An integrated design method for 3D simulation models of skid-mounted gas stations

Abstract

The present invention relates to the field of fuel safety technology, and in particular to an integrated design method for a three-dimensional simulation model of a skid-mounted gas station. The method comprises the following steps: obtaining a skid-mounted gas station structural drawing; constructing a three-dimensional component of the gas station according to the skid-mounted gas station structural drawing; performing virtual assembly based on the three-dimensional component of the gas station to generate a three-dimensional simulation model of the gas station; obtaining fuel data, and transmitting it to the three-dimensional simulation model of the gas station, and performing fuel flow simulation to generate fuel flow data; detecting oil reflux based on the fuel flow data to obtain oil reflux data; performing fuel pipeline cavitation detection based on the oil reflux data to obtain fuel pipeline cavitation data; marking the pipeline cavitation position based on the fuel pipeline cavitation data, and continuously monitoring the thermal load of the fuel pipe body at the pipeline cavitation position; and evaluating the fuel vaporization risk based on the thermal load of the fuel pipe body. The present invention improves the safety, stability and design optimization efficiency of skid-mounted gas stations based on fuel safety technology.

Description

Technical Field

[0001] The present invention relates to the field of fuel safety technology, and in particular to an integrated design method for a three-dimensional simulation model of a skid-mounted gas station. Background Art

[0002] The 3D simulation model of a skid-mounted gas station utilizes a standardized design, integrating oil storage tanks, pipelines, pumps, valves, and control devices onto a mobile skid-mounted foundation. This ensures a compact structure and facilitates transportation and installation. The oil storage and transportation system includes high-strength oil storage tanks, sealed oil pipelines, intelligent flow control devices, and real-time monitoring sensors. However, traditional models rely primarily on manual modeling, resulting in long update cycles and difficulty in quickly responding to design changes, leading to low design iteration efficiency. The lack of a highly integrated simulation platform and incompatible data formats between different software lead to information loss or increased conversion errors during data transmission, compromising the accuracy of simulation results. Separate structural mechanics, fluid dynamics, and thermodynamics analyses are typically employed, lacking multi-physics coupling capabilities and making it difficult to realistically simulate the dynamic interaction between fluids and structures within the gas station. Relying on single-variable optimization, these methods are unable to achieve global optimization under multi-objective constraints, leading to limitations in the final design solution's safety, stability, and economics. Traditional simulation methods often rely on manually defined boundary conditions and struggle to incorporate real-time data for feedback optimization. This results in a lack of adaptive adjustment capabilities in real-world applications, impacting the long-term applicability and scalability of the models. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide an integrated design method for a three-dimensional simulation model of a skid-mounted gas station to solve at least one of the above technical problems.

[0004] To achieve the above objectives, an integrated design method for a three-dimensional simulation model of a skid-mounted gas station is provided, comprising the following steps:

[0005] Step S1: Obtaining a skid-mounted gas station structural drawing; constructing a three-dimensional gas station component according to the skid-mounted gas station structural drawing; performing virtual assembly based on the three-dimensional gas station component to generate a three-dimensional simulation model of the gas station;

[0006] Step S2: Obtain fuel data and transmit it to a three-dimensional simulation model of the gas station, perform fuel flow simulation, and generate fuel flow data; detect fuel reflux based on the fuel flow data to obtain fuel reflux data; perform fuel pipeline cavitation detection based on the fuel reflux data to obtain fuel pipeline cavitation data;

[0007] Step S3: Marking the pipeline cavitation location based on the fuel pipeline cavitation data, and continuously monitoring the fuel pipe body heat load at the pipeline cavitation location; and assessing the fuel vaporization risk based on the fuel pipe body heat load;

[0008] Step S4: Filling the three-dimensional simulation model of the gas station with explosion-proof materials based on the risk of fuel vaporization to obtain explosion-proof material data; designing an inert gas explosion-proof device for the three-dimensional simulation model of the gas station based on the risk of fuel vaporization to obtain inert gas explosion-proof device data; integrating the explosion-proof material data and the inert gas explosion-proof device data into the three-dimensional simulation model of the gas station to generate a three-dimensional simulation optimization model of the gas station.

[0009] This invention obtains skid-mounted gas station structural drawings and constructs three-dimensional components to create a precise digital model, providing a foundation for virtual assembly and simulation. This model ensures the accurate spatial layout of oil tanks, pipelines, pumps, valves, and control devices, avoiding errors in traditional manual modeling and improving design efficiency. Once virtual assembly is implemented, optimization and adjustments can be made during the initial design phase to ensure structural rationality and enhance the reliability and safety of construction and operation. Real-time acquisition and transmission of fuel data enables more accurate fluid dynamic simulations, enabling early detection of flow problems and adjustments to system configuration to prevent pipeline cavitation risks. Pipeline cavitation detection precisely identifies damaged areas, facilitating monitoring and optimization, and reducing the risk of rupture. Continuous monitoring of pipe heat load and fuel vaporization risks ensures controllable temperature changes, reduces vaporization risks, and enhances safety. Based on vaporization risks, explosion-proof materials and inert gas protection devices are optimized to improve the station's ability to respond to unexpected risks. Through multi-physics field optimization, a balance is achieved between safety, stability, and cost-effectiveness in gas station design, operation, and maintenance, enhancing applicability and long-term operational safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0011] Figure 1 A schematic flow chart of the steps of an integrated design method for a three-dimensional simulation model of a skid-mounted gas station according to the present invention;

[0012] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0013] Figure 3 Detailed step flow diagram of step S15 in the present invention;

[0014] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0015] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative work are within the scope of protection of the present invention.

[0016] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0017] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0018] To achieve this, please refer to Figures 1 to 3 The present invention provides an integrated design method for a three-dimensional simulation model of a skid-mounted gas station, the method comprising the following steps:

[0019] Step S1: Obtaining a skid-mounted gas station structural drawing; constructing a three-dimensional gas station component according to the skid-mounted gas station structural drawing; performing virtual assembly based on the three-dimensional gas station component to generate a three-dimensional simulation model of the gas station;

[0020] In this example, based on the actual structural drawings of the skid-mounted gas station, professional 3D modeling software (such as AutoCAD, SolidWorks, or Revit) is used to construct the 3D components of the gas station. First, the size, shape, and position of each component are obtained from the drawings. Each component, such as the oil tank, pump, valve, pipeline, and dispenser, is then modeled one by one. Geometric parameters for each component, such as the diameter and volume of the oil tank, are entered according to the detailed annotations and technical specifications on the drawings. After modeling the components, the "Assemble" function is used in the 3D modeling software to assemble the components, ensuring that their connections and spatial relationships are reasonable. In particular, piping connections must be correct to avoid interference or errors. The entire 3D model is then inspected to ensure the precise fit of all components and their proper layout. To verify its correctness, the software's visualization features are used to check the model's stability, dimensional accuracy, and the presence of spatial interference or conflicts. Finally, the completed 3D model is exported to a standard file format, such as STEP, IGES, or STL, for subsequent simulation and optimization.

[0021] Step S2: Obtain fuel data and transmit it to a three-dimensional simulation model of the gas station, perform fuel flow simulation, and generate fuel flow data; detect fuel reflux based on the fuel flow data to obtain fuel reflux data; perform fuel pipeline cavitation detection based on the fuel reflux data to obtain fuel pipeline cavitation data;

[0022] In this embodiment, fuel flow data at the gas station, including parameters such as flow rate, pressure, and temperature, is acquired through sensors or a data acquisition system. This data needs to be input into the modeling software. Subsequently, fluid dynamics simulation software (such as ANSYS Fluent or OpenFOAM) is used to simulate the fuel flow at the gas station. During the fluid simulation process, boundary conditions are first set, including the fuel inlet and outlet pressures, flow rate, and temperature, to ensure that the simulation reflects actual operating conditions. Fuel physical properties (such as density and viscosity) are set based on the fuel type (e.g., gasoline or diesel), with a density of 0.75 g / cm³ and a viscosity of 0.45 cP. Next, fluid dynamics equations are used to calculate the flow velocity distribution, pressure changes, and flow rate distribution within the gas station pipeline. Changes in flow velocity and pressure can be used to identify backflow. To detect cavitation in the pipeline, a critical cavitation pressure threshold is set; areas below this threshold are marked as experiencing cavitation. The presence of cavitation zones indicates that the local pressure has dropped below the vapor pressure of the fluid, forming bubbles that rapidly collapse and can cause pipeline damage. Therefore, these areas require special attention. In addition, the simulation software will automatically generate pressure distribution diagrams, flow path diagrams, cavitation area and other data for subsequent analysis and optimization.

[0023] Step S3: Marking the pipeline cavitation location based on the fuel pipeline cavitation data, and continuously monitoring the fuel pipe body heat load at the pipeline cavitation location; and assessing the fuel vaporization risk based on the fuel pipe body heat load;

[0024] In this embodiment, cavitation areas are marked using fuel flow data obtained through simulation, and detailed monitoring is performed using information such as temperature and pressure. The cavitation locations marked in the simulation are imported into thermal load calculation software (such as COMSOL Multiphysics or ANSYS Mechanical) to perform a thermal load analysis of the pipeline. Thermal load analysis calculates the temperature distribution of the pipeline based on data such as the pipeline material, ambient temperature, fuel temperature, and pipeline geometry. Temperature variations in cavitation areas are particularly important, as excessively high temperatures can trigger fuel vaporization. Based on the temperature distribution, the heat conduction equation is used to analyze the thermal load of each area to ensure that the temperature in the cavitation area does not reach the fuel vaporization temperature. If high-temperature areas exist, particularly cavitation areas, appropriate measures must be taken to reduce the temperature in these areas to prevent vaporization. Further analysis identifies areas at risk of vaporization based on a set vaporization temperature threshold (e.g., 35°C for gasoline and 55°C for diesel). High-risk areas are monitored closely to ensure the safety of gas station operations. All analysis results, including heat load, gasification risk areas, etc., will generate a detailed data report and provide a basis for subsequent explosion-proof design.

[0025] Step S4: Filling the three-dimensional simulation model of the gas station with explosion-proof materials based on the risk of fuel vaporization to obtain explosion-proof material data; designing an inert gas explosion-proof device for the three-dimensional simulation model of the gas station based on the risk of fuel vaporization to obtain inert gas explosion-proof device data; integrating the explosion-proof material data and the inert gas explosion-proof device data into the three-dimensional simulation model of the gas station to generate a three-dimensional simulation optimization model of the gas station.

