Model design method and system for long-distance steam supply pipeline

Abstract

The invention relates to the technical field of model design, in particular to a model design method and system for a long-distance steam supply pipeline. The method comprises the following steps: acquiring the positions of a pipeline starting point and a pipeline target point; performing mid-distance landform analysis based on the pipeline starting point and the pipeline target point to generate mid-distance landform division data, the mid-distance landform division data including cross-road landform data and cross-river landform data; performing basic pipeline modeling according to the positions of the pipeline starting point and the pipeline target point, and generating basic pipeline model design data; and secondary internal stress analysis of the pipeline sleeve is carried out on the basic pipeline model design data through the cross-road landform data, and pipeline cross-road internal stress data are generated. According to the method, the problems that in the prior art, under the complex terrain, the pipeline design precision is insufficient, stress analysis is limited, and comprehensive optimization is insufficient are solved by introducing an optimization design method combining middle-distance landform analysis, pipeline stress secondary analysis and natural vibration analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of model design, and in particular to a model design method and system for a long-distance steam supply pipeline. Background Art

[0002] Early design methods relied on manual calculations and empirical judgment, making it difficult to account for the impact of complex terrain and environmental factors on pipeline stability and operational efficiency. This resulted in low design efficiency and a high risk of safety hazards. With the development of computer-aided design (CAD) technology, digital modeling and finite element analysis (FEA) have gradually been introduced into pipeline design, leading to improvements in stress analysis and geomorphic adaptability. However, current technologies still face several challenges, primarily in the following areas: Despite progress in mid-range geomorphic analysis and the generation of geomorphic data across roads and rivers, the accuracy and adaptability of existing technologies in complex terrain still need to be improved. The impact of complex terrain on pipeline structures is not fully considered, making design optimization difficult, especially when crossing large natural obstacles. Current pipeline casing stress analysis methods are primarily based on traditional static models, ignoring the effects of dynamic loads (such as earthquakes and temperature fluctuations) on pipelines. Furthermore, natural vibration analysis of river crossings often fails to fully consider the dynamic behavior of suspended pipe sections, resulting in less robust designs. Consequently, current technologies lack a comprehensive, dynamic optimization process, making it difficult to provide optimal pipeline design solutions in complex and changing geographical environments. Summary of the Invention

[0003] Based on this, it is necessary to provide a model design method and system for long-distance steam supply pipelines to solve at least one of the above technical problems.

[0004] To achieve the above object, a model design method for a long-distance steam supply pipeline is provided, the method comprising the following steps:

[0005] Step S1: obtaining the positions of the pipeline starting point and the pipeline target point; performing mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, wherein the mid-range landform division data includes cross-road landform data and cross-river landform data;

[0006] Step S2: Basic pipeline modeling is performed based on the locations of the pipeline starting point and the pipeline target point to generate basic pipeline model design data; secondary internal stress analysis of the pipeline casing is performed on the basic pipeline model design data using the cross-road topography data to generate pipeline cross-road internal stress data; suspended pipe section self-vibration analysis is performed on the basic pipeline model design data using the cross-river topography data to generate pipeline cross-river self-vibration data;

[0007] Step S3: Optimizing the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and the pipeline crossing road internal stress data, thereby generating pipeline segment design optimization data; and confirming the pipeline segment connection points of the basic pipeline model design data based on the pipeline segment design optimization data.

[0008] Step S4: Analyze the influence of pipeline supply flow dynamics on pipeline segment connection points, and optimize the basic pipeline model design data according to the analysis results and pipeline segment design optimization data, thereby generating a design model for the long-distance steam supply pipeline.

[0009] This invention ensures the stability and safety of long-distance gas supply pipelines in diverse terrain conditions through refined analysis and optimization. First, by obtaining the locations of the pipeline's starting and target points and conducting mid-range terrain analysis, the pipeline design is ensured to be adaptable to complex terrain conditions. By segmenting cross-road and cross-river terrain data, detailed terrain information is provided for subsequent pipeline design, avoiding terrain conflicts or special requirements. Next, basic pipeline modeling and a detailed analysis of terrain factors are performed to ensure that the pipeline structure in road or river crossing areas is not subject to excessive internal stress or unsafe vibration. Secondary internal stress analysis and natural vibration analysis provide scientific assurance of pipeline stability, reducing the risk of pipeline rupture or failure. Then, through design optimization based on cross-road and cross-river data, the pipeline structure is made more adaptable to complex terrain conditions. Pipeline segment design optimization helps further enhance the stability of pipeline connection points despite the influence of terrain factors, thereby improving the pipeline's long-term reliability and durability. Finally, an analysis of the impact of gas flow patterns on the connection points of pipeline segments is performed, allowing pipeline design to not only optimize the structure but also the airflow transmission efficiency. Through comprehensive analysis and design optimization, the pipeline design model finally generated can effectively reduce energy loss and ensure smooth airflow during long-distance steam supply, thereby improving the overall function and work efficiency of the pipeline. The entire process not only enhances the accuracy of pipeline design and ensures efficient operation under complex terrain, but also ensures the stability and risk resistance of the pipeline through in-depth stress and vibration analysis, further improves the design rationality of pipeline section connection points, reduces maintenance requirements and potential failures, and optimizes airflow efficiency and energy transmission to improve the overall performance of the gas supply system. Therefore, the present invention solves the problems of insufficient pipeline design accuracy, stress analysis limitations and insufficient comprehensive optimization under complex terrain in the existing technology by introducing an optimization design method that combines mid-distance terrain analysis, pipeline stress secondary analysis and self-vibration analysis.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: obtaining the pipeline starting point and pipeline target point positions based on GPS;

[0012] Step S12: Calculate the pipeline plane straight-line distance according to the pipeline starting point and the pipeline target point, and calculate the mean of the pipeline plane straight-line distance to generate the pipeline center distance point;

[0013] Step S13: collecting digital elevation data at the pipeline center distance point to obtain pipeline center elevation data; analyzing the terrain profile of the pipeline center elevation data to obtain pipeline terrain profile data;

[0014] Step S14: Identify the terrain information of the pipeline center distance point, and classify the landform type based on the terrain information and pipeline terrain profile data to generate medium-distance landform division data, where the medium-distance landform division data includes cross-road landform data and cross-river landform data.

[0015] This invention uses GPS to obtain the locations of the pipeline's starting and target points and calculates the pipeline's plane straight-line distance, ensuring that pipeline design is based on precise geographic coordinates, effectively avoiding positioning errors during subsequent design and construction. By collecting digital elevation data and analyzing terrain profiles, a detailed understanding of topographic variations along the pipeline route is achieved, providing a scientific basis for pipeline laying and support, and ensuring pipeline stability in complex terrain conditions. Based on pipeline center elevation data and terrain information, key terrain features, such as mountains and rivers, can be identified and classified, effectively identifying areas crossing roads and rivers. This helps designers optimize pipeline routes and avoid unnecessary conflicts and instability. By generating cross-road and cross-river topographic data, these potential influencing factors can be considered during the design phase, ensuring that the pipeline's structural design in road or river crossing areas can withstand the stress and vibration caused by terrain changes and reduce risks during long-term operation. The results of the topographic classification provide detailed data support for subsequent pipeline design and construction, enabling scientific planning of pipeline layout plans and identifying construction difficulties or special requirements in advance, laying the foundation for the smooth progress of the project.

[0016] Preferably, the landform type classification based on the land feature information and the pipeline terrain profile data in step S14 includes:

[0017] When any of the following conditions occurs, it is determined to be a cross-road landform and cross-road landform data is obtained: the road feature point in the terrain information intersects the pipeline path in the pipeline terrain profile data, and the height change of the pipeline path at the intersection is greater than 50 cm, and the ground undulation amplitude of the road section is greater than 20%;

[0018] When any of the following conditions occurs, it is determined to be a cross-river landform and cross-river landform data is obtained: the river features in the terrain information coincide with the pipeline path in the pipeline terrain profile data, the bottom height of the pipeline path is less than 10 meters below the river water level, the river width is greater than 50 meters, and the flow velocity is greater than 2m / s;

[0019] Integrate cross-road landform data and cross-river landform data into medium-range landform division data.

