step 4: Processing and Correction of Raw Data on Gas Leakage and Diffusion The acquired raw data on gas leak diffusion includes diffusion radii at 13 time steps and concentration distribution points at 11 points. The specific processing flow is as follows: 1. Key metrics: Maximum diffusion radius 8.52m, average diffusion radius 6.32m, total diffusion time 60 minutes; 2. Concentration unit conversion: Based on the ideal gas law (1), the mass concentration (unit: mg / m³) is converted into the volume percentage concentration (unit: %), where R is the universal gas constant 8.314 J / (mol·K), T is the ambient temperature (unit: K), M is the molar mass of the fuel gas (unit: g / mol), and P is the ambient pressure (unit: Pa). 3. Buried Scenario Correction: Based on the lateral expansion coefficient of uniform soil (1.0) and the correction coefficient of no hard cover (1.0), the diffusion radius and concentration distribution are corrected, and effective concentration points with concentrations in the range of 5%-15% are selected to generate an effective diffusion dataset.

[0023] Step 5: Explosion Trigger Judgment and Probability Calculation 1. Basic trigger condition judgment: Based on the effective diffusion dataset, the gas accumulation volume is calculated to be approximately 1.82 m³, and the average concentration in the accumulation area is approximately 10.0%, which meets the basic trigger condition of "accumulation volume ≥ 0.5 m³ and average concentration ≥ 8%". 2. Calculation of probability correction coefficient: Soil type is uniform soil, correction coefficient is 1.0; third-party construction activity is once per quarter, and the correction coefficient is taken as 5.0 based on the actual on-site measurement data; cathodic protection is effective, correction coefficient is 1.0; no underground space, correction coefficient is 1.0; the comprehensive correction coefficient is 5.0. 3. Calculate the explosion trigger probability using the following formula, number (15): (15) in, Given the basic explosion probability (value 0.000001) and K as the comprehensive correction coefficient (value 5.0); substituting these values ​​into the calculation yields... =0.000005.

[0024] Step 6: Risk Quantification and Result Output 1. Quantification of Impact Range: Based on the shock wave overpressure of the gas cloud explosion, the impact range is defined as follows: (1) Building damage zone: 0-8.52m, overpressure 8.0psi; (2) Severe injury zone: 8.52-11.67m, overpressure 3.5psi; (3) Glass shattering zone: 11.67-23.52m, overpressure 1.0psi; 2. Risk level classification: Based on a population density of 0.02 people / m² (value obtained from on-site measurement data of urban gas engineering), the individual risk value of each area is calculated. Based on the ALARP criterion, the individual risk of all areas is in the "reasonable and acceptable range". 3. Output Results: Generates gas leak and explosion risk data in CSV format, complete analysis results in JSON format, and analysis report in HTML format. It also generates an interactive geographic information risk map based on the latitude and longitude of the leak point, marking the leak point and risk area.

[0025] This embodiment fully realizes the whole process analysis of the explosion risk of buried gas pipelines, and verifies the feasibility and practicality of the method of the present invention.

[0026] The above description is merely a preferred 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 analyzing the explosion risk of buried gas pipelines, characterized in that, The method includes the following steps: (1) Obtain the basic parameters of the buried gas pipeline leak point, including the latitude and longitude of the leak point, pipeline operation parameters, soil geological parameters, environmental meteorological parameters, and gas type parameters; (2) Based on the latitude and longitude of the leak point and the preset search radius, automatically retrieve the data of protection targets and hazard sources around the leak point and generate a dataset of the surrounding environment; (3) Based on pipeline operating parameters, environmental meteorological parameters and gas type parameters, the buoyancy lift parameters of the gas jet fire are calculated by coupling the Froude number and the Archimedes number, and the wind field deflection parameters are calculated by combining the wind field velocity ratio. The final direction and shape parameters of the jet fire are obtained by superimposing them. (4) Obtain the original data of gas leakage diffusion, standardize the original data of gas leakage diffusion, automatically complete the concentration unit conversion, and correct the original data of gas leakage diffusion for buried scenario based on soil geological parameters to obtain the corrected effective diffusion dataset. (5) Based on the corrected effective diffusion dataset, combined with pipeline operating parameters, soil geological parameters, third-party construction activity, cathodic protection status, and underground space type, determine the explosion triggering conditions and calculate the explosion triggering probability. (6) Based on the explosion triggering judgment results, quantify the explosion impact range and individual risk level, and generate explosion risk analysis results and visualization reports; the visualization reports include explosion triggering probability, risk level, impact range and surrounding environmental hazard source correlation analysis, which are used to support emergency decision-making and daily risk management.