[0026] In this embodiment, a suitable explosion-proof material is selected for filling within the 3D simulation model. Explosion-proof materials typically possess high-temperature resistance, corrosion resistance, and excellent flame retardancy. The type and thickness of the material are selected based on the actual risk of gasification. The thickness of the explosion-proof material is calculated to ensure it can withstand potential explosion pressures and effectively isolate the fuel gas from the external environment. Furthermore, an inert gas explosion-proof device is designed. A suitable inert gas (such as nitrogen) is selected and introduced into the pipeline area where gasification occurs. Within the simulation model, based on the gasification risk assessment, parameters such as the gas delivery pipeline, pressure control valve, and gas flow rate are designed to ensure that the inert gas covers the entire high-risk area and forms an effective gas barrier. Fluid dynamics simulation is used to calculate the flow and pressure distribution of the inert gas within the pipeline to ensure optimal delivery. Finally, the design results for the explosion-proof material and inert gas explosion-proof device are integrated into the 3D simulation model of the gas station to generate an optimized model. Design drawings and reports for construction and implementation are then exported to ensure the feasibility and safety of the design.

[0027] Preferably, step S1 is specifically as follows:

[0028] Step S11: Obtaining a skid-mounted gas station structural drawing;

[0029] In this embodiment, the structural drawings of the skid-mounted gas station are obtained. The drawings can be electronic files provided during the design process of the gas station, which usually include detailed information such as the size, location, and shape of each facility and component. The drawings should include the specific layout of storage tanks, pipelines, valves, pump stations, electrical systems, and other facilities. At this time, use design tools such as AutoCAD or Revit to open the drawing file to ensure that all dimensioning is clear and correct. If there are multiple levels or multiple details in the drawing, you can use the layer function to separate the levels of each facility for viewing and extraction. The specifications, materials, and technical requirements of each component should be indicated in the drawings, especially the volume, pressure bearing capacity, and other data of storage tanks and pipelines, which are very important for subsequent modeling. Use the dimensioning and symbols on the drawings to ensure the accuracy of all information and prepare the data for subsequent three-dimensional modeling.

[0030] Step S12: identifying the tank structure based on the skid-mounted gas station structural drawing;

[0031] In this embodiment, all information about the tank in the drawing is extracted, including the shape, size, volume and location of the tank. In AutoCAD, according to the floor plan of the tank, use the polygon or circle tool to draw the base and shape of the tank. Accurately mark the height, diameter, etc. of the tank, and find its material properties on the drawing, such as steel or composite materials. If there are multiple tanks, they need to be identified and their specific data recorded one by one. The drawings of the tanks usually also contain other detailed information, such as valves, pressure relief devices, etc. For each tank, data can be extracted separately, such as the oil storage capacity of each tank, valve type and other parameters. These parameters are crucial in the subsequent 3D modeling and simulation process. After identification, the geometric data of the tank is organized into a format that can be imported into 3D modeling software, such as STEP, IGES or DXF files.

[0032] Step S13: Identifying the pipeline network structure based on the skid-mounted gas station structural drawing;

[0033] In this embodiment, the layout of the pipeline is usually represented by a single line or double lines in the drawing, and it is necessary to extract information such as the direction, diameter, elbows, valves, and joints of the pipeline. First, use software such as AutoCAD to open the pipeline plan and elevation of the gas station, and check the pipeline path and connection points one by one. It is necessary to indicate the specifications of each pipeline, such as the pipeline diameter, wall thickness, material (such as steel pipe or composite pipe), etc., and record the position of each valve and joint. For pipeline connection components, all pipeline interfaces and connection methods need to be identified to ensure the integrity of the pipeline. According to the pipeline numbers and identifications on the drawings, check the specifications and process requirements of each pipeline. For each pipeline, further organize the detailed data of each pipeline according to its direction and the facilities involved (such as storage tanks, pumping stations, etc.), including flow rate, pressure level, etc. After completion, all pipeline information is integrated and exported into a file format that can be used for 3D modeling to ensure the accuracy of subsequent modeling.

[0034] Step S14: Merge the gas station structure according to the storage tank structure and the pipeline network structure to obtain a three-dimensional gas station component;

[0035] In this embodiment, 3D modeling software (such as SolidWorks, Revit, or AutoCAD 3D) is used to import the tank and pipeline information identified in steps S12 and S13. Tank information includes its shape, dimensions, materials, and accessories, while pipeline information includes its dimensions, connection method, and routing. Using the 3D modeling software, these tank and pipeline components are accurately arranged and connected according to the data on the drawings. The position of each tank and the routing of each pipeline must conform to the layout requirements on the drawings. During the 3D modeling process, special attention must be paid to the connection between the pipeline and the tank to ensure the seal and structural stability of the connection. Pipeline bends, elbows, valves, and pump stations must be precisely measured and ensured to comply with design specifications. Any error in details during this process will affect subsequent simulation and optimization, so the model must be completed strictly in accordance with the dimensions and positions on the design drawings. Finally, all components are combined into a complete 3D gas station structure and saved as a 3D model file format for subsequent simulation and analysis.

[0036] Step S15: Perform virtual assembly based on the three-dimensional components of the gas station to generate a three-dimensional simulation model of the gas station.

[0037] In this embodiment, the three-dimensional component file of the gas station is imported, and the virtual assembly function (such as the virtual assembly module of SolidWorks or the three-dimensional assembly function of Revit) is used to accurately assemble the various components according to the design drawings. During the virtual assembly process, ensure that the connection relationship between each component is accurate, especially the connection between the pipeline and the storage tank needs to be carefully checked. Through the assembly process, check the fit between the various components to ensure that no collision or interference occurs. If errors or unreasonable connection methods are found during the assembly process, they can be resolved by adjusting the component position or modifying the design. After assembly is completed, a virtual simulation tool is used to perform dynamic inspection to ensure the stability of the overall structure of the gas station. During this process, the spatial layout of the gas station is checked to ensure the rationality and operability of each component. Finally, a complete three-dimensional simulation model of the gas station is generated and saved in a standard simulation file format, such as STL, OBJ or other formats suitable for subsequent simulation and optimization.

[0038] Preferably, step S15 is specifically as follows:

[0039] Step S151: performing component interference detection based on the three-dimensional components of the gas station to obtain component interference data;

[0040] In this embodiment, the three-dimensional component data of the gas station is imported into interference detection software, such as AutoCAD, SolidWorks, CATIA, etc. These software provide interference detection functions, which can detect whether there are collisions, interferences or unreasonable overlaps between various components. The key steps of interference detection include setting the detection accuracy and detection range. The accuracy is usually set to 0.1mm, and the detection range needs to cover the geometric shapes of all components, including storage tanks, pipes, valves, pump stations, etc. When performing interference detection, the system will automatically identify and list all areas where interference occurs, and record the specific location of the interference, the degree of interference and the affected components. The interference data is presented in a list or graphical form, listing in detail the coordinate information of each interference area, the size and type of the interfering object. These interference data are crucial for subsequent optimization and adjustment work, and need to accurately reflect the relative position and geometry of each component. After the detection is completed, the interference data is saved in a standard format (such as CSV, TXT or database format) for subsequent use.

[0041] It is particularly important that step S151 includes the following steps:

[0042] Extract component structure data of gas station 3D component data;

[0043] In this embodiment, a 3D scanning device (such as a laser scanner or structured light scanner) is used to acquire the physical form data of the gas station. Point cloud data preprocessing techniques (including noise reduction, deduplication, and uniform sampling) are employed to ensure data quality. A triangulated mesh-based reconstruction algorithm is then used to convert the point cloud data into mesh data. This data is then aligned with the CAD design files of the gas station components to ensure that the extracted 3D component structure is consistent with the actual gas station layout. To analyze the geometric relationships between components, topological analysis is required. The connectivity relationships between components are stored in an adjacency matrix, and a topological sorting algorithm is used to analyze the component hierarchical structure. This process requires identifying key gas station components, such as storage tanks, pipelines, valves, filters, and pumps, extracting their 3D geometric parameters (such as length, width, height, wall thickness, and pipe diameter), and performing data standardization to ensure the integrity and accuracy of the component structure data.

[0044] Perform surface mesh division according to component structure data to obtain component surface mesh data;

[0045] In this example, the component structure data is cleaned up to eliminate redundant facets and optimize topological connections to ensure mesh quality. The component surfaces are then meshed using either the Delaunay triangulation algorithm or the octree subdivision method. Uniform quadrilateral meshing is used for regular geometries (such as rectangular oil tanks and cubic storage boxes), while adaptive triangulation is used for complex geometries (such as irregularly shaped pipes and flange interfaces) to improve mesh quality. The mesh size is selected based on the actual size of the gas station components and the simulation requirements. For example, a fine mesh of 1mm to 5mm can be used for key components (such as oil pumps and flow meters), while a coarse mesh of 10mm to 50mm can be used for large-scale structures (such as oil tanks and platforms). To ensure the morphological quality of the mesh cells, quality factors (aspect ratio, skewness, and Jacobian ratio) are used to evaluate the mesh. The Laplace smoothing algorithm is then used to optimize the mesh quality, keeping the deformation rate of all cells within 10% to improve the accuracy of subsequent calculations.

[0046] Perform component space occupancy analysis based on component surface mesh data to obtain component space occupancy data;

[0047] In this embodiment, the bounding box (Bounding Box) of each component is calculated based on the surface mesh data. The axis-aligned bounding box (AABB) method is used to quickly determine the component's approximate spatial extent. The minimum enclosing rectangle (MER) algorithm is then used to further optimize the bounding box size to improve the accuracy of the spatial occupancy calculation. Next, a spatial hierarchical model of the components is constructed based on the AABB tree's hierarchical bounding structure, enabling subsequent neighbor relationship calculations and interference detection to be accelerated through hierarchical traversal. The spatial occupancy data must include the component's three-dimensional boundary information, including the minimum coordinates (xmin, ymin, zmin) and maximum coordinates (xmax, ymax, zmax), and is stored in standardized units (millimeter or meter). Furthermore, to more accurately analyze spatial occupancy, the component's convex hull is calculated. The Quickhull algorithm is then used to construct the component's minimum enclosing volume, thereby more accurately reflecting the component's actual occupancy.

[0048] Calculate component adjacency relationships based on component space occupancy data to obtain component adjacency relationship data;

[0049] In this embodiment, a spatial indexing method (such as KD-Tree or R-Tree) is used to construct an adjacency index between components, reducing the computational complexity of querying adjacent components from O(n²) to O(log n), improving computational efficiency. The Euclidean distance calculation method is then used to determine the spacing between components. For components with spacing less than a set threshold (e.g., 5mm or 10mm), their actual contact area is further calculated. Specifically, for two components A and B, the intersection area of their bounding boxes is calculated. If the volume of the intersection area is greater than a set threshold (e.g., 1000mm³), the two components are considered to be in contact. For components with rotating parts (e.g., valves and pumps) or flexible connections (e.g., hoses), a rotation transformation matrix is also used to calculate their dynamic contact state, ensuring that the adjacency data covers the relative positions of components under different operating states. Finally, the adjacency data is stored as an adjacency table structure, recording information such as the adjacent component ID, distance, and contact area for each component to facilitate interference detection.

[0050] Component interference detection is performed based on component adjacent relationship data to obtain component interference data.