[0020] The present invention can accurately identify the cross-road and cross-river landforms along the pipeline through a detailed analysis based on terrain information and pipeline terrain profile data. This refined judgment method ensures that the pipeline design can reasonably respond to the terrain and environmental challenges encountered, avoiding unexpected problems during later construction. By judging the height changes at road intersections and the undulations of the road surface, it is possible to identify the specific areas where the pipeline passes through the road. This provides necessary data support for the design of pipelines across road sections, avoiding uneven stress or damage to the pipeline due to ground undulations or excessive height changes. At the same time, the judgment of cross-river landforms can ensure the safety of pipeline designs in river areas, especially under the influence of environmental factors such as river water level and flow rate, ensuring the stable operation of the pipeline. Through the precise classification and data collection of cross-road and cross-river landforms, detailed landform data is provided for pipeline design, which enables designers to carry out targeted design optimization according to different terrain features, such as strengthening the structural support of the pipeline in the road section or adjusting the pipeline depth in the river section, ensuring the safety and long-term stability of the pipeline in complex terrain. By proactively identifying factors influencing cross-road and river topography, construction teams can prepare in advance to avoid unexpected situations such as terrain changes and river flooding that could impact construction progress or lead to accidents, thereby improving project safety and efficiency. The integration of cross-road and river topography data provides an accurate foundation for mid-range topography delineation, ensuring that pipeline design can be tailored to the terrain. This improves the scientific nature, accuracy, and feasibility of the design process and reduces the need for subsequent maintenance and adjustments.

[0021] Preferably, in step S2, determining the length of the gas supply pipeline according to the positions of the pipeline starting point and the pipeline target point and performing basic pipeline modeling includes:

[0022] The actual length of the pipeline is calculated based on the mid-range landform division data at the starting point and target point of the pipeline to obtain the actual length data of the pipeline;

[0023] Based on the actual length data of the pipeline and the predetermined path of the pipeline, the pipeline path modeling is performed to generate pipeline path model data;

[0024] Analyze pipeline path model data by pipeline diameter, material, and load requirements to generate basic pipeline design parameter data;

[0025] Structural stability and bearing capacity are evaluated based on basic pipeline design parameter data to generate basic pipeline model design data.

[0026] The present invention calculates the actual length of the pipeline by mid-range landform division data, ensuring that the pipeline design can be based on real geographical conditions rather than theoretical estimates, thereby reducing length errors caused by terrain changes or irregular paths. This accurate pipeline length calculation provides a solid foundation for subsequent pipeline construction. The pipeline path modeling is performed by combining the actual pipeline length data with the predetermined path to generate pipeline path model data. This process ensures that the pipeline design takes into account the actual terrain conditions, avoids unforeseen obstacles or terrain conflicts during construction, and makes the pipeline design scheme more feasible. Based on the pipeline path model, the pipeline diameter, material and load requirements are analyzed to generate basic pipeline design parameter data. This analysis can provide comprehensive technical parameters for the construction and subsequent operation of the pipeline, ensuring that the pipeline can withstand the expected pressure and load, and improving the long-term safety and stability of the pipeline. By evaluating the structural stability and bearing capacity based on the design parameters, potential design problems can be discovered in advance, ensuring the stability of the pipeline under different environmental and load conditions, which helps to improve the pressure resistance of the pipeline and avoid pipeline damage or failure caused by inappropriate design. The generation of basic pipeline model design data, combined with multiple factors such as pipeline path, diameter, material, and load-bearing capacity, provides a comprehensive and scientific design basis for pipeline construction and management. This not only ensures the structural rationality and functionality of the pipeline, but also greatly improves the safety, economy, and sustainability of the project.

[0027] Preferably, in step S2, performing secondary internal stress analysis of the pipeline casing on the basic pipeline model design data using the cross-road topography data includes:

[0028] Extract terrain features from cross-road geomorphic data, analyze geological structure changes under the road, and generate sub-road geological data;

[0029] Conduct pipeline casing load analysis based on basic pipeline model design data and subsurface geological data to generate preliminary load data;

[0030] Calculate the elastic modulus and material strength of the pipe casing based on the preliminary load data to obtain the stress state data of the pipe casing;

[0031] Conduct secondary internal stress analysis on the stress state data of the pipeline casing to generate secondary stress distribution data, where the secondary internal stress analysis includes road traffic load stress analysis and surface settlement stress analysis;

[0032] Based on the secondary stress distribution data and combined with the preset pipeline design standards, the stress limit is checked to generate the pipeline cross-road stress data.

[0033] By extracting terrain features and analyzing the geological structure under the road from cross-road geomorphological data, the present invention can accurately understand the geological changes under the road and generate underground geological data. This provides detailed underground geological information for pipeline design, ensuring that the laying of pipelines and casing design can adapt to different geological conditions and reduce the impact of underground unstable factors on the pipeline. By combining the basic pipeline model design data with the underground geological data to perform load analysis on the pipeline casing, the performance of the pipeline casing under different load conditions can be effectively evaluated and preliminary load data can be generated. This analysis provides the necessary basic data for subsequent pipeline design optimization, ensuring that the pipeline can withstand the pressure from the surface and road loads. By calculating the elastic modulus and material strength of the pipeline casing, the stress state data of the pipeline casing is obtained. This process can accurately evaluate the load-bearing capacity and pressure resistance of the pipeline casing, ensuring that the pipeline can remain stable during long-term use and avoiding pipeline damage due to design defects. By conducting secondary internal stress analysis, particularly road traffic load stress analysis and ground settlement stress analysis, the stress distribution of pipeline casings in actual environments can be comprehensively assessed. This analysis helps identify areas of stress concentration in pipelines affected by factors such as traffic loads or ground settlement, thereby providing designers with targeted improvement suggestions. By combining secondary stress distribution data with preset pipeline design standards to perform stress limit verification, it is possible to ensure that pipeline designs meet strict safety standards, avoid damage or leakage due to excessive stress on the pipeline, and improve the overall safety and durability of the pipeline. The generation of pipeline cross-road internal stress data can provide more accurate stress distribution data for pipeline design, making the design of pipelines across road sections more scientific and reasonable, thereby reducing risks during construction and the need for subsequent maintenance.

[0034] Preferably, in step S2, performing a suspended pipe section self-vibration analysis on the basic pipeline model design data using the cross-river topography data includes:

[0035] Analyze riverbed geology and water flow characteristics on cross-river geomorphological data to generate riverbed geology data and water flow interaction data;

[0036] Based on the basic pipeline model design data and riverbed geological data, the suspended pipe section position of the pipeline is identified and marked, and the suspended pipe section position data is generated;

[0037] Calculate the natural frequency of the suspended pipe section position data;

[0038] The external force vibration of the suspended pipe section is simulated by using water flow interaction data and natural frequency to generate pipeline vibration data under external force;

[0039] The pipeline crossing river natural vibration characteristics are analyzed based on the pipeline vibration data and natural frequency, and the pipeline crossing river natural vibration data is generated.

[0040] By analyzing riverbed geology and flow characteristics based on cross-river geomorphological data, this method can provide a deep understanding of the riverbed's soil structure and characteristics such as the speed and direction of the water flow, generating riverbed geological data and water flow interaction data. This provides a scientific basis for the design of pipelines across river sections, ensuring that the pipelines can adapt to different water flows and geological environments, and reducing structural problems caused by water flow changes. Based on the basic pipeline model design data and riverbed geological data, the location of the suspended pipe section of the pipeline can be accurately identified and marked, generating suspended pipe section position data. This process ensures that the special conditions of the pipeline crossing the river section are clearly identified, providing accurate input data for subsequent design optimization and preventing the pipeline from being affected by unnecessary external forces due to improper position. By calculating the natural frequency of the suspended pipe section position data, important vibration characteristic information can be provided for pipeline design. This process can identify the vibration frequency of the pipeline under the influence of water flow and geological conditions, thereby providing a preliminary assessment of the pipeline's stability. Using water flow interaction data and natural frequency data to simulate the external force vibration of the suspended pipe section, pipeline vibration data under external force can be generated. This process can help designers understand how external forces such as water flow and air flow affect pipeline vibration and optimize the pipeline's anti-vibration design. Analysis of the natural vibration characteristics of pipelines crossing rivers based on pipeline vibration data and natural frequency can provide targeted optimization suggestions for the design of pipeline crossing river sections, ensuring that the pipeline can remain stable under the dynamic effects of water flow and avoiding damage or failure of the pipeline due to vibration or improper design. Through the natural vibration analysis of pipeline crossing river sections, designers can take necessary measures to strengthen the structural design of the pipeline, such as adding supports and adjusting the pipeline material or thickness, to ensure that the pipeline can withstand the influence of water flow, vibration and other external forces during long-term use, extending the pipeline's service life and reducing maintenance costs.

[0041] Preferably, step S3 includes the following steps:

[0042] Step S31: using the natural vibration data of the pipeline crossing the river to divide the basic pipeline model design data into frequency response regions, identify vibration sensitive areas and resonance risk areas, and generate vibration impact areas;

[0043] Step S32: using the pipeline cross-path stress data to identify stress concentration locations on the basic pipeline model design data and calculate stress peaks to generate pipeline stress hotspot distribution data;

[0044] Step S33: Adapting and optimizing the pipeline segment topography to the basic pipeline model design data using the vibration impact area and pipeline stress hotspot distribution data to generate optimized pipeline segment topography mechanical performance data;

[0045] Step S34: Optimizing the selection of pipeline materials and geometric dimensions using the pipeline segment geomorphological mechanical performance optimization data to obtain pipeline segment design optimization data;

[0046] Step S35: performing pipeline topology analysis on the basic pipeline model design data according to the pipeline segment design optimization data, and performing geomorphic pipeline intersection verification on the results of the topology analysis, thereby identifying pipeline segment connection points.