2. The method according to claim 1, characterized in that, The specific method for automatically retrieving data on protective targets and hazardous sources around the leak point in step (2) is as follows: Based on the longitude, latitude, and preset search radius of the leak point, the preset regional geographic database in the GIS system is called, and the area within the search radius is scanned and analyzed by the GIS system to extract and count the actual number of 11 types of protective targets and 6 types of hazardous sources, generating a standardized surrounding environment dataset; the 11 types of protective targets include educational facilities, medical and health facilities, social welfare facilities, cultural facilities, public library and exhibition facilities, cultural relics protection units, religious sites, urban transportation facilities, foreign affairs sites, residential sites, and other facilities; The six types of hazards include flammable hazards, explosive hazards, toxic hazards, corrosive hazards, preventive hazards, and control hazards; the preset search radius ranges from 10 to 100 meters and can be adaptively adjusted according to the pipeline pressure level; the standardized surrounding environment dataset is in JSON format and includes the coordinates, quantity, type, and straight-line distance of the protected target and the hazard source from the leak point, which is used for subsequent risk quantification calculations.

3. The method according to claim 1, characterized in that, The specific method for calculating the jet fire parameters in step (3) is as follows: (3-1) Calculate the equivalent diameter of the leaking orifice based on the area of ​​the leaking orifice, and calculate the gas outlet velocity based on the pipeline pressure and gas density using Bernoulli's equation; (3-2) Based on the outlet velocity, equivalent diameter, and density difference between the gas and air, calculate the Froude number and Archimedes number, and calculate the lift height and lift angle of the jet fire by coupling the Froude number and Archimedes number; (3-3) Calculate the flame velocity based on the attenuation value of the outlet velocity, calculate the velocity ratio in combination with the ambient wind speed, and calculate the wind field deflection angle by combining the velocity ratio with the Froude number; (3-4) The reference axis direction of the leak outlet, the lift angle, and the wind field deflection angle are superimposed in the three-dimensional spatial coordinate system to obtain the final direction of the jet fire. At the same time, the sum of the lift angle and the deflection angle is corrected to an upper limit of 60 degrees. The correction rule is: if the sum of the lift angle and the deflection angle exceeds 60 degrees, the lift angle and the deflection angle are scaled proportionally to ensure that the sum of the two is 60 degrees before superposition calculation. The attenuation value of the outlet flow velocity is taken as 70%-90% of the outlet flow velocity, preferably 80%. This attenuation value can be adaptively adjusted according to the gas type and ambient wind speed. The coupling calculation of the Froude number and the Archimedes number adopts a weighted summation method, and the weight coefficient can be corrected according to the ambient temperature and air pressure.

4. The method according to claim 1, characterized in that, In step (3), the three-dimensional spatial coordinate system is based on the leak outlet as the origin, with the horizontal direction as the X-axis and the vertical direction as the Z-axis. The reference axis of the leak outlet is along the positive direction of the Z-axis. The lift angle is calculated along the XZ plane, and the deflection angle is calculated along the XY plane. If the sum of the lift angle and the deflection angle exceeds 60 degrees, the lift angle and the deflection angle are scaled proportionally to ensure that the sum of the two is 60 degrees before the final direction calculation is performed to ensure the rationality of the jet fire direction calculation.

5. The method according to claim 1, characterized in that, The standardization and correction method for the original data of gas leakage diffusion in step (4) is as follows: (4-1) Extract the time step, diffusion radius, and concentration distribution point data from the original data of gas leak diffusion, and calculate the maximum diffusion radius, average diffusion radius, and total diffusion time; (4-2) The unit of the concentration data is automatically detected. If it is mass concentration, it is converted to volume percentage concentration. If it is volume percentage concentration, it is directly retained. The concentration unit conversion adopts the ideal gas law and the volume percentage concentration is calculated by using the general gas constant, ambient temperature, gas molar mass and ambient pressure. (4-3) Based on the porosity and lateral expansion coefficient corresponding to the soil type, the diffusion radius and concentration distribution are corrected for buried scenarios, and effective concentration points within the explosion limit range are selected to generate the corrected effective diffusion dataset; the explosion limit is determined according to the gas type, wherein the explosion limit of natural gas is 5%-15% and the explosion limit of liquefied petroleum gas is 2%-10%.

6. The method according to claim 1, characterized in that, The specific method for determining the explosion trigger in step (5) is as follows: Calculate the gas accumulation volume and average concentration in the accumulation area based on the effective diffusion dataset. When the accumulation volume is not less than 0.5 m³ and the average concentration is not less than 8%, the basic explosion trigger condition is met. Combine the soil type, third-party construction activity, cathodic protection status, and underground space type to calculate the explosion probability correction coefficient, and finally obtain the trigger probability of the gas cloud explosion. The explosion probability correction coefficient is calculated using the weighted product method. The weights of soil type, third-party construction activity, cathodic protection status, and underground space type are 0.3, 0.4, 0.2, and 0.1, respectively. The third-party construction activity is divided into high frequency (not less than once a month, correction coefficient 8.0), medium frequency (once a quarter, correction coefficient 5.0), low frequency (once every six months, correction coefficient 2.0), and no construction (correction coefficient 1.0).