[0051] In this embodiment, interfering component pairs are screened based on neighbor relationship data, and a surface-to-surface collision detection method is used for fine-grained analysis. For rigid components (such as oil tanks and pipe supports), an OBB (directed bounding box) collision detection algorithm is used to calculate the overlap of component projections. If the projected areas intersect, the GJK (Gilbert-Johnson-Keerthi) algorithm is further used to calculate the closest point distance to accurately determine interference. For flexible components (such as rubber pipes and flexible connectors), the finite element method is used to simulate their deformation. The actual degree of interference is calculated through contact stress analysis, and a contact stress threshold (e.g., 10 MPa) is set to determine whether interference occurs. In addition, the storage of interference data must include key information such as the interfering component ID, interference depth, and interference area to facilitate subsequent interference optimization and adjustment. To improve detection efficiency, parallel computing can be used to accelerate the interference detection process. For example, GPU-accelerated algorithms (such as CUDA parallel computing) can be used to achieve real-time interference detection for large-scale components, reducing detection time to milliseconds, thereby meeting the real-time requirements of the gas station simulation system.

[0052] Step S152: Optimizing component spacing based on component interference data;

[0053] In this embodiment, the interference area is analyzed to identify which components have interference, and the minimum distance of interference is calculated. According to the degree of interference, the method of adjusting the component spacing is adopted to eliminate the interference. For example, if the spacing between two storage tanks is insufficient, resulting in mutual interference, their spacing needs to be increased. When adjusting, the increase in spacing is usually set to 2mm to 10mm, and the specific value is determined according to the degree of interference and the size and structural requirements of the components. During the optimization process, it is necessary to ensure that the adjusted component spacing does not affect the overall function and safety of the gas station. The parameters in the optimization process include the geometric dimensions, load-bearing capacity, pipeline flow requirements, etc. of the components, which should be considered during optimization to ensure that the adjusted spacing can meet the structural, operational and safety requirements. All optimized spacing data should be recorded for subsequent adjustment and assembly.

[0054] Step S153: adjusting the component installation position based on the component spacing;

[0055] In this embodiment, the component spacing is applied to the three-dimensional model of the gas station, and the specific position of each component is adjusted. The components are rearranged in the virtual space according to the optimized spacing using three-dimensional modeling software (such as AutoCAD, SolidWorks, Revit). When adjusting, the movement of the components needs to take into account their functions and operating space to avoid excessive squeezing or affecting the installation and use of other components. The adjustment of the installation position should ensure that the positions of key components such as storage tanks and pipelines meet the design specifications, and the layout of each component does not interfere with normal operation and maintenance. The adjustment range depends on the functional requirements and layout constraints of each component. The adjustment range is usually set to 10mm to 50mm to ensure the overall structural stability and space utilization efficiency. The installation position of each component needs to be recorded and marked to ensure that the adjusted position meets the requirements of the final three-dimensional simulation model.

[0056] Step S154: reconstructing component connection relationships according to component installation positions;

[0057] In this embodiment, in the three-dimensional modeling software, the connection relationship between each component is re-established according to the adjusted component installation position. The connection relationship includes the connection between the storage tank and the pipeline, the connection between the valve and the pipeline, etc. According to the design requirements of the oil station, the connection method of each component is confirmed to ensure that the connection point of the pipeline, the position of the valve, and the interface between the pump station and the storage tank meet the requirements of fluid flow. When reconstructing the connection relationship, attention should be paid to the direction of the pipeline, the contact method between the pipeline and the storage tank, and the installation requirements of other components to ensure the accuracy and reliability of each connection point. At this time, it is necessary to set technical requirements such as the maximum bending angle of the pipeline connection and the sealing performance of the interface to ensure that leakage or structural instability will not occur during actual operation. All new connection relationships should be recorded in the data sheet for subsequent assembly and optimization.

[0058] Step S155: Perform virtual assembly based on the component connection relationship, wherein the assembly alignment accuracy is set to ≤1mm and the simulation time step is 0.01-1s, and generate a three-dimensional simulation model of the gas station.

[0059] In this example, component connection relationships are imported into virtual assembly software, and the assembly alignment accuracy is set to ≤1mm to ensure precise connections between components. Components are virtually assembled using virtual assembly capabilities (such as SolidWorks, AutoCAD, or PTC Creo), gradually connecting each component according to a preset assembly sequence. During the virtual assembly process, the system automatically calculates the relative position, angle, and orientation of each component based on its connection relationships and precisely aligns them. To ensure a smooth assembly process, the simulation time step is set to 0.01 to 1 second, ensuring that the motion of each component in the virtual environment is accurately simulated and that the interaction forces and stability of the components are accurately calculated at each step. During the assembly process, if any component is found to be improperly assembled or has interference issues, the system will provide real-time feedback and adjust the component's position or reset the connection relationship as needed. Ultimately, all components are virtually assembled, generating a complete 3D simulation model of the gas station. This model is saved in a standard simulation file format, such as STL or OBJ, for subsequent analysis, verification, and optimization.

[0060] It is particularly important that step S155 includes the following steps:

[0061] Analyze assembly constraints based on component connection relationships to obtain assembly constraint data;

[0062] In this embodiment, component connection data for a skid-mounted gas station is obtained. This data includes information such as the interface type, connection method, installation orientation, and motion constraints between components. This connection data is sourced from gas station design documents, 3D CAD assembly drawings, or product BOMs (Bill of Materials). Based on the component connection relationships, topological analysis methods are used to analyze assembly constraints. Assembly constraints primarily include fixed constraints, rotational constraints, translational constraints, and sliding constraints. Fixed constraints describe situations where there is no relative motion between components, such as the connection between a flanged pipe and a tank. Rotational constraints describe the motion of hinged or revolving components, such as the connection between a valve and a pipe. Translational constraints describe the motion of linear sliding components, such as a fuel pump bracket on a rail. Sliding constraints describe the free sliding of components in a specific direction, such as adjustable support structures. During assembly constraint analysis, computer-aided assembly (CAA) technology is used to extract component constraint data through mathematical analysis or finite element analysis (FEA) to ensure that the assembly relationships meet engineering design requirements.

[0063] Calculate component matching relationships based on component assembly constraint data;

[0064] In this embodiment, the fit relationship includes key parameters such as the contact type between components, tolerance matching, and assembly sequence. Contact types can be divided into three categories: surface contact, line contact, and point contact. For example, flange connections are surface contacts, and bearing balls and inner and outer rings are point contacts. Tolerance matching is used to ensure the dimensional compatibility of components during assembly, such as the clearance, tolerance grade, and roughness requirements of the hole-shaft fit. The assembly sequence is calculated using a hierarchical assembly analysis method. First, the basic components, such as the base and support frame, are determined, and then other components, such as oil tanks, pipes, pumps, and valves, are gradually assembled upward. During the fit relationship calculation process, the assembly tolerance analysis (ATA) method is used to calculate the cumulative dimensional errors between different components using an error transfer matrix. For components involving multi-degree-of-freedom motion, such as rotary valves or sliding guides, dynamic fit analysis is also required using kinematic simulation software (such as ADAMS and MSC.Nastran) to ensure that the motion between components does not cause interference or overconstraint.

[0065] Perform virtual assembly according to component matching data to obtain virtual assembly data;

[0066] In this embodiment, virtual assembly utilizes 3D assembly modeling technology to virtually construct all components according to the calculated assembly sequence and constraint relationships. During the virtual assembly process, the initial and target positions of each component must be defined, and the assembly transformation matrix (ATM) is used to calculate the component's spatial transformation information, including rotation, translation, and scaling. For components involving complex motion, such as rotating or sliding structures, inverse kinematics (IK) algorithms are used to adjust their positions to ensure the correct assembly posture. During the assembly process, interference between components is detected. If interference occurs, the assembly path is adjusted or the component spacing is optimized. Interference detection is implemented using geometric Boolean operations or octree partitioning, which compares the geometric overlap between components to determine the interference area. All assembly process data, including component positions, assembly sequence, and motion trajectories, is stored as virtual assembly data for subsequent 3D simulation.

[0067] Construct a three-dimensional simulation model of the gas station based on virtual assembly data.

[0068] In this embodiment, the 3D simulation model is constructed using a physics-based simulation method, integrating geometric data, assembly relationships, material properties, physical parameters, and other information about the gas station components. First, the virtual assembly data is converted into a format supported by 3D simulation software (such as ANSYS, SolidWorks Simulation, or Unity 3D), such as STL, STEP, or IGES. Next, simulation parameters are defined based on the gas station's operating environment, including fluid parameters (flow rate, pressure, temperature, etc.), structural parameters (material elastic modulus, Poisson's ratio, density, etc.), and kinematic parameters (rotation angle, slip velocity, etc.). Finite element meshing is used to decompose the 3D model into small elements for physical calculations. Meshing uses hexahedral or tetrahedral elements, and the mesh density is adjusted based on the simulation accuracy requirements. For example, the mesh density in critical stress-bearing areas is higher, typically set to 0.1mm-1mm. Subsequently, based on the simulation environment parameters, the system simulates gas station operating conditions, such as pump startup, pipeline fluid flow, and valve opening and closing. Key indicators such as structural stress, thermal expansion, and vibration response of the gas station system under different operating conditions are monitored. Ultimately, the resulting simulation data is integrated into a 3D simulation model, forming a complete 3D gas station simulation system for subsequent analysis and optimization.

[0069] Preferably, the fuel flow simulation in step S2 includes:

[0070] Obtain fuel data and perform standardization processing to obtain standardized fuel data;

[0071] In this embodiment, relevant parameters of the fuel type used in the skid-mounted gas station are collected, including the density, viscosity, specific heat capacity, etc. of the fuel. The raw data of the fuel can be obtained through gas station sensors or laboratory analysis. These data are usually expressed in original units, such as kilograms per cubic meter (kg / m³) and Pascal (Pa). The purpose of standardization is to convert these raw data into unified standard units and normalize them to a specific range. For example, the standardization of fuel density can be performed using the formula (ρfuel-ρmin) / (ρmax-ρmin), where ρfuel is the actual measured density value, and ρmax and ρmin are the maximum and minimum values of the fuel density. The standardized data will make the comparison between different data more intuitive and convenient for use in subsequent simulations. For other parameters such as temperature and pressure, similar standardization methods are used to ensure that all data are converted to a standard range, such as the interval from 0 to 1, to facilitate calculation and analysis by the simulation software.

[0072] Transmit standardized fuel data to the gas station 3D simulation model, and upload the gas station 3D simulation model to the simulation software;

[0073] In this embodiment, it is ensured that the standardized fuel data has been stored in a format that is compatible with the simulation software. Commonly used formats include JSON, CSV, XML, etc. In the simulation software, the input data of the three-dimensional simulation model of the gas station includes information such as the flow rate, temperature, and pressure of the fuel. The simulation software needs to accept this data in order to perform further simulation. During the upload process, the standardized fuel data is associated with the relevant parts of the three-dimensional model of the gas station, such as connecting with the pipeline system, storage tanks, pumping stations, etc., to ensure that each component can correctly reflect the characteristics of the fuel during the simulation process. When uploading to the simulation software, it is necessary to confirm that the accuracy of all input data meets the simulation requirements and ensure that the simulation software can correctly parse this data. After uploading, the simulation software will automatically combine the fuel data with the three-dimensional model to perform multi-physics field simulation calculations.