[0047] The present invention divides the basic pipeline model design data into frequency response areas by using the pipeline cross-river self-vibration data, which can identify vibration-sensitive areas and resonance risk areas, and generate vibration impact areas. This provides an accurate vibration assessment for pipeline design, ensuring that the pipeline design can avoid or reduce potential damage caused by vibration and improve the long-term stability of the pipeline. By using the pipeline cross-road stress data to identify the stress concentration position of the basic pipeline model design data and calculate the stress peak, it is possible to generate pipeline stress hotspot distribution data. This analysis helps designers accurately identify areas where pipeline stress is concentrated, and then take targeted design measures to avoid pipeline failure in stress concentration areas and ensure the structural safety of the pipeline. Based on the vibration impact area and pipeline stress hotspot distribution data, the pipeline section terrain adaptation and optimization design are carried out, which can optimize the mechanical properties of the pipeline section according to different terrain conditions and generate pipeline section terrain mechanical property optimization data. This process ensures that the mechanical properties of the pipeline under complex terrain conditions are optimized, enhances the pipeline's anti-vibration and anti-pressure capabilities, and improves the reliability and safety of the pipeline. By optimizing the selection of pipeline materials and geometric dimensions based on pipeline segment geomorphological mechanical performance optimization data, the optimal material and dimensions can be selected based on the pipeline's operating environment and mechanical performance requirements. This not only improves the pipeline's physical performance but also reduces costs, avoids unnecessary resource waste, and ensures the pipeline's efficiency and durability in practical applications. By performing pipeline topology analysis on the basic pipeline model design data based on pipeline segment design optimization data and validating the topological pipeline intersection results, the connection points of pipeline segments can be effectively identified. This process ensures efficient connectivity of the pipeline network and avoids pipeline transportation bottlenecks or potential structural safety hazards caused by topological design issues.

[0048] Preferably, performing geomorphic pipeline intersection verification on the results of the topological analysis includes:

[0049] Based on the topological analysis results, the intersection points between the pipeline path and the terrain features in the basic pipeline model design data are extracted, and the verification criteria for the intersection points are set:

[0050] The slope change of the pipeline path should be greater than 10% and less than 25% to ensure that the slope of the pipeline at the intersection is suitable for the interconnection design; the relative height difference of the intersection should be greater than 30 cm and less than 150 cm to ensure that the height difference at the intersection is within a reasonable range and does not affect the connection of the pipeline segments; the shortest distance between the intersection and the surrounding terrain features should be less than 300 meters to ensure that there is an operational connection distance between the intersection and the surrounding terrain features;

[0051] According to the verification standard of the intersection point, the geomorphic pipeline intersection verification condition is set for the intersection point:

[0052] If the slope change of the intersection point is between 10% and 25%, the relative height difference is between 30 and 150 cm, and the shortest distance between the intersection point and the surrounding landform features is less than 300 meters, the intersection point is determined to be a connecting point of the pipeline section; if it does not meet the above value range, the intersection point is determined to be a non-connecting point and is eliminated.

[0053] Identify all pipeline segment connection points that meet the geomorphic pipeline intersection verification conditions and generate pipeline segment connection point data.

[0054] The present invention can accurately identify the intersection between the pipeline path and the terrain features by setting specific intersection verification standards (such as slope change, relative height difference, shortest distance, etc.). This process ensures the practical feasibility of the pipeline design. By verifying the suitability of the intersection, the intersection that does not meet the design standards is avoided, and the rationality and stability of the pipeline network are improved. The intersection verification standard ensures that the slope, relative height difference and distance of the pipeline at the intersection are within a reasonable range, thereby avoiding design problems or structural instability caused by terrain mismatch at the intersection. This makes the connection of pipeline sections in different terrain environments more stable and safe, and reduces the potential risks caused by improper intersection design. Through accurate intersection verification, it can ensure that the connection points of the pipeline sections can adapt to the surrounding terrain features, ensuring the flexibility and adaptability of the pipeline design, which not only improves the overall efficiency of the pipeline system, but also reduces the additional adjustments required under complex terrain conditions, thereby improving the convenience of pipeline construction and maintenance. In the pipeline design process, the intersections that do not meet the standards are eliminated, which can effectively avoid high-cost modifications and delays caused by terrain mismatch in future pipeline construction. Furthermore, accurate verification during the initial design phase can reduce the need for subsequent pipeline maintenance and adjustments, lowering overall project costs. Verification of intersections addresses not only pipeline connectivity but also the stability of the pipeline during long-term operation. This early verification ensures that the design and implementation of each intersection can address future environmental changes, thereby guaranteeing the safety and reliability of the pipeline system over the long term.

[0055] Preferably, step S4 includes the following steps:

[0056] Step S41: performing internal airflow simulation on the pipeline connection points to generate pipeline connection point airflow simulation data; performing airflow turbulence characteristic analysis on the pipeline connection point airflow simulation data to generate pipeline airflow turbulence impact data;

[0057] Step S42: Evaluate the airflow interference effect of the connecting points of the pipeline sections based on the pipeline airflow turbulence impact data, and generate analysis results of the pipeline air flow state impact;

[0058] Step S43: Adjust the cross-sectional shape and layout design of the basic pipeline model design data according to the analysis results, and optimize the overall pipeline model of the basic pipeline model design data in combination with the pipeline segment design optimization data, thereby generating a design model of the long-distance steam supply pipeline.

[0059] By simulating internal pipeline airflow and analyzing turbulence characteristics, the present invention accurately understands airflow conditions at pipeline interconnection points, particularly the effects of turbulence. This process provides essential airflow behavior data for pipeline design, helping to optimize airflow distribution, ensure smooth airflow, and avoid unnecessary resistance and waste. Airflow interference effect assessment based on pipeline airflow turbulence impact data effectively identifies and reduces airflow interference within the pipeline, particularly at the junctions of pipeline segments. This assessment minimizes the negative impact of airflow variations on pipeline air supply, thereby ensuring the stability and efficiency of the air supply system. Optimizing the pipeline cross-sectional shape and layout based on the results of the airflow interference effect assessment improves pipeline airflow and reduces airflow resistance caused by improper design. This adjustment not only improves pipeline efficiency but also effectively prevents malfunctions and performance degradation. Integrating the pipeline segment design optimization data to optimize the basic pipeline model overall ensures that the pipeline design is more aligned with actual operational needs. This optimization process ensures that the pipeline shape and layout match the gas supply requirements, enhancing the pipeline's adaptability and operability and avoiding unnecessary modifications and adjustments later. By optimizing the overall pipeline model, especially during the design of long-distance gas supply pipelines, the pipeline's gas transmission capacity and stability can be effectively improved. The optimized pipeline design reduces airflow turbulence and interference, ensuring efficient and safe operation of the pipeline over long-distance gas supply.

[0060] In this specification, a model design system for a long-distance steam supply pipeline is provided, which is used to execute the above-mentioned model design method for a long-distance steam supply pipeline. The model design system for a long-distance steam supply pipeline includes:

[0061] The landform division module is used to obtain the locations of the pipeline starting point and the pipeline target point; perform mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, where the mid-range landform division data includes cross-road landform data and cross-river landform data;

[0062] The pipeline segment analysis module is used to perform basic pipeline modeling based on the locations of the pipeline starting point and pipeline target point, generating basic pipeline model design data; perform secondary internal stress analysis of the pipeline casing on the basic pipeline model design data using cross-road topography data to generate pipeline cross-road internal stress data; and perform suspended pipe segment self-vibration analysis on the basic pipeline model design data using cross-river topography data to generate pipeline cross-river self-vibration data;

[0063] The segmented design module is used to optimize the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and pipeline crossing road internal stress data, and generate pipeline segment design optimization data; based on the pipeline segment design optimization data, the pipeline segment connection points of the basic pipeline model design data are confirmed;

[0064] The gas supply optimization module is used to analyze the impact of pipeline section connection points on pipeline gas flow dynamics, and optimize the basic pipeline model design data based on the analysis results and pipeline section design optimization data, thereby generating a design model for long-distance steam supply pipelines.