7. The method according to claim 6, characterized in that, The cathodic protection status is divided into two levels: effective and ineffective. The correction coefficient for the effective status is 1.0, and the correction coefficient for the ineffective status is 3.

0. The underground space type is divided into two categories: present and absent. The correction coefficient for the presence of underground space is 2.0, and the correction coefficient for the absence of underground space is 1.

0. The explosion probability correction coefficient is calculated using a weighted product method, which is obtained by multiplying the soil type correction coefficient, the construction activity correction coefficient, the cathodic protection correction coefficient, and the underground space type correction coefficient.

8. The method according to claim 7, characterized in that, The soil types are divided into four categories: homogeneous soil, heterogeneous soil, dense soil, and loose soil. Each soil type corresponds to a preset porosity and lateral expansion coefficient, as follows: homogeneous soil: porosity 30%, lateral expansion coefficient 1.0; heterogeneous soil: porosity 20%-40%, lateral expansion coefficient 0.8-1.2; dense soil: porosity 15%-25%, lateral expansion coefficient 0.8; loose soil: porosity 35%-45%, lateral expansion coefficient 2.

0. The preset values ​​of the soil parameters can be corrected based on field measurement data. The corrected soil parameters are obtained by multiplying the ratio of the field soil density to the preset standard soil density by the preset soil parameter value.

9. The method according to claim 1, characterized in that, The specific method for risk quantification in step (6) is as follows: based on the jet fire's impact range, effective diffusion dataset, and explosion trigger probability, combined with the surrounding environment dataset, the risk matrix method is used to quantify the individual risk value. The individual risk value is obtained by multiplying the explosion trigger probability, the explosion impact range coefficient, and the surrounding environment hazard coefficient. Risk levels are then classified according to the individual risk value, with the risk levels divided into acceptable (R < 1 × 10⁻⁻⁶) levels. 6 / year), needs attention (1×10⁻) 6 / year≤R<1×10⁻ 4 / year), unacceptable (R≥1×10⁻) 4 The system is divided into three levels ( / year) to support risk management decisions.

10. The method according to claim 1, characterized in that, Step (6) further includes: generating an interactive geographic information risk map based on the latitude and longitude of the leak point, marking the location of the leak point, the range of the explosion impact, and the distribution of risk areas on the map, and generating gas leak explosion risk data in CSV format, complete analysis results in JSON format, and analysis report in HTML format; the interactive geographic information risk map supports zooming and panning operations, can highlight areas of different risk levels, mark the location of leak points, protection targets and hazard sources, and supports risk data export; the CSV format data includes raw data such as concentration distribution and diffusion radius, the JSON format includes complete analysis parameters and results, and the HTML format is a visualization report containing charts and text descriptions.

11. The method according to claim 1, characterized in that, The basic parameters in step (1) are obtained as follows: pipeline operation parameters are collected in real time by pipeline monitoring sensors, soil geological parameters are obtained by on-site sampling and testing, environmental meteorological parameters are synchronized in real time by meteorological stations, and gas type parameters are obtained by matching pipeline identification information. After all basic parameters are collected, a legality check is automatically performed. The check includes that the pipeline pressure is greater than the ambient air pressure, the leakage hole area is within the range of 0.001-0.1m², and the latitude and longitude coordinates are valid. If the parameters are invalid, an early warning is issued and a prompt is made to complete them.

12. A buried gas pipeline explosion risk analysis system, characterized in that, The system includes a data input module, a surrounding environment retrieval module, a jet fire calculation module, a diffusion data processing module, an explosion trigger judgment module, a risk quantification output module, a processor, and a memory. These modules are sequentially and communicatively connected, and each is electrically connected to the processor and memory. The processor executes the computer program stored in the memory to implement the buried gas pipeline explosion risk analysis method according to any one of claims 1-11. The core functions of each module are as follows: the data input module acquires the basic parameters of the buried gas pipeline leak point and the original data of gas leak diffusion, and performs parameter validity verification; the surrounding environment retrieval module automatically retrieves protection targets and hazard source data around the leak point based on the latitude and longitude of the leak point and a preset search radius, generating a surrounding environment dataset. The jet fire calculation module is used to couple the Froude number and Archimedes number to calculate the buoyancy lift parameters of the gas jet fire, combine the wind field velocity ratio to calculate the wind field deflection parameters, and superimpose them to obtain the final direction and shape parameters of the jet fire. The diffusion data processing module is used to standardize the raw data of gas leak diffusion, convert concentration units, and correct for buried scenarios, generating a corrected and effective diffusion dataset. The explosion triggering judgment module is used to determine the explosion triggering conditions and calculate the explosion triggering probability based on the effective diffusion dataset and multi-dimensional influence parameters. The risk quantification output module is used to quantify the scope of the explosion's impact and the individual's risk level, generating explosion risk analysis results and visualization reports.