[0074] Perform fuel flow simulation in the simulation software, setting the flow range to 5-200m³ / h and the flow velocity range to 0.1-5m / s;

[0075] In this embodiment, the flow range is set to 5-200m³ / h, and the flow velocity range is set to 0.1-5m / s. The specific operation is to input the standardized data of the diameter, shape, length and fuel of the pipeline into the simulation model, and the simulation software will calculate the fluid flow in the pipeline based on these parameters. In terms of flow setting, the software adjusts the flow rate of the fuel in the pipeline according to the set flow range, and the flow velocity setting will affect the friction loss, pressure distribution and flow stability of the fluid. The purpose of setting these ranges is to simulate the behavior of the oil station system from low flow to high flow, to ensure that the flow of fuel under different working conditions can be fully evaluated. In the simulation program, the flow characteristics of the oil flow in the pipeline are calculated by solving the Navier-Stokes equations and the continuity equation based on parameters such as flow rate and flow velocity.

[0076] The fuel pressure distribution is simulated in the simulation software, and the initial pressure of the pipeline is set to 0.1-5MPa and the pressure loss coefficient is set to 0.01-0.1;

[0077] In this embodiment, the initial pipeline pressure range is set to 0.1-5MPa, and the pressure loss coefficient range is set to 0.01-0.1. The specific operation is to input the initial pipeline pressure, pipeline length, diameter, fluid characteristics and other data based on the pipeline configuration in the gas station system. The pressure loss coefficient is usually determined based on the roughness of the pipeline, the bend angle and the flow rate of the fluid. During the simulation process, the software will calculate the pressure change in the pipeline based on these initial conditions and estimate the pressure loss of each pipe section based on the pressure loss coefficient. This simulation will help analyze the transmission pressure of fuel in the pipeline system and detect whether there is excessive pressure loss, which affects the safety and efficiency of the pipeline and equipment.

[0078] The fuel temperature field distribution was simulated in the simulation software, with the fuel inlet temperature set to -20°C to 80°C, the ambient temperature to 30°C to 50°C, and the heat transfer coefficient to 10-500W / (m²·K);

[0079] In this embodiment, the fuel inlet temperature range is set to -20°C to 80°C, the ambient temperature range is 30°C to 50°C, and the heat transfer coefficient is set to 10-500W / (m²·K). In this process, the heat exchange conditions of the pipelines in the gas station need to be input into the simulation model, and the heat transfer coefficient of the pipeline surface needs to be set. This coefficient will affect the heat transfer efficiency. The set fuel inlet temperature range is to simulate the operation of the gas station under different climatic conditions, while the ambient temperature reflects the impact of the external environment on the gas station. The setting of the heat transfer coefficient is usually selected based on the material of the pipeline, the surface roughness, and the heat exchange conditions between the pipeline and the environment. During the simulation process, the software will calculate the temperature distribution of each point in the pipeline and analyze the impact of temperature changes on the flow of fuel, especially whether the fluidity of the fuel will be adversely affected when the temperature is low or high.

[0080] Run the fuel flow simulation program in the simulation software to obtain fuel flow data.

[0081] In this example, a fuel flow simulation program in simulation software is run to obtain fuel flow data. This data includes information such as flow velocity distribution, pressure distribution, and temperature changes within the pipeline. Based on all input conditions and parameters, the simulation program numerically solves fluid dynamics equations to generate detailed simulation results. The resulting flow data can help designers understand the operating state of the gas station system under different flow rates, flow velocities, temperatures, and pressures, and further optimize the station design to ensure efficient and safe operation.

[0082] Preferably, the detection of oil reflux in step S2 includes:

[0083] extracting a fuel flow video sequence based on the fuel flow data;

[0084] In this embodiment, fuel flow data from the simulation software is exported, and each frame of the image represents the state of fuel flow at a specific moment. By mapping fuel flow data at different time steps into continuous image frames while maintaining temporal continuity, a fuel flow video sequence is generated. Each frame of the image shows the flow path of the fluid within the pipeline and displays the distribution of parameters such as flow rate and pressure. The color or brightness of the image represents different flow states, facilitating subsequent processing and analysis. These video sequences record the dynamic changes in the flow state, forming a time series of video data for subsequent flow analysis.

[0085] Preprocessing the fuel flow video sequence, including grayscale processing, Gaussian blurring, and edge detection, to obtain a preprocessed fuel flow video sequence;

[0086] In this embodiment, the first step is grayscale processing, which converts the color image of each frame into a grayscale image, removes the color information, and retains only the brightness information. This process can simplify the calculation process and reduce data complexity. Next, Gaussian blur is applied for denoising. Gaussian blur makes the image smoother by performing a weighted average on each pixel, reducing the impact of noise, which in turn helps to improve the accuracy of subsequent analysis. Finally, edge detection is performed, and the Canny edge detection algorithm is commonly used. It can effectively identify the edge parts in the image and highlight the pipeline outline and flow direction. Edge detection is to ensure that the flow path is clearly visible in subsequent steps and to accurately extract the flow structure.

[0087] Identifying the flow direction of the pre-processed fuel flow video sequence; calculating the flow rate of the pre-processed fuel flow video sequence;

[0088] In this embodiment, in a preprocessed fuel flow video sequence, flow direction is identified by calculating pixel displacements between adjacent frames in the image. Pixels within each frame are compared to determine the change in pixel position between adjacent frames, thereby extracting the flow direction. Optical flow is typically used to perform pixel matching between adjacent frames to determine the direction and magnitude of pixel displacement. By calculating the flow direction of each point using optical flow, the flow trend of the fuel within the pipeline can be determined, identifying the flow direction of the fluid at each location. Flow rate is calculated based on the pixel displacement between adjacent frames. By calculating the displacement of each pixel in a time series, flow velocity information can be obtained. The displacement of each pixel in each frame reflects the speed of the fuel flow. By averaging or weighted averaging the displacements of all pixels, the average flow velocity for each area is obtained in meters per second (m / s). The flow velocity can be calculated at different locations and time points within the pipeline to determine the distribution of the flow velocity throughout the pipeline.

[0089] Construct an optical flow vector field based on the flow direction and flow rate;

[0090] In this embodiment, the displacement information of each pixel is converted into a vector form. The direction of the vector represents the direction of flow, and the length of the vector represents the flow velocity. The optical flow vector field can intuitively display the spatial characteristics of flow, especially in complex pipeline structures, where the vector field can clearly reveal the changing trends of flow. The optical flow vector field is an important tool for analyzing flow states, effectively demonstrating the overall dynamics of fluid in a pipeline.

[0091] Calculate the curl of the optical flow vector field; identify the vortex area of the optical flow vector field based on the curl;

[0092] In this embodiment, curl is an important physical quantity that describes the rotational characteristics of a fluid. It indicates the intensity of the fluid's rotation at a specific point. In an optical flow vector field, curl is calculated by analyzing the local rotation of the vector field. When calculating curl, the changes in the vector field around each point are evaluated to determine whether the flow exhibits rotational characteristics. If the optical flow vector field exhibits significant rotational changes in a certain area, the curl value in that area is higher. The larger the curl value, the more rotational the flow in that area. A vortex region is a region of fluid motion that exhibits rotational characteristics, and curl in the optical flow vector field can reveal this rotational characteristic. Curl describes the degree of rotation of the fluid at a specific point or within a specific area. When analyzing the optical flow vector field, the curl value of each point is first calculated, which reflects the rotation of the fluid around that point. If the curl value of a local area increases significantly, it indicates that the fluid has rotated within that area, forming a vortex. To accurately identify vortex regions, a curl threshold must be set. This threshold is typically determined based on the actual flow conditions and the required accuracy. For example, if the curl threshold is set to 0.1, any region with a curl value exceeding 0.1 is considered a vortex region. The threshold value is adjusted based on the flow state, flow velocity, and fluid properties of the pipe. Higher curl values typically correspond to abrupt changes in flow or areas of backflow, while lower curl values indicate smoother flow. Therefore, setting an appropriate curl threshold is crucial for accurately identifying vortex regions.

[0093] The oil reflux is detected based on the vortex area to obtain the oil reflux data.

[0094] In this embodiment, in vortex regions, fluid often experiences localized backflow or reverse flow, manifesting as a decrease in flow velocity or a change in flow direction. By analyzing the dynamic changes in the vortex region, oil backflow can be detected. The intensity, location, and time series of backflow can be obtained by continuously tracking the evolution of the vortex region. Backflow data can provide information about the flow characteristics of oil in pipelines, including backflow points and intensity, providing valuable data support for gas station pipeline design and optimization.

[0095] Preferably, the fuel pipeline cavitation detection in step S2 includes:

[0096] Mark the oil return area of the gas station 3D simulation model based on the oil return data;

[0097] In this embodiment, information about the reflux area is extracted from the acquired oil flow data, and the characteristics of the reflux are identified by analyzing the flow direction and velocity. The reflux area typically appears as a region with negative velocity or reversed flow direction. Based on these characteristics, the relevant areas are marked in the three-dimensional simulation model of the gas station. To ensure the accuracy of the reflux area marking, a velocity threshold is set. If the flow velocity is less than -0.1 m / s, the area is considered a reflux area. The threshold varies for different gas station designs and operating conditions, so it needs to be adjusted based on the actual gas station data. Using this data, the oil reflux area is accurately calibrated and matched to structural elements (such as pipelines, storage tanks, etc.) in the three-dimensional model of the gas station.

[0098] Detect pressure gradients in the oil reflux area; mark low-pressure areas in the oil reflux area based on the pressure gradients;

[0099] In this embodiment, after identifying the oil reflux area, the pressure distribution is calculated using fluid mechanics. In the reflux area, the pressure gradient is large, so the rate of change of pressure at each point in the pipeline needs to be calculated. By measuring the pressure data within the gas station pipeline, numerical methods such as the finite difference method are used to calculate the pressure gradient. It is assumed that when the pressure gradient exceeds a certain value, it indicates that the area has stronger flow disturbances. Specifically, when the pressure gradient value exceeds 0.2 Pa / m, it can be marked as an area with drastic pressure changes. At this point, the area is further analyzed as a low-pressure area, especially in areas where fluid refluxes, where pressure is often low. Once the pressure gradient is calculated, low-pressure areas can be accurately identified in the reflux area by setting a pressure gradient threshold. Low-pressure areas typically appear in the center of the reflux area or where the flow rate varies extremely. A pressure threshold is set, for example, areas below 0.5 MPa are considered low-pressure areas. By screening the pressure data of the entire three-dimensional model, low-pressure areas are accurately demarcated and marked on the three-dimensional simulation model of the gas station.