[0065] The beneficial effect of the present invention is that the landform division module can accurately analyze the landform characteristics of the area through which the pipeline passes by obtaining the positions of the starting point and target point of the pipeline, and generate detailed mid-range landform division data. This data includes cross-road and cross-river landforms, which provides important terrain information for pipeline design, ensures that the pipeline design is perfectly consistent with the actual geographical environment, and avoids environmental neglect and potential risks in the design process. The pipeline segment analysis module constructs and analyzes the pipeline model by combining cross-road and cross-river landform data. In particular, the secondary internal stress analysis of the pipeline casing and the self-vibration analysis of the suspended pipe section not only ensure the structural stability of the pipeline under different terrain conditions, but also provide strong data support for subsequent pipeline design optimization, effectively avoiding insufficient bearing capacity or vibration problems during the use of the pipeline. The segmented design module combines the pipeline cross-river self-vibration data and the pipeline cross-road internal stress data to optimize the pipeline segment landform design, which can achieve optimization of the mechanical properties of the pipeline segment under different landform conditions. This optimization process ensures that the pipeline segment can give full play to its structural advantages when crossing different landform areas, thereby improving the overall pipeline performance and reliability. The gas supply optimization module analyzes the impact of gas flow patterns on pipeline connection points, ensuring a good match between pipeline design and gas flow conditions, and optimizing pipeline design to accommodate long-distance steam supply needs. By optimizing the cross-sectional shape and layout of the pipeline, the smoothness of the gas flow in the pipeline during long-distance gas transmission is improved, reducing airflow turbulence and pressure drop problems, and improving gas supply efficiency and system stability. Therefore, the present invention addresses the problems of insufficient pipeline design accuracy, stress analysis limitations, and insufficient comprehensive optimization in complex terrains in existing technologies by introducing an optimization design method that combines mid-range topography analysis, secondary pipeline stress analysis, and self-vibration analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic flow chart of the steps of a model design method for a long-distance steam supply pipeline;

[0067] Figure 2 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0068] Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0069] 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

[0070] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. It is obvious that the embodiments described are part of the embodiments of the present invention, but 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 efforts are within the scope of protection of the present invention.

[0071] 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.

[0072] 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.

[0073] To achieve this, please refer to Figures 1 to 3 A model design method for a long-distance steam supply pipeline comprises the following steps:

[0074] Step S1: obtaining the positions of the pipeline starting point and the pipeline target point; performing mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, wherein the mid-range landform division data includes cross-road landform data and cross-river landform data;

[0075] Step S2: Basic pipeline modeling is performed based on the locations of the pipeline starting point and the pipeline target point to generate basic pipeline model design data; secondary internal stress analysis of the pipeline casing is performed on the basic pipeline model design data using the cross-road topography data to generate pipeline cross-road internal stress data; suspended pipe section self-vibration analysis is performed on the basic pipeline model design data using the cross-river topography data to generate pipeline cross-river self-vibration data;

[0076] Step S3: Optimizing the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and the pipeline crossing road internal stress data, thereby generating pipeline segment design optimization data; and confirming the pipeline segment connection points of the basic pipeline model design data based on the pipeline segment design optimization data.

[0077] Step S4: Analyze the influence of pipeline supply flow dynamics on pipeline segment connection points, and optimize the basic pipeline model design data according to the analysis results and pipeline segment design optimization data, thereby generating a design model for the long-distance steam supply pipeline.

[0078] This invention ensures the stability and safety of long-distance gas supply pipelines in diverse terrain conditions through refined analysis and optimization. First, by obtaining the locations of the pipeline's starting and target points and conducting mid-range terrain analysis, the pipeline design is ensured to be adaptable to complex terrain conditions. By segmenting cross-road and cross-river terrain data, detailed terrain information is provided for subsequent pipeline design, avoiding terrain conflicts or special requirements. Next, basic pipeline modeling and a detailed analysis of terrain factors are performed to ensure that the pipeline structure in road or river crossing areas is not subject to excessive internal stress or unsafe vibration. Secondary internal stress analysis and natural vibration analysis provide scientific assurance of pipeline stability, reducing the risk of pipeline rupture or failure. Then, through design optimization based on cross-road and cross-river data, the pipeline structure is made more adaptable to complex terrain conditions. Pipeline segment design optimization helps further enhance the stability of pipeline connection points despite the influence of terrain factors, thereby improving the pipeline's long-term reliability and durability. Finally, an analysis of the impact of gas flow patterns on the connection points of pipeline segments is performed, allowing pipeline design to not only optimize the structure but also the airflow transmission efficiency. Through comprehensive analysis and design optimization, the pipeline design model finally generated can effectively reduce energy loss and ensure smooth airflow during long-distance steam supply, thereby improving the overall function and work efficiency of the pipeline. The entire process not only enhances the accuracy of pipeline design and ensures efficient operation under complex terrain, but also ensures the stability and risk resistance of the pipeline through in-depth stress and vibration analysis, further improves the design rationality of pipeline section connection points, reduces maintenance requirements and potential failures, and optimizes airflow efficiency and energy transmission to improve the overall performance of the gas supply system. Therefore, the present invention solves the problems of insufficient pipeline design accuracy, stress analysis limitations and insufficient comprehensive optimization under complex terrain in the existing technology by introducing an optimization design method that combines mid-distance terrain analysis, pipeline stress secondary analysis and self-vibration analysis.

[0079] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a flow chart showing the steps of a method for designing a model of a long-distance steam supply pipeline according to the present invention. In this example, the method for designing a model of a long-distance steam supply pipeline includes the following steps:

[0080] Step S1: obtaining the positions of the pipeline starting point and the pipeline target point; performing mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, wherein the mid-range landform division data includes cross-road landform data and cross-river landform data;

[0081] Step S2: Basic pipeline modeling is performed based on the locations of the pipeline starting point and the pipeline target point to generate basic pipeline model design data; secondary internal stress analysis of the pipeline casing is performed on the basic pipeline model design data using the cross-road topography data to generate pipeline cross-road internal stress data; suspended pipe section self-vibration analysis is performed on the basic pipeline model design data using the cross-river topography data to generate pipeline cross-river self-vibration data;

[0082] Step S3: Optimizing the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and the pipeline crossing road internal stress data, thereby generating pipeline segment design optimization data; and confirming the pipeline segment connection points of the basic pipeline model design data based on the pipeline segment design optimization data.

[0083] Step S4: Analyze the influence of pipeline supply flow dynamics on pipeline segment connection points, and optimize the basic pipeline model design data according to the analysis results and pipeline segment design optimization data, thereby generating a design model for the long-distance steam supply pipeline.

[0084] In an embodiment of the present invention, the geographical location data of the pipeline project area, including the precise coordinates of the starting point and the target point, is obtained through remote sensing technology or a geographic information system (GIS), ensuring that the data accuracy reaches the centimeter level. Then, aerial images, LiDAR data, and digital elevation models (DEMs) are used to perform mid-range geomorphological analysis. The analysis includes extracting the main terrain features along the pipeline path, such as terrain height changes, river intersections, road crossing points, etc., and using spatial analysis tools to divide the area between the starting point and the target point into different geomorphological types, generating cross-road geomorphological data and cross-river geomorphological data. The cross-road geomorphological data records the type, structure, and potential influencing factors of the road through which the pipeline passes; while the cross-river geomorphological data reflects the riverbed depth, flow velocity, and crossing method of the river along the pipeline, providing basic support for subsequent pipeline design. According to the positions of the starting point and target point of the pipeline, the spatial coordinates of the pipeline path and the surrounding environment data are used to construct a basic pipeline model using pipeline design software (such as AutoCAD, Bentley, Pipesim, etc.). The model includes components such as straight sections, elbows, flanges, and valves, along with their geometric parameters. After the model was generated, a stress analysis was performed on the area where the pipeline crosses the road, based on the cross-road topography data. Finite element analysis (FEA) was used to perform a secondary internal stress analysis on the pipeline casing, accounting for factors such as road loads, soil reaction forces, and temperature fluctuations. This generated cross-road internal stress data, helping to assess the safety of the pipeline under the road. Next, a natural vibration analysis of the suspended section of the pipeline in the river crossing was conducted based on the cross-river topography data. Considering the effects of fluid dynamics and wind loads on the pipeline, a dynamic analysis method was used to generate cross-river natural vibration data, providing a basis for pipeline stability and vibration control in the river crossing section. Based on the cross-river natural vibration data and the cross-road internal stress data, an optimization algorithm was used to optimize the topography design of the basic pipeline model. First, using the cross-river natural vibration data, dynamic analysis was used to adjust the pipeline's suspension support position, material selection, and structural reinforcement methods to ensure that the pipeline's vibration frequency in the river crossing section is lower than its natural frequency, preventing resonance. Secondly, using the internal stress data of the pipeline crossing the road, through stress distribution and bearing capacity analysis, the pipeline crossing the road section is optimized again, adjusting the pipeline depth, casing thickness and pipeline laying method to ensure that it does not generate excessive internal stress when bearing the ground load, ensuring structural safety. The optimized data will generate pipeline segment design optimization data, including optimized pipeline structural parameters, terrain adaptation strategy and other technical requirements. Finally, based on these optimization results, the pipeline segment connection points, that is, the interface locations between the pipeline sections, are confirmed to ensure that the pipeline connection parts meet the construction and long-term operation requirements, avoid connection problems during construction and stress concentration during operation. Detailed fluid dynamics analysis is carried out on the pipeline segment connection points to evaluate the impact of different pipeline segment connection methods on the gas supply flow.Fluid dynamics simulation software (such as ANSYS Fluent, COMSOL Multiphysics, etc.) is used to establish a fluid model of the pipeline, simulating the flow state of gas at the connection points of different pipeline sections, with special attention paid to the flow state changes in pipe elbows, joints, flanges and other parts. By monitoring and analyzing parameters such as flow velocity, pressure loss, and turbulence level, areas that cause unstable airflow or excessive pressure drop are identified, and the pipeline layout and connection methods are optimized. Based on the flow state impact analysis results and pipeline section design optimization data, the basic pipeline model is further adjusted and optimized, involving aspects such as pipeline size, material selection, pipeline support and vibration isolation measures, to ensure that the pipeline system can operate stably and efficiently throughout the entire process. Ultimately, a design model of a long-distance steam supply pipeline that meets actual usage needs is generated, providing a complete technical solution for subsequent construction and operation.