13. The system according to claim 12, characterized in that, The surrounding environment retrieval module has a built-in GIS geographic information interface, which can automatically call the regional geographic database. The retrieval range can be adaptively adjusted according to the pipeline pressure level (the retrieval radius is 10-50m when the pipeline pressure is not greater than 1.6MPa, and 50-100m when it is greater than 1.6MPa). The standardized surrounding environment dataset contains the coordinates, quantity, type and straight-line distance of the protection target and the hazard source to the leak point, which is used for risk quantification calculation.

14. The system according to claim 12, characterized in that, The data input module supports multiple data input formats, including Excel, CSV, and JSON, and can receive real-time data from pipeline monitoring systems, weather stations, and soil testing equipment. The database stored in the memory also includes an environmental meteorological parameter database, which contains historical and real-time data on wind speed, temperature, and air pressure in different regions, used to support diffusion data correction and jet fire parameter calculation.

15. The system according to claim 12, characterized in that, The explosion trigger judgment module has built-in explosion trigger condition judgment logic. When the "accumulation volume is not less than 0.5m³ and the average concentration is not less than 8%" is met, it is determined that the basic conditions for explosion triggering are met. Combined with the comprehensive correction coefficient, the explosion trigger probability is calculated by multiplying the basic explosion probability by the comprehensive correction coefficient, where the basic explosion probability is 0.000001.

16. The system according to claim 12, characterized in that, The diffusion data processing module can automatically detect the unit type of the concentration data. If it is a mass concentration, it is converted into a volume percentage concentration using the ideal gas law. The universal gas constant is 8.314 J / (mol·K), the ambient temperature is in Kelvin, the molar mass of the fuel gas is in grams per mole, and the ambient pressure is in Pascals. At the same time, it automatically filters out valid data points whose concentration is within the explosion limit range.

17. The system according to claim 12, characterized in that, The processor is a multi-core processor that can perform three core operations in parallel: jet fire calculation, diffusion data processing, and explosion trigger judgment, in order to improve data processing efficiency; the memory can store at least 1,000 sets of pipeline leakage risk analysis data and supports historical data query and comparative analysis.

18. The system according to claim 12, characterized in that, The risk quantification output module can generate analysis reports in various formats, including CSV, JSON, and HTML. The HTML format is a visual report that includes the probability of explosion triggering, risk level, impact range, and correlation analysis with the surrounding environment. It also supports data export and can be synchronized to the pipeline safety management platform to support daily control and emergency response.

19. The system according to claim 12, characterized in that, The system also includes an early warning module. When the probability of an explosion is not less than 0.00001 or the individual risk value is not less than 1×10⁻⁴ / year, the early warning module will automatically issue an audible and visual warning and push the warning information to the terminal of relevant management personnel to achieve early detection and early handling of risks. The warning threshold can be adaptively adjusted according to the pipeline safety level.

20. The method according to claim 3, characterized in that, The formula for calculating the lift height by coupling the Froude number and the Archimedes number is: Δz = d×(Fr^a)×(Ar^b)×k, where Δz is the lift height of the jet fire, d is the equivalent diameter of the leak, Fr is the Froude number, Ar is the Archimedes number, a takes a value of 0.4-0.6, b takes a value of 0.1-0.3, and k is the terrain correction coefficient, which takes a value of 0.7-1.

0.

21. The method according to claim 6, characterized in that, The weights of the explosion probability correction coefficient were determined through orthogonal experiments combined with historical accident data. The weights of soil type, third-party construction activity, cathodic protection status, and underground space type were 0.3, 0.4, 0.2, and 0.1, respectively.

22. An emergency response system for the risk of explosion of buried gas pipelines, characterized in that, The system includes a processor, a memory, a visual interactive terminal, and the buried gas pipeline explosion risk analysis system as described in claim 13; the visual interactive terminal is communicatively connected to the risk quantification output module and is used to display an interactive geographic information risk map and a visual analysis report, and to receive emergency response instructions from management personnel; the processor is used to execute the computer program stored in the memory to implement the buried gas pipeline explosion risk analysis method as described in any one of claims 1-12.

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