[0100] Calculate the turbulence intensity in the low-pressure area; determine the turbulence cavitation value based on the preset cavitation critical value and turbulence intensity to obtain the turbulence cavitation value;

[0101] In this embodiment, after the low-pressure area is confirmed, the turbulence intensity of the area is calculated based on the principles of fluid dynamics. Turbulence intensity reflects the irregularity of the fluid and the degree of flow disturbance. The turbulence intensity in the low-pressure area is calculated by combining the flow velocity and viscosity data through simulation software or analytical methods. The calculation of turbulence intensity is usually based on the standard deviation of flow velocity fluctuations or the disturbance amplitude of the flow field. A turbulence intensity threshold is set. For example, when the intensity exceeds 0.5, it means that the flow in the area is very unstable and cavitation is formed. The turbulence intensity is compared with the cavitation critical value (such as the critical turbulence intensity for cavitation to occur is 0.7). If the turbulence intensity exceeds the critical value, it is considered to have a potential risk of cavitation. Through this judgment rule, areas with large turbulence intensity and cavitation are identified. The calculation of turbulence cavitation value in each low-pressure area will be judged in combination with specific pressure, flow velocity and turbulence intensity data.

[0102] According to the turbulent cavitation value, the suspected cavitation area is identified in the low-pressure area to obtain the suspected cavitation area;

[0103] In this example, low-pressure areas are analyzed in conjunction with the turbulent cavitation value. When the turbulent cavitation value exceeds a set threshold (e.g., 0.8), the area is identified as a suspected cavitation area. Based on this determination, these suspected cavitation areas are marked using simulation software. These areas are typically located in areas with low pressure and high turbulence intensity, where bubbles are likely to form and cause cavitation.

[0104] Based on performing laser transmission to the suspected cavitation area, laser transmission data is obtained;

[0105] In this embodiment, laser transmission assesses the presence of bubbles by emitting a laser beam and detecting its transmission through the bubble area. A laser detection instrument transmits a laser beam to the suspected cavitation area, and a receiver measures the laser transmittance. Changes in transmittance reflect the presence of bubbles. When the transmittance drops to a set threshold (e.g., below 0.5), it indicates the presence of large bubbles in the area. This technique further confirms the distribution of bubbles in the suspected cavitation area.

[0106] Calculate the transmittance of the laser transmission data; determine the bubble area of the suspected cavitation area based on the transmittance;

[0107] In this embodiment, the transmittance is calculated by measuring the laser light intensity to determine the degree of laser transmission in the bubble area. In the bubble area, light will be scattered and absorbed, resulting in a decrease in transmittance. By setting the transmittance threshold, the specific range of the bubble area can be confirmed. If the transmittance is lower than 0.5, it means that the bubbles in the area are more obvious, and further analysis is needed to determine whether cavitation occurs in the area. The bubble area is marked using the transmittance data. When the transmittance data reflects a significant decrease, combined with the presence of bubbles, the area is calibrated as a bubble area. The identification of the bubble area helps in subsequent cavitation analysis, especially in areas with lower pressure, where the accumulation of bubbles exacerbates the occurrence of cavitation.

[0108] Monitor pipeline pressure in bubble areas and draw pipeline pressure graphs;

[0109] In this embodiment, the pressure within the bubble region is continuously monitored, real-time data is collected, and a pressure graph is plotted. This pipeline pressure graph can show pressure trends within the bubble region at different time points. Rapidly decreasing sections of the pressure graph typically represent areas at risk of cavitation. The monitoring process is accomplished by installing pressure sensors and a real-time data transmission system. Pressure graphs can be created using simulation software or dedicated data visualization tools.

[0110] Identify periods of rapid pressure drop based on pipeline pressure graphs;

[0111] In this example, by analyzing the pipeline pressure graph, rapid drops within a certain time period are identified. Rapid drops often indicate potential cavitation issues. A pressure drop threshold is set. When pipeline pressure drops by more than a certain percentage (for example, more than 10%) within a short period of time, it is considered a rapid drop, indicating the risk of cavitation. This time period can be used as a focus for subsequent cavitation detection.

[0112] The fuel pipeline cavitation detection is performed according to the period of rapid pressure drop to obtain the fuel pipeline cavitation data.

[0113] In this embodiment, a period of rapid pressure drop within a pipeline is detected. By setting a pressure change rate threshold, for example, if the pressure drops by more than 10% within 1 second, this period is identified as a period of rapid pressure drop. At this point, a cavitation detection program is initiated to conduct a detailed analysis of the state of the fluid within the pipeline during this period. Bubble formation typically occurs in areas of rapid pressure drop, particularly in low-pressure areas. When the gas in the fluid drops below its vapor pressure, bubbles begin to form. Sensors monitor the bubble information within the pipeline in real time, including bubble size, number, and distribution. Ultrasonic sensors or laser transmission instruments are used for bubble detection to obtain real-time bubble data. Based on this, the bubble growth process is analyzed by combining fluid dynamics models and computational fluid dynamics (CFD) simulation. Furthermore, the impact of bubbles on the fluid within the pipeline is evaluated. In high-velocity flow areas, bubbles can generate violent shock waves, leading to fluid instability and exacerbating cavitation. Based on the formation and growth of bubbles, a cavitation index is calculated. The value of the cavitation index is typically quantified based on factors such as the number, volume, and distribution of bubbles. A critical value for the cavitation index is set. For example, when the cavitation index exceeds 1.0, it can be considered that significant cavitation has occurred in the pipeline. This data is used to generate a cavitation report, which details the number and size of bubbles, the cavitation index, and other data, and analyzes their potential impact on the pipeline, such as material corrosion, pipeline damage, or decreased fluid flow efficiency. The ultimate goal of cavitation detection is to provide a scientific basis for the maintenance and management of gas stations, so that effective measures can be taken to prevent the damage caused by cavitation to pipelines and oil transportation.

[0114] Preferably, step S3 is specifically as follows:

[0115] Step S31: Marking the pipeline cavitation location based on the fuel pipeline cavitation data;

[0116] In this embodiment, during the pipeline cavitation detection phase, bubble sensors, ultrasonic sensors, and other equipment are installed to monitor bubble data within the pipeline in real time. The location of the cavitation area is determined by analyzing the distribution, size, and number of bubbles, combined with information such as the pipeline's flow rate, pressure, and temperature. The bubble detection results are typically processed using the sensor feedback signal, setting a bubble count threshold (for example, when the number of bubbles in a certain section of the pipeline exceeds 50, the area is marked as a cavitation location). This step determines which sections of the pipeline are cavitation areas based on the pipeline's geometric structure and fluid state (e.g., when the pressure is less than the vapor pressure), thereby providing basic data for subsequent processing.

[0117] Step S32: continuously monitoring the heat load of the fuel pipe body at the cavitation location of the pipeline;

[0118] In this embodiment, the heat load of the pipe body in the marked cavitation areas is continuously monitored. The heat load is usually collected in real time by the temperature sensor of the pipeline and analyzed together with factors such as flow rate, flow velocity, and pressure. The calculation of the heat load takes into account factors such as the heat change and flow state of the fluid in the pipeline. For example, the threshold range for temperature monitoring is set to 50°C to 100°C, and the heat load of the fuel in the pipeline is evaluated based on the output data of the flow sensor. When the monitored temperature rises abnormally, it is considered that the heat load of the area is out of the normal range and requires further monitoring.

[0119] Step S33: Evaluating the fuel pipe pressure based on the fuel pipe thermal load;

[0120] In this embodiment, the pipeline's pressure state is assessed based on the monitored pipeline heat load data, combined with real-time fluid pressure data within the pipeline. Heat load typically affects the flow characteristics of the fluid within the pipeline, which in turn affects the pressure within the pipeline. Using a fluid dynamics model, combined with factors such as the temperature and flow rate within the pipeline, a formula can be used to calculate the pressure distribution within the pipeline. For example, a standard range for pipeline pressure is set at 0.1-5 MPa; exceeding this range is considered an abnormal state. Based on the heat load data and the fluid dynamics calculation model, the pressure state of each area of the pipeline is further assessed and appropriate measures are taken.

[0121] Step S34: Calculating the fuel pipe body temperature based on the fuel pipe body heat load;

[0122] In this embodiment, the pipeline's pressure state is assessed based on the monitored pipeline heat load data, combined with real-time fluid pressure data within the pipeline. Heat load typically affects the flow characteristics of the fluid within the pipeline, which in turn affects the pressure within the pipeline. Using a fluid dynamics model, combined with factors such as the temperature and flow rate within the pipeline, a formula can be used to calculate the pressure distribution within the pipeline. For example, a standard range for pipeline pressure is set at 0.1-5 MPa; exceeding this range is considered an abnormal state. Based on the heat load data and the fluid dynamics calculation model, the pressure state of each area of the pipeline is further assessed and appropriate measures are taken.

[0123] Step S35: determining the fuel vapor pressure according to the fuel pipe temperature;

[0124] In this embodiment, fuel vapor pressure is one of the key factors influencing the occurrence of cavitation. Based on the temperature data of the fuel in the pipeline and utilizing the fuel's physical properties (such as boiling point and critical temperature), the fuel vapor pressure at that temperature can be calculated. Generally, fuel vapor pressure increases with increasing temperature. When the temperature of the fuel in the pipeline rises to near its vapor pressure, bubbles are more likely to form. In this step, the vapor pressure data of the fuel in the pipeline is calculated using the temperature data and the corresponding vapor pressure formula. For example, the temperature range for vapor pressure calculation is set to -20°C to 80°C, and accurate calculations are performed based on the specific composition and properties of the fuel.

[0125] Step S36: Identifying the vaporization critical point based on the fuel vapor pressure and the fuel pipe pressure;

[0126] In this embodiment, the vaporization threshold refers to the point where the vapor pressure of the fuel in the pipeline equals the internal pressure of the pipeline, at which point vaporization occurs. By comparing the real-time pressure and vapor pressure data within the fuel pipeline, vaporization occurs when the vapor pressure of the fuel in the pipeline is equal to or greater than the actual pressure within the pipeline. A criterion for the vaporization threshold can be set. When the difference between the vapor pressure and the pressure is less than a certain threshold (for example, 0.05 MPa), the vaporization threshold is considered reached. By monitoring the temperature and pressure data within the pipeline and combining it with the set vaporization threshold, it is possible to identify in real time whether the pipeline has entered the vaporization risk zone.

[0127] Step S37: Evaluate the fuel vaporization risk based on the vaporization critical point.

[0128] In this embodiment, bubble formation and vaporization occur near the vaporization critical point, leading to fluid instability within the pipeline. Based on pressure and vapor pressure data, combined with the fuel's properties and flow conditions, the pipeline's vaporization risk is assessed. Assuming the vaporization risk threshold is set as bubble density or vaporization index, when it exceeds the set standard, the pipeline is considered to face a high vaporization risk. By continuously monitoring pipeline pressure, temperature, and flow conditions, vaporization risk data is updated in real time, and measures, such as reducing pressure or temperature, are implemented to prevent vaporization.