[0085] Preferably, step S1 includes the following steps:

[0086] Step S11: obtaining the pipeline starting point and pipeline target point positions based on GPS;

[0087] Step S12: Calculate the pipeline plane straight-line distance according to the pipeline starting point and the pipeline target point, and calculate the mean of the pipeline plane straight-line distance to generate the pipeline center distance point;

[0088] Step S13: collecting digital elevation data at the pipeline center distance point to obtain pipeline center elevation data; analyzing the terrain profile of the pipeline center elevation data to obtain pipeline terrain profile data;

[0089] Step S14: Identify the terrain information of the pipeline center distance point, and classify the landform type based on the terrain information and pipeline terrain profile data to generate medium-distance landform division data, where the medium-distance landform division data includes cross-road landform data and cross-river landform data.

[0090] In an embodiment of the present invention, a high-precision GPS device is used to accurately locate the starting point and target point of the pipeline. The GPS device should have centimeter-level accuracy and be able to provide the latitude and longitude coordinates of the starting point and target point. Real-time differential technology or RTK (real-time dynamic positioning technology) is used to improve positioning accuracy, ensure accurate starting point and target point location information, and further provide basic data for pipeline design. Based on the GPS positioning data, the plane straight-line distance between the starting point and target point of the pipeline is first calculated. Using coordinate conversion technology, the longitude and latitude are converted into a plane coordinate system, and the plane straight-line distance between the starting point and target point of the pipeline is calculated. Next, the plane straight-line distance of the pipeline is averaged to obtain the center distance point of the pipeline. This point serves as the middle position of the pipeline and provides benchmark data for subsequent terrain and landform analysis. Elevation data of the area surrounding the center point of the pipeline is obtained through remote sensing data, LiDAR (laser radar) data, or digital elevation model (DEM). Using this data, elevation information of the center of the pipeline is generated. By processing and analyzing the elevation data, a topographic profile of the pipeline center is constructed, analyzing the topographical variations along the pipeline route, including mountainous terrain, plains, and low-lying areas. This step helps designers understand the terrain characteristics the pipeline will traverse, providing a crucial reference for subsequent landform classification and pipeline design. Land features around the pipeline center are identified through remote sensing imagery, satellite imagery, or ground surveys, including roads, rivers, buildings, and forests. By classifying and labeling these features, detailed landform information is generated. Next, combining the pipeline center elevation data with the landform information, a landform classification analysis is performed to determine the landform characteristics along the pipeline route. Specifically, the pipeline will traverse different landform types, such as roads (cross-road landforms) and rivers (cross-river landforms). Finally, these analysis results are integrated into mid-range landform classification data, including cross-road landform data and cross-river landform data, providing detailed landform information for subsequent pipeline design and construction plan development.

[0091] Preferably, the landform type classification based on the land feature information and the pipeline terrain profile data in step S14 includes:

[0092] When any of the following conditions occurs, it is determined to be a cross-road landform and cross-road landform data is obtained: the road feature point in the terrain information intersects the pipeline path in the pipeline terrain profile data, and the height change of the pipeline path at the intersection is greater than 50 cm, and the ground undulation amplitude of the road section is greater than 20%;

[0093] When any of the following conditions occurs, it is determined to be a cross-river landform and cross-river landform data is obtained: the river features in the terrain information coincide with the pipeline path in the pipeline terrain profile data, the bottom height of the pipeline path is less than 10 meters below the river water level, the river width is greater than 50 meters, and the flow velocity is greater than 2m / s;

[0094] Integrate cross-road landform data and cross-river landform data into medium-range landform division data.

[0095] In an embodiment of the present invention, the pipeline path is classified into detailed landform types based on the previously acquired terrain information and terrain profile data of the pipeline center point, and cross-road landform data and cross-river landform data are generated respectively. The specific implementation details are as follows: When any of the following situations occurs, it is determined to be cross-road landform, and cross-road landform data is generated: The intersection position of the road feature point and the pipeline path is determined by spatial analysis methods. The intersection position usually indicates that the pipeline needs to cross the road or be arranged parallel to the road. The height change of the pipeline path near the intersection is calculated using the terrain profile data. When the height change of the pipeline path exceeds 50 cm, it means that the terrain change of the pipeline at this location is large, and cross-road construction needs to be considered. The undulation amplitude of the ground in this section is calculated based on the terrain profile data. When the undulation amplitude is greater than 20%, it means that the terrain in this section is relatively complex, the construction of the pipeline in this area is difficult, and cross-road design should be considered. If the above conditions are met at the same time, the landform in this section is determined to be cross-road landform, and cross-road landform data is generated as an important basis for pipeline design. When any of the following conditions occur, it is identified as river-crossing landform, and river-crossing landform data is generated. Spatial registration and coincidence analysis are used to determine whether the pipeline path overlaps with river features. If the pipeline path is located within a river area, the pipeline will cross the river. The relative height of the pipeline path and the river water level is analyzed. If the elevation of the pipeline bottom is less than 10 meters from the river water level, the pipeline will be affected by the river water level at this location, and special design measures must be considered. Based on the terrain information, the river width and flow velocity are analyzed. If the river width is greater than 50 meters and the flow velocity is greater than 2 m / s, this section of the river has a high flow rate and is wide, significantly impacting the pipeline structure and stability. Appropriate measures must be taken in the pipeline design to ensure it can withstand the impact of water flow and riverbed subsidence. If all of these conditions are met, the landform is identified as river-crossing landform, and river-crossing landform data is generated for subsequent pipeline design and construction strategy development. After identifying and generating the road-crossing and river-crossing landform data, these data must be integrated to form complete mid-range landform classification data. Using spatial data processing and fusion technologies, we integrated cross-road and cross-river geomorphological data to create a comprehensive geomorphological delineation dataset. This dataset reflects the specific geomorphological characteristics of each section along the pipeline route, including whether roads or rivers need to be crossed, and the impact of these geomorphological features on pipeline construction and design. The resulting mid-range geomorphological delineation data will serve as a key input to pipeline design, ensuring that the design fully considers the impact of topography and avoids potential construction risks.

[0096] Preferably, in step S2, determining the length of the gas supply pipeline according to the positions of the pipeline starting point and the pipeline target point and performing basic pipeline modeling includes:

[0097] The actual length of the pipeline is calculated based on the mid-range landform division data at the starting point and target point of the pipeline to obtain the actual length data of the pipeline;

[0098] Based on the actual length data of the pipeline and the predetermined path of the pipeline, the pipeline path modeling is performed to generate pipeline path model data;

[0099] Analyze pipeline path model data by pipeline diameter, material, and load requirements to generate basic pipeline design parameter data;

[0100] Structural stability and bearing capacity are evaluated based on basic pipeline design parameter data to generate basic pipeline model design data.