[0129] Preferably, step S4 is specifically as follows:

[0130] Step S41: identifying risky fuel pipelines in the three-dimensional simulation model of the gas station based on the risk of fuel vaporization;

[0131] In this example, a computational fluid dynamics (CFD) model is used to assess and identify areas with a high risk of vaporization, combining real-time pipeline pressure, temperature, vapor pressure, and flow rate data. A vaporization risk threshold is set (for example, a pipeline segment is considered risky when the vaporization index exceeds 0.6). By comparing this data with pipeline data from the 3D simulation model, the locations of risky fuel pipelines are identified, providing data support for subsequent processing.

[0132] Step S42: monitoring the fuel flow rate of the risk fuel pipeline;

[0133] In this embodiment, flow sensors are installed in identified risky fuel pipelines for real-time monitoring, capturing fuel flow velocity data within the pipeline. The sensor data is combined with the pipeline geometry and fuel properties to accurately calculate the flow velocity. A standard flow velocity value is set (for example, a normal flow velocity range of 0.5-3 m / s). Exceeding this range indicates turbulence or other abnormal flow conditions within the pipeline. This real-time monitoring data is used for subsequent flow classification and pipeline condition assessment.

[0134] Step S43: Classifying the risky fuel pipeline into flow types according to the fuel flow rate to obtain turbulent fuel pipeline data and laminar fuel pipeline data;

[0135] In this example, real-time flow velocity data from various points within the pipeline is collected and analyzed in conjunction with Reynolds number theory in fluid mechanics. The Reynolds number (Re) is a key indicator of fluid flow conditions and is calculated using the formula Re=(ρ*V*D) / μ, where ρ is the fluid density, V is the flow velocity, D is the pipe inner diameter, and μ is the fluid's dynamic viscosity. The Reynolds number is calculated by substituting the flow velocity data for each pipeline segment into the formula. To classify flow types, a Reynolds number threshold of 2000 is set. When the Reynolds number is greater than 2000, the flow within the pipeline is considered turbulent; if the Reynolds number is less than 2000, the flow is considered laminar. Using this criterion, all risky fuel pipelines are classified as either turbulent or laminar. Data for turbulent and laminar fuel pipelines is recorded separately based on flow velocity and Reynolds number. This data not only covers the flow conditions of each pipeline segment but also includes specific physical parameters such as flow velocity and Reynolds number, providing a detailed basis for subsequent pipeline location identification, material selection, and explosion-proof design. This flow type classification method can accurately identify the flow state in the pipeline, thereby providing data support for optimizing pipeline design and ensuring pipeline safety.

[0136] Step S44: Based on the turbulent fuel pipeline data, the 3D simulation model of the gas station is used to identify the location of the turbulent fuel pipeline to obtain the location of the turbulent fuel pipeline; based on the location of the turbulent fuel pipeline, carbon fiber composite material is filled to obtain carbon fiber composite material data;

[0137] In this embodiment, the geometry, flow velocity and flow type of each section of the pipeline are analyzed, and combined with the theory of fluid mechanics, it is determined which sections of the pipeline belong to the turbulent area. The location where turbulence occurs is determined by the relationship between the Reynolds number and the flow velocity, and the location of the turbulent pipeline is marked in the three-dimensional simulation model. For the identified turbulent fuel pipeline, carbon fiber composite materials are selected for filling design based on the high strength, corrosion resistance and other performance requirements of the material. The filling thickness of the carbon fiber composite material is usually set to 2-5mm according to the pipe diameter and the fluid flow pressure. The distribution of carbon fiber materials is calculated through the simulation model, and specific carbon fiber composite material data is obtained, which is incorporated into the subsequent design to ensure that the design scheme meets the strength and durability requirements of the pipeline.

[0138] Step S45: Based on the laminar fuel pipeline data, the laminar fuel pipeline position is identified on the three-dimensional simulation model of the gas station to obtain the laminar fuel pipeline position; based on the laminar fuel pipeline position, an epoxy resin explosion-proof coating is designed to obtain epoxy resin explosion-proof coating data;

[0139] In this embodiment, all laminar flow areas are marked by analyzing the flow type of each section of the pipeline and combining the flow velocity and Reynolds number data. The pipeline characteristics in the laminar flow area, such as low flow velocity and stable flow, usually do not produce obvious turbulence or pressure fluctuations. Based on these data, the epoxy resin explosion-proof coating is designed. During the design, the working pressure of the fluid in the pipeline and the external ambient temperature are considered to determine the thickness of the coating, which is generally 1-3mm. The choice of thickness ensures that it can effectively cope with the effects of gas explosions and pressure fluctuations, while taking into account long-term corrosion resistance. According to the specific location, size and pressure conditions of the pipeline, a specific application plan for the epoxy resin explosion-proof coating is formulated, and the epoxy resin explosion-proof coating data is generated in the three-dimensional simulation model. These data will be used for subsequent engineering implementation to ensure that the pipelines in the laminar flow area meet the design requirements of explosion protection and pressure resistance.

[0140] Step S46: Integrate the carbon fiber composite material data and the epoxy resin explosion-proof coating data to obtain explosion-proof material data;

[0141] In this example, data on carbon fiber composite materials and epoxy resin explosion-proof coatings are integrated to aggregate the data and analyze their respective roles in pipeline locations. In turbulent flow areas, carbon fiber composites primarily enhance pipeline strength and corrosion resistance; in laminar flow areas, epoxy resin coatings primarily provide explosion protection and pipeline protection. This integrated explosion-proof material data includes detailed information such as material type, thickness, and coating area, providing data support for gas station safety design.

[0142] Step S47: Designing an inert gas explosion-proof device for the three-dimensional simulation model of the gas station according to the risk of fuel vaporization, and obtaining inert gas explosion-proof device data;

[0143] In this embodiment, an inert gas release device is installed in pipeline areas with a higher risk of vaporization to mitigate potential vaporization. During design, an activation threshold is determined based on the pipeline's vaporization risk index (for example, when the vaporization risk index exceeds 0.7). Then, based on pipeline fluid vaporization pressure, temperature, and flow rate data, an appropriate inert gas (typically nitrogen) is selected, and the required gas flow rate and release pressure are calculated. The designed inert gas release device must be compatible with the pipeline's pressure control system to ensure timely and stable gas release when the risk of vaporization increases, preventing bubble formation or increasing vaporization levels. Furthermore, the relationship between the gas release volume and the flow rate and temperature within the pipeline is further considered to ensure that the inert gas release effectively suppresses vaporization. Finally, based on these design parameters, relevant data for the inert gas explosion-proof device is generated and integrated into a three-dimensional simulation model of the gas station to facilitate subsequent engineering implementation and real-time monitoring.

[0144] Step S48: Integrate the explosion-proof material data and the inert gas explosion-proof device data into the gas station three-dimensional simulation model to generate a gas station three-dimensional simulation optimization model.

[0145] In this example, explosion-proof material data derived from the design of carbon fiber composite materials and epoxy resin explosion-proof coatings is integrated with data from inert gas explosion-proof devices designed based on a gasification risk assessment. This data includes the type, thickness, location, and applicable area of the explosion-proof material, as well as parameters such as the installation location, activation threshold, gas flow rate, and pressure of the inert gas explosion-proof device. Using a 3D simulation platform, this data is accurately embedded into a 3D simulation model of the gas station, ensuring that explosion-proof measures for all risky pipeline sections are fully reflected. The locations of all identified risky pipeline sections are accurately demarcated within the 3D model, particularly those with a higher risk of gasification. Subsequently, based on the design data for the carbon fiber composite materials and epoxy resin coatings determined in the previous step, they are mapped to the pipeline surfaces in these high-risk areas, accurately recording the distribution of the explosion-proof materials. Simultaneously, the design parameters of the inert gas explosion-proof device (such as the specific location of the equipment, gas flow rate, pressure requirements, and activation conditions) are integrated into the 3D model, indicating the device's installation points and operating status. The integrated 3D simulation optimization model intuitively displays the specific location and configuration of all explosion-proof materials and inert gas explosion-proof devices. This optimization model clearly demonstrates the effectiveness of the placement of various explosion-proof devices and materials, assessing their impact on gas station safety. The model also enables dynamic monitoring and risk assessment during gas station operations. By simulating performance under different vaporization risk conditions, explosion-proof designs can be adjusted and optimized in a timely manner to maximize gas station safety. Furthermore, simulations can proactively identify system vulnerabilities or deficiencies in explosion-proof measures, allowing them to be corrected before actual implementation, providing technical support for gas station safety management and emergency response.

[0146] Preferably, step S47 is specifically as follows:

[0147] Step S471: identifying high-risk fuel vaporization structures in the three-dimensional simulation model of the gas station based on the fuel vaporization risk;

[0148] In this example, real-time data such as pressure, temperature, flow rate, and vapor pressure is collected from sensors installed on each pipeline segment within the gas station. Based on the theory of vaporization in fluid mechanics, this data is input into a CFD (computational fluid dynamics) model for analysis, calculating a vaporization risk index for each pipeline segment. Assuming a vaporization risk threshold of 0.7, when the vaporization risk index for a pipeline segment exceeds this threshold, the segment is considered a high-risk fuel vaporization structure. By comparing the data for each pipeline segment, the locations of these high-risk structures are identified and highlighted in the 3D model, ensuring precise identification and location of risk areas.

[0149] Step S472: Arranging inert gas injection points for high-risk fuel gasification structures to obtain inert gas injection points;

[0150] In this embodiment, the location of the injection point is determined based on the high-risk area. Specifically, the location of the injection point is selected based on parameters such as the degree of vaporization, pressure and temperature of the fluid in the pipeline. The inert gas injection point is usually arranged in the pipeline section close to the vaporization risk area to ensure that the inert gas can effectively cover the vaporization risk area and prevent the occurrence of fuel vaporization. The location of each injection point needs to take into account factors such as the fluid flow direction and pipeline elbows to avoid setting the injection point in an area where the fluid flow is restricted, thereby affecting the injection effect. The number and location of the injection points should be reasonably planned according to the specific size and pipeline configuration of the high-risk area to ensure that the inert gas can be evenly distributed throughout the risk area. The three-dimensional simulation model can be used to simulate the gas injection effect and optimize the layout of the injection points.

[0151] Step S473: performing an inert gas injection simulation based on the inert gas injection point, and performing an inert gas leakage analysis on the simulation process to obtain inert gas leakage data;

[0152] In this embodiment, a gas injection simulation is performed based on the arranged inert gas injection points. The injection process is simulated using a CFD model to simulate the flow behavior of an inert gas (such as nitrogen). Parameters that need to be input include the flow rate, flow rate, temperature, and physical properties of the inert gas (such as density, viscosity, etc.). By simulating the injection process, the distribution of the gas in the pipeline and its flow path are monitored, while taking into account the diffusion and transmission behavior of the gas under different pressure and temperature conditions. For the leakage point, further inert gas leakage analysis is performed to monitor whether there is any gas leakage, and inert gas leakage data is generated based on data such as gas leakage volume, leakage path, and leakage rate. These data will be used for subsequent gas leakage path identification and explosion-proof barrier design.

[0153] Step S474: identifying a gas leakage path based on the inert gas leakage data;

[0154] In this embodiment, the location of the leakage point is determined by analyzing the leakage data in the simulation results. It is necessary to determine the main leakage path by calculating the pressure distribution and flow velocity distribution of the gas flow and the location of the leakage point in the pipeline. The identification of the leakage path depends on the CFD simulation results. The specific location and length of the leakage path are calibrated in combination with data such as the gas leakage amount, flow direction and leakage pressure. In particular, attention should be paid to parts prone to leakage such as pipeline connection points and elbows to ensure complete identification of the leakage path. Through accurate identification of the gas leakage path, data support can be provided for the subsequent optimization of injection parameters and explosion-proof barrier design.

[0155] Step S475: Optimizing gas injection parameters according to the gas leakage path;

[0156] In this embodiment, gas injection parameters are further optimized based on the gas leakage path. Input parameters include the length of the leakage path, the location of the leak point, and the amount of leaked gas, all of which are derived from the gas leakage path identification data from the previous stage. Computational fluid dynamics (CFD) tools are used to establish a gas flow model. This model combines the physical properties of the gas, such as temperature, pressure, density, and viscosity, with the geometric parameters of the pipeline, such as the inner diameter, length, and bend angle, to create a complete gas flow simulation model. By simulating gas diffusion along the leakage path, the distribution of the injected gas along the leakage path is calculated. Next, injection parameters, including injection pressure, injection rate, and injection angle, are adjusted based on the simulation results. The injection pressure is adjusted based on the pressure difference between the inside and outside of the pipeline and the gas flow rate at the leak point to ensure that the gas can effectively traverse the pipeline and reach the leakage area. The injection angle is set based on the geometry of the leakage path, especially when there are pipe bends or other complex structures, and the injection angle needs to be adjusted to the optimal position. The injection rate is determined based on the gas flow rate at the leak point to ensure that the gas flow effectively covers the leakage area within the pipeline. In addition, external environmental factors such as temperature and pressure affect the density and flow characteristics of the gas, so these are also factored into the optimization process. In particular, the gas injection parameters are adjusted accordingly in low- and high-temperature environments. Through multiple rounds of simulation, the injection parameters are adjusted until the optimal injection effect is achieved. The optimized parameters include an injection pressure of 5-10 MPa, an injection rate of 30-50 m³ of gas per hour, and an injection angle adjusted between 30° and 45° based on the specific layout of the leak path. The ultimate goal is to ensure that the inert gas evenly covers the leak path and forms an effective protective layer, thereby effectively reducing the risk of gas leakage.

[0157] Step S476: Identify the main leakage path according to the gas leakage path; design a gas explosion-proof barrier for the main leakage path to obtain gas explosion-proof barrier data;

[0158] In this embodiment, the leakage path is usually the path with the largest leakage or the widest impact range, and requires special attention. By analyzing the flow characteristics of the gas leakage path, the location of the main leakage path is determined, and the explosion-proof barrier is designed according to its leakage nature and risk level. The design of the explosion-proof barrier needs to take into account the external environment of the pipeline, the nature of the leaking gas, the leakage rate, and the performance requirements of the barrier material. The design of the barrier includes selecting suitable explosion-proof materials, determining the thickness and shape of the barrier, and setting the activation conditions of the explosion-proof device. Common explosion-proof barrier design materials include steel, composite materials, etc., and their thickness and strength are accurately calculated according to the flow rate and pressure of the leaking gas. After completing the barrier design, the data of the gas explosion-proof barrier is generated for use in the subsequent deployment of explosion-proof devices.

[0159] Step S477: Integrate the gas injection parameters and the gas explosion-proof barrier data to obtain inert gas explosion-proof device data.

[0160] In this example, optimized injection parameters (such as injection pressure, injection angle, and injection rate) are combined with detailed data from the explosion barrier design to form a complete explosion-proof device design plan. This data is applied to a 3D simulation model of the gas station based on the station's pipeline layout and leakage risk areas, ensuring that the inert gas explosion-proof device covers all high-risk areas. During the integration process, the synergy between the various devices must be considered to ensure that the gas injection and explosion barrier can function together in the event of a leak, providing comprehensive safety protection. Ultimately, the generated inert gas explosion-proof device data will provide a basis for gas station safety management and emergency response, ensuring timely and effective response to gas leaks.

[0161] Preferably, step S476 is specifically as follows:

[0162] Perform gas diffusion simulation based on gas leakage paths and identify the main leakage paths during the simulation;

[0163] In this embodiment, the gas leakage path identification data from the previous stage is used to extract parameters such as the leak point's location, gas type, leakage rate, temperature, and pressure. These parameters are used to simulate gas diffusion using CFD (computational fluid dynamics) software, based on fluid mechanics theory. During the simulation, initial conditions are set, including the leak location, pressure differential, physical properties of the gas, and ambient temperature, to ensure that the simulation accurately reflects the actual leakage situation. During the simulation, the gas diffusion path within the pipeline or structure is calculated to determine the gas concentration distribution. Through the simulation process, the primary gas diffusion path—that is, the path with the highest gas flow rate and widest diffusion range—can be identified and calibrated as the primary leakage path. Data on the primary leakage path includes the path's spatial location, gas flow rate, gas concentration distribution, and its variations. This data provides the basis for subsequent barrier design.

[0164] Identifying a gas diffusion path based on the main leakage path, and setting a gas barrier according to the gas diffusion path to obtain gas barrier data;

[0165] In this embodiment, the diffusion path encompasses not only the direct path of gas leakage but also the area of gas diffusion into the surrounding environment. This requires CFD simulation analysis. Specifically, CFD (computational fluid dynamics) software is used to simulate the diffusion of a gas leak. Using known parameters such as leak rate, leak location, gas type, air pressure, ambient temperature, and wind speed, the flow and diffusion of gas in the pipeline and surrounding space are simulated. During the simulation, the gas concentration is tracked over time to determine the gas diffusion range and velocity, and the area of highest gas concentration and the gas diffusion boundary are demarcated. Based on this data, the gas diffusion path and its impact range can be determined. Once the gas diffusion paths are identified, the next task is to design a gas barrier based on the characteristics of these paths. Barrier design requires consideration of multiple factors, including gas flow direction, flow rate, gas concentration, ambient temperature, and the presence of obstacles. Based on these conditions, the gas barrier is designed with appropriate materials and structures to ensure it effectively prevents gas diffusion. Barrier materials typically possess high gas barrier properties, such as polymers like polyethylene and polyurethane, or metal barriers like steel, which offer excellent gas permeability resistance and can prevent further gas diffusion into hazardous areas. The placement of gas barriers must be strictly based on specific data about gas diffusion paths, such as the gas diffusion rate and the peak location of gas concentration, to determine the optimal location and thickness of the barrier. These parameters can be used to calculate design requirements for the barrier's thickness, shape, and sealing properties, ensuring that gases are effectively isolated outside the barrier and preventing further spread of leaked gas. The design process also requires consideration of the barrier's installation method to ensure reliable operation in the actual environment and to avoid degradation of barrier performance due to environmental factors such as high temperature and high humidity. Gas barrier design data should include the barrier's location, selected material, thickness, structural design, sealing properties, and installation method. This data provides the technical basis for implementing safety measures at gas stations.

[0166] Mark key path points based on the main leakage path, set up adsorption barriers according to the key path points, and obtain adsorption barrier data;

[0167] In this embodiment, critical points in the gas diffusion process are further identified based on the gas diffusion path. These critical points typically include points of maximum gas concentration, areas of rapid gas diffusion, and areas of secondary leakage. By analyzing the spatiotemporal distribution of the gas using a gas flow model, particularly the temporal variation of concentration, areas of higher risk during the diffusion process are identified. Specifically, CFD simulations are used to calculate the gas concentration distribution over different time periods, identifying points of highest concentration and areas of rapid diffusion. These critical points require precise calibration to ensure effective identification of areas of high risk during the gas diffusion process, particularly those where gas concentrations rise rapidly or leakage rates are high. Adsorption barriers are designed and installed at these identified key points. The function of the adsorption barrier is to reduce the gas concentration in that area by adsorbing gas molecules, thereby reducing the potential threat to the environment and equipment. When selecting an adsorbent material, the physicochemical properties of the gas, such as the size, polarity, and molecular weight of the gas molecules, must be considered. These factors directly influence the choice of adsorbent material. Commonly used adsorbent materials include activated carbon and molecular sieves. These materials have high specific surface areas and adsorption capacities, effectively adsorbing gas molecules and reducing gas concentration. The placement of the adsorption barrier is determined based on the calibration results of key points. The adsorption barrier should be set in areas with the highest gas concentration or areas with faster gas diffusion rates. The thickness of the adsorption barrier is usually set at 3-5mm, and the specific thickness is determined based on the gas concentration, diffusion rate, and characteristics of the adsorption material. The design of the adsorption barrier also needs to consider the installation method to ensure that the adsorption material can continue to function effectively and prevent the adsorption effect from decreasing due to time and environmental changes. Through these steps, the design data of the adsorption barrier is finally obtained, including the location of the adsorption barrier, the selected adsorption material, thickness, layout method, and installation requirements, etc., which provide effective support for subsequent explosion-proof design.

[0168] Calculate gas leakage rate based on gas leakage path and predict explosion risk based on volume leakage rate;

[0169] In this embodiment, the calculation of the leakage rate requires comprehensive consideration of parameters such as the gas pressure and temperature at the leak point, the properties of the gas within the pipeline, the leakage area, and the pressure differential at the time of the leak. Using this data, the gas dynamics equation can be applied to calculate the specific leakage rate, typically expressed as flow rate per minute (m³ / min). Based on data such as the gas leakage rate, ambient temperature, and pressure, the likelihood of gas accumulation and the risk of causing an explosion are predicted. To ensure accuracy, a gas concentration threshold is set based on the gas's lower explosion limit (LEL) and upper explosion limit (UEL). Once the concentration reaches or exceeds the LEL, a potential explosion risk is determined. The specific leakage rate value depends on parameters such as the pipeline's inner diameter, the leakage area, the gas flow rate, and the pressure differential.