[0101] In an embodiment of the present invention, the locations of the pipeline's starting and destination points are analyzed in detail using mid-range terrain demarcation data to calculate the actual length of the pipeline. The specific process is as follows: First, the geographic coordinates of the pipeline's starting and destination points are accurately acquired using GPS and other positioning technologies. The pipeline's path is then corrected using mid-range terrain demarcation data (including cross-road and cross-river terrain data), identifying terrain undulations, road or river obstacles, and adjusting the actual length of the pipeline. Based on the adjusted path data, the actual length of the pipeline is calculated using a geographic information system (GIS) or other spatial analysis tool. This actual length data serves as the foundation for subsequent pipeline modeling. Based on the calculated actual length data and the planned pipeline path, the pipeline is modeled. The specific steps are as follows: Using the actual length data and the path planning information from the preliminary pipeline design plan, the pipeline path is modeled. This process takes into account terrain, obstacles, and other environmental factors to ensure that the pipeline path conforms to the actual terrain conditions. Advanced modeling techniques (such as path planning algorithms and 3D modeling tools) are used to generate 3D spatial model data of the pipeline path. This model reflects the actual pipeline path from the starting point to the destination, including turns, slopes, and elevation changes. The generated pipeline path model data is analyzed for pipeline design parameters to ensure that the pipeline meets design requirements. The specific steps are as follows: Based on the actual pipeline length and path data, and in conjunction with project requirements, the pipeline diameter and material are selected and analyzed. The appropriate pipeline diameter and material (e.g., steel pipe, polyethylene pipe, etc.) are determined, taking into account factors such as the properties of the gas transported, the required flow rate, and the ambient temperature. Based on the pipeline's load-bearing requirements, the pressures the pipeline must withstand and the external impact forces (such as earthquakes and traffic loads) are analyzed, and the required pipeline material and structural strength are determined. Based on the pipeline design parameter data, the pipeline's structural stability and load-bearing capacity are assessed. The specific steps are as follows: Finite element analysis or other structural analysis methods are performed on the pipeline path model data to evaluate the pipeline's stability under various environmental conditions. Factors such as topography, soil type, and climatic conditions are taken into account to ensure the pipeline maintains its structural integrity over the long term. The pipeline's maximum load-bearing capacity is calculated to assess the internal and external pressures it will encounter during gas transportation, ensuring that the pipeline can withstand the stresses of normal operation. Based on the evaluation results of stability and bearing capacity, basic pipeline design parameter data is generated. These data will serve as an important basis for subsequent pipeline design optimization and construction. After completing all the above analyses, the final basic pipeline model design data will be generated based on the evaluation results. This data will include: Pipeline size and material: Determine the diameter, thickness, material and other design parameters of the pipeline. Pipeline path optimization: Optimize the pipeline path according to the terrain characteristics and bearing requirements, reduce unnecessary curves and turns, and ensure the installation and operation efficiency of the pipeline. Structural reinforcement: For pipeline sections that are easily affected by external factors, such as sections across roads and rivers, structural reinforcement design is carried out to ensure the safe operation of the pipeline.

[0102] Preferably, in step S2, performing secondary internal stress analysis of the pipeline casing on the basic pipeline model design data using the cross-road topography data includes:

[0103] Extract terrain features from cross-road geomorphic data, analyze geological structure changes under the road, and generate sub-road geological data;

[0104] Conduct pipeline casing load analysis based on basic pipeline model design data and subsurface geological data to generate preliminary load data;

[0105] Calculate the elastic modulus and material strength of the pipe casing based on the preliminary load data to obtain the stress state data of the pipe casing;

[0106] Conduct secondary internal stress analysis on the stress state data of the pipeline casing to generate secondary stress distribution data, where the secondary internal stress analysis includes road traffic load stress analysis and surface settlement stress analysis;

[0107] Based on the secondary stress distribution data and combined with the preset pipeline design standards, the stress limit is checked to generate the pipeline cross-road stress data.

[0108] In an embodiment of the present invention, topographic data beneath the pipeline path, including soil type, rock formation distribution, and groundwater level information, is extracted through remote sensing technology, geological survey reports, and topographic surveys. Based on this extracted topographic data, an underground geological structure analysis is performed to identify weak strata, rock faults, and potential soil heterogeneity. These geological features can affect the stability and load-bearing capacity of the pipeline. Combined with road construction history and regional geological survey data, subsurface geological data is generated. This data includes the thickness, strength, and other key physical properties of different soil layers. A load analysis model is developed by combining pipeline foundation design data (including pipeline diameter, material, and load-bearing requirements) with the subsurface geological data. This model accounts for static and dynamic loads on the pipeline casing, including road traffic loads, surface subsidence, and other environmental factors. Finite element analysis or other computational methods are used to generate preliminary load data from this data to evaluate the response of the pipeline casing under different loads. This preliminary load data provides data on various mechanical influences on the pipeline. The elastic modulus of the pipeline casing under load is calculated based on the material and structural characteristics of the pipeline casing. The elastic modulus is a key parameter for assessing a material's deformability. It determines the stiffness and deformation behavior of a pipeline under load. The material properties of the pipeline casing (such as the yield strength and tensile strength of the steel pipe) are combined to analyze the material strength of the pipeline casing under extreme loads. By calculating the maximum load-bearing capacity of the pipeline material, the maximum load-bearing capacity is ensured to prevent damage or excessive deformation under extreme conditions. Based on the elastic modulus and material strength analysis results, the stress state data of the pipeline casing is obtained. This data reflects the stress distribution of the pipeline under different loads and provides a basis for subsequent stress analysis. The stress effects of road traffic loads on the pipeline casing are analyzed. By considering the traffic vehicle load, load frequency, and the load transmission method along the pipeline path, the stress effects of road traffic loads on the pipeline casing are calculated. The stress effects caused by surface settlement (such as soil loosening and groundwater level changes) are analyzed. Surface settlement can cause localized settlement or bending in the pipeline, affecting the overall stability of the pipeline. The stresses caused by the above traffic loads and surface settlement are combined to generate secondary stress distribution data for the pipeline casing. This data will show the stress distribution of the pipeline under different geological environments and traffic load conditions, helping to identify high-stress areas. The secondary stress distribution data will be verified according to relevant industry standards, engineering design requirements and the service life of the pipeline. The verification includes checking whether the stress of each part of the pipeline exceeds the preset safety limits, such as yield strength, maximum stress, etc. The secondary stress distribution data will be compared with the pipeline design standards to ensure that the stress of the pipeline during operation does not exceed the specified safety limit. Finally, combined with the results of the stress verification, the pipeline cross-road stress data will be generated. This data will serve as a reference for subsequent pipeline design and construction to ensure that the pipeline can operate safely in complex road environments.

[0109] Preferably, in step S2, performing a suspended pipe section self-vibration analysis on the basic pipeline model design data using the cross-river topography data includes:

[0110] Analyze riverbed geology and water flow characteristics on cross-river geomorphological data to generate riverbed geology data and water flow interaction data;

[0111] Based on the basic pipeline model design data and riverbed geological data, the suspended pipe section position of the pipeline is identified and marked, and the suspended pipe section position data is generated;

[0112] Calculate the natural frequency of the suspended pipe section position data;

[0113] The external force vibration of the suspended pipe section is simulated by using water flow interaction data and natural frequency to generate pipeline vibration data under external force;

[0114] The pipeline crossing river natural vibration characteristics are analyzed based on the pipeline vibration data and natural frequency, and the pipeline crossing river natural vibration data is generated.

[0115] In this embodiment of the present invention, by collecting and analyzing riverbed geological structural data, including soil type, rock layer distribution, and groundwater levels at the riverbed bottom, potential weak zones and uneven geological structures are identified. Riverbed geological data helps determine whether the pipeline is experiencing subsidence, friction, or other geological impacts. Data such as water velocity, direction, and water level fluctuations are collected to analyze the impact of water flow on the pipeline. Factors such as water velocity, direction fluctuations, and turbulence will affect the vibration mode of the pipeline, particularly in the suspended section. This analysis generates detailed riverbed geological data and water flow interaction data, which provide the external environmental context for how water flow affects pipeline vibration. Based on the pipeline's basic design data and riverbed geological data, it is determined whether the pipeline is suspended. If the pipeline passes through a river section and is not fixed to the riverbed, this section of pipeline is considered a suspended section. Furthermore, based on topographical and geological conditions, the starting and ending points of the suspended section are precisely located. The suspended section is marked to generate suspended section location data. This data records the specific location of the suspended section within the entire pipeline system, as well as relevant geological information, for subsequent analysis. A mechanical model of the pipeline is established using parameters such as the length, material, mass distribution, and support conditions of the suspended pipe section. Classical vibration theory or finite element analysis is used to calculate the natural frequency of the suspended section. Natural frequency refers to the frequency at which the pipeline vibrates due to its inherent characteristics without external excitation, affecting its stability and long-term safety. The calculated results provide data on the natural frequency of the suspended pipe section. This data will be used for subsequent vibration analysis and design optimization. The forces exerted by the water flow on the suspended pipe section are simulated by combining information such as the flow velocity and direction. Turbulence and fluctuations in the water flow generate periodic external forces on the pipeline. Based on the water flow interaction data and the natural frequency of the pipeline, vibration simulations of the pipeline under the influence of water flow are performed. The simulation considers parameters such as the pipe mass, elastic modulus, and damping coefficient to analyze the pipeline's vibration response. Vibration simulations provide data on the pipeline's vibration under external forces. This data, including the amplitude, frequency, and vibration mode of the pipeline vibration, provides fundamental data for pipeline design. Combining the pipeline's natural frequency and external force vibration data, the resonance effect when the pipeline's natural frequency matches the water flow vibration frequency is analyzed. Resonance increases the pipeline's vibration amplitude, which in turn causes fatigue damage. By analyzing the pipeline's natural vibration characteristics in the river crossing section, the long-term stability of the pipeline under the influence of water flow is evaluated. Considering the pipeline's vibration mode, frequency distribution, and environmental factors, the pipeline's fatigue life and safety risks are analyzed. Based on this analysis, pipeline cross-river natural vibration data is generated. This data records the pipeline's natural vibration characteristics, vibration amplitude, and resonance phenomena in the river crossing section, providing a basis for pipeline design optimization and construction planning.

[0116] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes:

[0117] Step S31: using the natural vibration data of the pipeline crossing the river to divide the basic pipeline model design data into frequency response regions, identify vibration sensitive areas and resonance risk areas, and generate vibration impact areas;

[0118] Step S32: using the pipeline cross-path stress data to identify stress concentration locations on the basic pipeline model design data and calculate stress peaks to generate pipeline stress hotspot distribution data;

[0119] Step S33: Adapting and optimizing the pipeline segment topography to the basic pipeline model design data using the vibration impact area and pipeline stress hotspot distribution data to generate optimized pipeline segment topography mechanical performance data;

[0120] Step S34: Optimizing the selection of pipeline materials and geometric dimensions using the pipeline segment geomorphological mechanical performance optimization data to obtain pipeline segment design optimization data;

[0121] Step S35: performing pipeline topology analysis on the basic pipeline model design data according to the pipeline segment design optimization data, and performing geomorphic pipeline intersection verification on the results of the topology analysis, thereby identifying pipeline segment connection points.

[0122] In this embodiment of the present invention, the natural vibration frequency of a pipeline crossing a river is extracted based on its natural vibration data. The pipeline is then segmented and the frequency response characteristics of each section are analyzed. Based on the natural vibration frequency of the pipeline, the pipeline's vibration response regions are divided, and the sensitivity of each region to water flow vibration is determined. Typically, the frequency response regions are determined based on the degree of match between the pipeline's natural frequency and the excitation frequency of the water flow. Based on the segmentation results, the regions most significantly affected by external water flow vibration are identified and marked as vibration-sensitive regions. These regions are then assessed for resonance risk, ultimately generating data on the pipeline's vibration-affected regions. Based on the frequency response characteristics of each pipeline region, vibration-sensitive regions are identified. These regions experience significant vibration under external excitation and typically correspond to resonance-prone areas. Matching analysis with the excitation frequency of the water flow further identifies resonance-prone areas. Resonance-risk regions are typically areas where the vibration response region and the water flow frequency are close, posing a greater risk. Based on the stress data within the pipeline crossing the road, the stress conditions of the pipeline in the road section are analyzed. Stress changes in the pipeline crossing the road due to factors such as road traffic loads and ground subsidence are identified. Based on the stress analysis results, the areas of pipeline stress with the highest concentrations are located. These areas are often the most critical areas for pipeline design, as factors such as topography and traffic loads can lead to high stress levels. The pipeline stress distribution is calculated to identify the locations of peak stresses. Stress peaks can be used to assess the stress limits and structural safety of pipelines crossing roads. Based on the calculated stress peaks, pipeline stress hotspot distribution data is generated, identifying sensitive areas of the pipeline crossing roads. These areas typically require special reinforcement or protective measures during pipeline design. Based on vibration-affected areas, the mechanical properties of the pipeline in these areas are evaluated, and the pipeline support structure, materials, and installation methods are optimized to reduce the impact of vibration caused by external water flow. Combined with the stress hotspot data, optimized design is implemented for areas of pipeline stress concentration, including strengthening pipe wall thickness, adjusting support methods, and selecting stronger materials. Based on terrain adaptation data, the pipeline's mechanical properties are assessed to ensure they meet engineering requirements, particularly in areas of vibration and stress concentration. Through simulation analysis, pipeline design parameters such as materials, geometry, and support methods are optimized to ensure pipeline safety and stability under vibration and stress. Based on the adaptation and optimization results, the geomorphological mechanical performance optimization data of the pipeline section is generated to provide a basis for subsequent design.

[0123] Preferably, performing geomorphic pipeline intersection verification on the results of the topological analysis includes:

[0124] Based on the topological analysis results, the intersection points between the pipeline path and the terrain features in the basic pipeline model design data are extracted, and the verification criteria for the intersection points are set:

[0125] The slope change of the pipeline path should be greater than 10% and less than 25% to ensure that the slope of the pipeline at the intersection is suitable for the interconnection design; the relative height difference of the intersection should be greater than 30 cm and less than 150 cm to ensure that the height difference at the intersection is within a reasonable range and does not affect the connection of the pipeline segments; the shortest distance between the intersection and the surrounding terrain features should be less than 300 meters to ensure that there is an operational connection distance between the intersection and the surrounding terrain features;

[0126] According to the verification standard of the intersection point, the geomorphic pipeline intersection verification condition is set for the intersection point:

[0127] If the slope change of the intersection point is between 10% and 25%, the relative height difference is between 30 and 150 cm, and the shortest distance between the intersection point and the surrounding landform features is less than 300 meters, the intersection point is determined to be a connecting point of the pipeline section; if it does not meet the above value range, the intersection point is determined to be a non-connecting point and is eliminated.

[0128] Identify all pipeline segment connection points that meet the geomorphic pipeline intersection verification conditions and generate pipeline segment connection point data.

[0129] In an embodiment of the present invention, geometric feature information of the pipeline path is extracted from the basic pipeline model design data. This includes data on the pipeline's starting point, end point, and intermediate paths, covering the spatial coordinates, direction, and slope of each pipeline segment. Spatial data on surrounding topographic features is obtained. This data includes terrain slope, ground elevation, and spatial information on terrain obstacles (such as rivers and mountains). This data is typically obtained through remote sensing data, topographic maps, or geomorphic survey results. Based on the pipeline path and topographic feature data, spatial analysis algorithms (such as spatial proximity analysis) are used to identify the intersection points between the pipeline path and the topographic features. The intersection point is the intersection of the pipeline path and a topographic feature (such as a river, road, or mountain). Slope change requirements are set at the intersection point to ensure that the pipeline slope at the intersection is suitable for the interconnection design. The slope change should be greater than 10% and less than 25%. The slope change value is calculated by calculating the slope of the pipeline path before and after the intersection point. If the slope change is within the specified range (greater than 10% and less than 25%), the slope of the intersection point meets the design requirements. The relative height difference at the intersection should be greater than 30 cm and less than 150 cm to ensure that pipeline connections are not affected by excessive terrain height differences. The relative height difference is calculated by comparing the ground level of the pipeline intersection with the height of the surrounding terrain. If the relative height difference is between 30 cm and 150 cm, the design requirements are met. The minimum distance between the intersection and surrounding terrain features (such as mountains, rivers, roads, etc.) should be less than 300 meters to ensure sufficient operating space between the pipeline and the terrain features for connection. Spatial analysis methods are used to calculate the shortest distance between the intersection and the nearest terrain feature. If the shortest distance is less than 300 meters, the requirements are met. Each intersection is verified according to the above criteria to determine whether it meets the design requirements. Slope verification: The slope change at the intersection should be within the range of 10%-25%. Height difference verification: The relative height difference at the intersection should be between 30-150 cm. Distance verification: The shortest distance between the intersection and surrounding terrain features should be less than 300 meters. If the slope change, relative height difference and shortest distance of the intersection point meet the above standards, the intersection point is determined to be the connection point of the pipeline segment. If the intersection point does not meet any of the standards, the intersection point is determined to be a non-connection point and is eliminated. According to the conditions of the terrain pipeline intersection verification, all intersection points that meet the requirements are screened out as the connection points of the pipeline segment. Each intersection point that meets the requirements is marked as a connection point of the pipeline segment. All qualified intersection points (i.e., connection points) are integrated into a database to generate pipeline segment connection point data. This data includes: the coordinates of each connection point, the relevant parameters of each intersection point, and the marking of the intersection point as the connection point of the pipeline segment. The generated pipeline segment connection point data will serve as the further design basis of the basic pipeline model to ensure that the subsequent pipeline design is reasonable and feasible under the terrain conditions.