[0170] Determine the high explosion risk path of the gas leakage path based on the explosion risk, and set up physical barriers based on the high explosion risk path to obtain physical barrier data;

[0171] In this embodiment, gas leakage paths are further evaluated based on explosion risk. By comparing the leak rate, gas concentration, and explosion hazard of different paths, leak paths with high explosion risk are identified. Specifically, a leak rate threshold is determined based on the relationship between the gas leak rate and the explosion threshold. When the leak rate exceeds this threshold, the path is considered to have a high explosion risk. Furthermore, the gas concentration level is compared with the lower explosive limit (LEL) and the lower explosive limit (UEL). When the gas concentration approaches or exceeds the lower explosive limit (LEL), the risk of the path increases further. Based on these leak path parameters, a multi-dimensional risk assessment is performed to comprehensively determine the high explosion risk of the leak path. By analyzing data such as leak rate and gas concentration, higher-risk leak paths are identified and designated as high explosion risk paths. Physical barriers are then designed along these high-risk paths. The design of the physical barriers primarily considers the barrier material's strength, high-temperature resistance, and impact resistance. According to the type and properties of the leaked gas and the size of the explosion risk, select appropriate explosion-resistant materials, such as steel plates, concrete, etc. These materials have high impact resistance, high temperature resistance and isolation properties, and can effectively prevent gas leakage and spread and prevent explosion accidents. In the design of the thickness of the barrier, it is usually set to 10-20mm. The specific thickness depends on the pressure and temperature of the leaking gas and the assessment results of the explosion risk. The installation position of the barrier needs to be connected with the risk point of the gas leakage path to ensure that the barrier can cover the key areas of gas leakage to the greatest extent and prevent gas diffusion. The design data of the physical barrier will include detailed parameters such as the specific location of the barrier, the selected material, the thickness of the barrier, impact strength, high temperature resistance and installation method, to ensure that in the event of a leak, the gas can be effectively prevented from further diffusion and the risk of explosion can be reduced.

[0172] The gas barrier data, adsorption barrier data and physical barrier data are integrated to obtain the gas explosion barrier data.

[0173] In this example, data from various types of barriers are integrated to form a complete gas explosion barrier design. This data includes barrier type (gas barrier, adsorption barrier, physical barrier), location, material, thickness, installation method, and more. By integrating this data, a systematic explosion barrier network is constructed to effectively address the risks of gas leaks and explosions within gas stations. The integration process ensures that the various barriers are rationally arranged, covering all high-risk areas and avoiding blind spots. Furthermore, the synergy between the barriers is ensured to minimize the risk of gas leaks.

[0174] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0175] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. An integrated design method for a three-dimensional simulation model of a skid-mounted gas station, characterized in that: The following steps are involved: Step S1: Obtaining a skid-mounted gas station structural drawing; constructing a three-dimensional gas station component according to the skid-mounted gas station structural drawing; Perform virtual assembly based on the three-dimensional components of the gas station to generate a three-dimensional simulation model of the gas station; Step S2: Obtain fuel data and transmit it to the three-dimensional simulation model of the gas station, and perform fuel flow simulation to generate fuel flow data; Detect oil reflux based on fuel flow data to obtain oil reflux data; Perform fuel pipeline cavitation detection based on oil reflux data to obtain fuel pipeline cavitation data; Step S3: Marking the pipeline cavitation location based on the fuel pipeline cavitation data, and continuously monitoring the fuel pipe body heat load at the pipeline cavitation location; and assessing the fuel vaporization risk based on the fuel pipe body heat load; Step S4: filling the three-dimensional simulation model of the gas station with explosion-proof materials based on the risk of fuel vaporization to obtain explosion-proof material data; designing an inert gas explosion-proof device based on the three-dimensional simulation model of the gas station to obtain inert gas explosion-proof device data; Integrate the explosion-proof material data and the inert gas explosion-proof device data into the gas station three-dimensional simulation model to generate a three-dimensional simulation optimization model of the gas station. Step S4 is specifically as follows: Step S41: identifying risky fuel pipelines in the three-dimensional simulation model of the gas station based on the risk of fuel vaporization; Step S42: monitoring the fuel flow rate of the risk fuel pipeline; Step S43: Classifying the risky fuel pipeline into flow types according to the fuel flow rate to obtain turbulent fuel pipeline data and laminar fuel pipeline data; Step S44: Based on the turbulent fuel pipeline data, the 3D simulation model of the gas station is used to identify the location of the turbulent fuel pipeline to obtain the location of the turbulent fuel pipeline; based on the location of the turbulent fuel pipeline, carbon fiber composite material is filled to obtain carbon fiber composite material data; Step S45: Based on the laminar fuel pipeline data, the laminar fuel pipeline position is identified on the three-dimensional simulation model of the gas station to obtain the laminar fuel pipeline position; based on the laminar fuel pipeline position, an epoxy resin explosion-proof coating is designed to obtain epoxy resin explosion-proof coating data; Step S46: Integrate the carbon fiber composite material data and the epoxy resin explosion-proof coating data to obtain explosion-proof material data; Step S47: Designing an inert gas explosion-proof device for the three-dimensional simulation model of the gas station according to the risk of fuel vaporization, and obtaining inert gas explosion-proof device data; Step S48: Integrate the explosion-proof material data and the inert gas explosion-proof device data into the gas station three-dimensional simulation model to generate a gas station three-dimensional simulation optimization model.

2. The integrated design method for a skid-mounted gas station three-dimensional simulation model according to claim 1, characterized in that: Step S1 is specifically as follows: Step S11: Obtaining a skid-mounted gas station structural drawing; Step S12: identifying the tank structure based on the skid-mounted gas station structural drawing; Step S13: Identifying the pipeline network structure based on the skid-mounted gas station structural drawing; Step S14: Merge the gas station structure according to the storage tank structure and the pipeline network structure to obtain a three-dimensional gas station component; Step S15: Perform virtual assembly based on the three-dimensional components of the gas station to generate a three-dimensional simulation model of the gas station.

3. The integrated design method for a three-dimensional simulation model of a skid-mounted gas station according to claim 2, characterized in that: Step S15 is specifically as follows: Step S151: performing component interference detection based on the three-dimensional components of the gas station to obtain component interference data; Step S152: Optimizing component spacing based on component interference data; Step S153: adjusting the component installation position based on the component spacing; Step S154: reconstructing component connection relationships according to component installation positions; Step S155: Perform virtual assembly based on the component connection relationship, wherein the assembly alignment accuracy is set to ≤1mm and the simulation time step is 0.01-1s, and generate a three-dimensional simulation model of the gas station.

4. The integrated design method for a skid-mounted gas station three-dimensional simulation model according to claim 1, characterized in that: The fuel flow simulation in step S2 includes: Obtain fuel data and perform standardization processing to obtain standardized fuel data; Transmit standardized fuel data to the gas station 3D simulation model, and upload the gas station 3D simulation model to the simulation software; Perform fuel flow simulation in the simulation software, setting the flow range to 5-200m³ / h and the flow velocity range to 0.1-5m / s; The fuel pressure distribution is simulated in the simulation software, and the initial pressure of the pipeline is set to 0.1-5MPa and the pressure loss coefficient is set to 0.01-0.1; The fuel temperature field distribution was simulated in the simulation software, with the fuel inlet temperature set to -20°C to 80°C, the ambient temperature to 30°C to 50°C, and the heat transfer coefficient to 10-500W / (m²·K); Run the fuel flow simulation program in the simulation software to obtain fuel flow data.

5. The integrated design method for a skid-mounted gas station three-dimensional simulation model according to claim 1, characterized in that: The oil reflux detection in step S2 includes: extracting a fuel flow video sequence based on the fuel flow data; Preprocessing the fuel flow video sequence, including grayscale processing, Gaussian blurring, and edge detection, to obtain a preprocessed fuel flow video sequence; Identifying the flow direction of the pre-processed fuel flow video sequence; calculating the flow rate of the pre-processed fuel flow video sequence; Construct an optical flow vector field based on the flow direction and flow rate; Calculate the curl of the optical flow vector field; identify the vortex area of the optical flow vector field based on the curl; The oil reflux is detected based on the vortex area to obtain the oil reflux data.

6. The integrated design method for a three-dimensional simulation model of a skid-mounted gas station according to claim 1, characterized in that: The fuel pipeline cavitation detection in step S2 includes: Mark the oil return area of the gas station 3D simulation model based on the oil return data; Detect pressure gradients in the oil reflux area; mark low-pressure areas in the oil reflux area based on the pressure gradients; Calculate the turbulence intensity in the low-pressure area; determine the turbulence cavitation value based on the preset cavitation critical value and turbulence intensity to obtain the turbulence cavitation value; According to the turbulent cavitation value, the suspected cavitation area is identified in the low-pressure area to obtain the suspected cavitation area; Based on performing laser transmission to the suspected cavitation area, laser transmission data is obtained; Calculate the transmittance of the laser transmission data; determine the bubble area of the suspected cavitation area based on the transmittance; Monitor pipeline pressure in bubble areas and draw pipeline pressure graphs; Identify periods of rapid pressure drop based on pipeline pressure graphs; The fuel pipeline cavitation detection is performed according to the period of rapid pressure drop to obtain the fuel pipeline cavitation data.

7. The integrated design method for a three-dimensional simulation model of a skid-mounted gas station according to claim 1, characterized in that: Step S3 is specifically as follows: Step S31: Marking the pipeline cavitation location based on the fuel pipeline cavitation data; Step S32: continuously monitoring the heat load of the fuel pipe body at the cavitation location of the pipeline; Step S33: Evaluating the fuel pipe pressure based on the fuel pipe thermal load; Step S34: Calculating the fuel pipe body temperature based on the fuel pipe body heat load; Step S35: determining the fuel vapor pressure according to the fuel pipe temperature; Step S36: Identifying the vaporization critical point based on the fuel vapor pressure and the fuel pipe pressure; Step S37: Evaluate the fuel vaporization risk based on the vaporization critical point.

8. The integrated design method for a skid-mounted gas station three-dimensional simulation model according to claim 1, characterized in that: Step S47 is specifically as follows: Step S471: identifying high-risk fuel vaporization structures in the three-dimensional simulation model of the gas station based on the fuel vaporization risk; Step S472: Arranging inert gas injection points for high-risk fuel gasification structures to obtain inert gas injection points; Step S473: performing an inert gas injection simulation based on the inert gas injection point, and performing an inert gas leakage analysis on the simulation process to obtain inert gas leakage data; Step S474: identifying a gas leakage path based on the inert gas leakage data; Step S475: Optimizing gas injection parameters according to the gas leakage path; Step S476: Identify the main leakage path according to the gas leakage path; design a gas explosion-proof barrier for the main leakage path to obtain gas explosion-proof barrier data; Step S477: Integrate the gas injection parameters and the gas explosion-proof barrier data to obtain inert gas explosion-proof device data.

9. The integrated design method for a three-dimensional simulation model of a skid-mounted gas station according to claim 8, characterized in that: Step S476 is specifically as follows: Perform gas diffusion simulation based on gas leakage paths and identify the main leakage paths during the simulation; Identifying a gas diffusion path based on the main leakage path, and setting a gas barrier according to the gas diffusion path to obtain gas barrier data; Mark key path points based on the main leakage path, set up adsorption barriers according to the key path points, and obtain adsorption barrier data; Calculate gas leakage rate based on gas leakage path and predict explosion risk based on volume leakage rate; Determine the high explosion risk path of the gas leakage path based on the explosion risk, and set up physical barriers based on the high explosion risk path to obtain physical barrier data; The gas barrier data, adsorption barrier data and physical barrier data are integrated to obtain the gas explosion barrier data.

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