[0130] As an example of the present invention, refer to Figure 3As shown, in this example, step S4 includes:

[0131] Step S41: performing internal airflow simulation on the pipeline connection points to generate pipeline connection point airflow simulation data; performing airflow turbulence characteristic analysis on the pipeline connection point airflow simulation data to generate pipeline airflow turbulence impact data;

[0132] Step S42: Evaluate the airflow interference effect of the connecting points of the pipeline sections based on the pipeline airflow turbulence impact data, and generate analysis results of the pipeline air flow state impact;

[0133] Step S43: Adjust the cross-sectional shape and layout design of the basic pipeline model design data according to the analysis results, and optimize the overall pipeline model of the basic pipeline model design data in combination with the pipeline segment design optimization data, thereby generating a design model of the long-distance steam supply pipeline.

[0134] In an embodiment of the present invention, computational fluid dynamics (CFD) software (such as ANSYS Fluent, COMSOL Multiphysics, etc.) is used to simulate the airflow at the connection point of the pipeline section, taking into account factors such as the geometric shape of the pipeline, flow velocity, and pressure conditions inside and outside the pipeline to simulate the flow process of the airflow. The density, viscosity, temperature and other characteristics of the fluid should be considered in the simulation, and the flow characteristics are calculated using an appropriate turbulence model (such as the k-ε model, the k-ω model, etc.). After the airflow simulation is completed, simulation data of the airflow at the connection point of the pipeline is generated, mainly including: the velocity field, pressure field, temperature distribution, etc. of the airflow in the pipeline, as well as the airflow characteristics at different flow rates, including the uniformity of the flow, the degree of turbulence, etc. The turbulence analysis is performed on the airflow inside the pipeline to calculate the turbulence intensity, turbulence energy distribution, vortex structure, etc. inside the pipeline. The location and intensity of the turbulence and its impact on the stability and transmission efficiency of the pipeline airflow are analyzed. The turbulence characteristic data of the airflow in the pipeline are obtained from the turbulence analysis, and relevant turbulence impact data are generated, such as key indicators such as turbulence intensity and turbulence energy. The impact of the turbulent area on the stability and transmission efficiency of the pipeline airflow. Based on turbulence impact data, assess the airflow stability of the duct section. Considering the disruptive effects of turbulence on the airflow within the duct, analyze the resulting airflow fluctuations, pressure fluctuations, and decreased transmission efficiency. Considering the pulsating characteristics of the airflow, the spread of turbulence, and its impact on the supply flow pattern, focus on assessing whether areas of high turbulence intensity lead to reduced airflow quality or abnormal flow phenomena (such as vortex formation and uneven flow velocity). Analyze the amplitude and frequency of airflow fluctuations to assess their disruptive effects on the flow pattern within the duct. Based on the velocity distribution of the airflow, analyze whether velocity unevenness leads to excessive or insufficient flow in certain duct sections, impacting the stable supply of gas. Focus on analyzing the impact of turbulent sections on gas transmission, particularly at duct interconnections and intersections. Based on the airflow disruption effect assessment, generate an analysis report on the impact of airflow disruption on the supply flow pattern of the duct section. This report should include: the specific location and impact of the airflow disruption areas; an assessment and recommendations for airflow stability in each duct section; and turbulence hotspots requiring attention in duct design and their potential impact on airflow efficiency. Adjust the duct cross-sectional shape and layout based on the results of the airflow stability assessment and turbulence impact analysis. For areas where the airflow interference effect is large, consider increasing the cross-sectional area of the pipeline, changing the geometric shape of the pipeline, or adding flow distribution devices (such as diverters, regulating valves, etc.) to reduce the fluctuation and unevenness of the airflow. When adjusting the design, the material strength, economy and airflow stability of the pipeline should be comprehensively considered. On the basis of the adjustment of the cross-sectional shape and layout of the pipeline, the basic pipeline model is optimized as a whole in combination with the design optimization data of the pipeline section (such as the material, bearing capacity, flow requirements, etc. of the pipeline). During the optimization design process, each part of the pipeline needs to be coordinated and adjusted to ensure that the pipeline design can adapt to different terrain features and airflow conditions, while meeting the requirements of operating efficiency, stability and safety.After completing the pipeline design optimization, a final design model of the long-distance steam supply pipeline is generated. This model should include: adjusted design features such as pipeline cross-sections, layout, and connection points; optimized pipeline airflow stability data and turbulence analysis results; and operational performance, load capacity, and safety analysis results of the long-distance steam supply pipeline. A complete pipeline design report is generated, including the optimized pipeline design scheme, airflow stability analysis results, turbulence impact assessment, airflow interference effect assessment, and pipeline segment design optimization data, providing data support for construction and subsequent operations.

[0135] It is particularly important that step S42 further includes the following steps:

[0136] Step S421: extracting airflow interference parameters from the connecting points of the pipeline segments based on the pipeline airflow turbulence impact data, and generating a connecting point airflow interference parameter set;

[0137] Step S422: performing finite element local simulation on the airflow interference parameter set of the connection point to generate local interference field three-dimensional distribution data; performing spectrum time-frequency analysis on the local interference field three-dimensional distribution data to generate interference spectrum feature data;

[0138] Step S423: performing multiple linear regression and principal component analysis on the interference spectrum feature data to generate flow pattern impact prediction model parameters; performing Monte Carlo random sampling on the flow pattern impact prediction model parameters to generate flow pattern impact confidence distribution data;

[0139] Step S424: Perform graph neural network topology propagation simulation on the three-dimensional distribution data of the local interference field to generate high-dimensional interference propagation data.

[0140] In an embodiment of the present invention, airflow interference parameters are extracted from pipeline segment interconnected points based on pipeline airflow turbulence impact data. First, using the airflow turbulence impact data, airflow interference parameters such as airflow volatility, turbulence intensity, local velocity variations, and temperature gradients are extracted for the interconnected points. These parameters are calculated to obtain a set of interconnected point airflow interference parameters. This set of parameters provides key input data for subsequent analysis and can provide a basis for assessing the stability and uniformity of airflow within the pipeline. Finite element analysis is then performed on the interconnected point airflow interference parameter set. Using the interconnected point airflow interference parameter set as boundary conditions, finite element analysis is performed to simulate the local interference field of the airflow within the pipeline. The generated three-dimensional distribution data of the local interference field reveals the variations and impact of the airflow around the interconnected point, reflecting the instability or turbulence effects of the airflow at different locations within the pipeline. Subsequently, spectral time-frequency analysis is performed on these three-dimensional local interference field distribution data to further extract frequency components and temporal features, generating interference spectrum feature data. This data can quantify the frequency characteristics of the airflow disturbance and thus assess the flow stability. Multiple linear regression and principal component analysis are performed on the interference spectrum feature data. Using multiple linear regression, the correlation between the interference spectrum characteristics and the flow regime within the pipeline is analyzed to generate parameters for the flow regime impact prediction model. Principal component analysis (PCA) is used to simplify the data dimensionality and extract the main components that most influence the airflow state, thereby optimizing the performance of the flow regime prediction model. Following this analysis, Monte Carlo random sampling is performed based on the flow regime impact prediction model parameters to generate flow regime impact confidence distribution data. Monte Carlo methods are used to simulate airflow responses under different disturbance conditions and quantify the reliability and confidence of the prediction model. A graph neural network topological propagation simulation is performed on the three-dimensional distribution data of the local interference field. In this substep, the three-dimensional distribution data of the local interference field is first converted into graph-structured data, where each node represents a specific airflow state and each edge represents the airflow transmission relationship between nodes. A graph neural network (GNN) is used to perform topological propagation simulation to study the propagation paths and impacts of airflow in the pipeline network. GNNs can capture the high-dimensional propagation patterns of airflow disturbances in space, generating high-dimensional interference propagation data. This data can help identify the propagation mode and speed of airflow disturbances, providing a scientific basis for optimizing pipeline design and operation.

[0141] It is particularly important to analyze the turbulence characteristics of the airflow simulation data at the pipeline connection point, including:

[0142] Perform airflow velocity field analysis on the airflow simulation data of pipeline connection points, solve the velocity distribution of each point, and generate airflow velocity distribution data;

[0143] Calculate local turbulence intensity and turbulence kinetic energy based on airflow velocity distribution data, extract important turbulence features, and generate turbulence intensity data;

[0144] Identify various turbulence scales in the airflow based on turbulence intensity data and generate turbulence scale data;

[0145] The impact of turbulence scale data is quantified to generate turbulence impact assessment data.

[0146] In an embodiment of the present invention, the airflow velocity field analysis is performed on the airflow simulation data of the pipeline connection point, the velocity distribution of each point is solved, and the airflow velocity distribution data is generated. In this process, the computational fluid dynamics (CFD) software is used to solve the Navier-Stokes equations, calculate the velocity of the airflow in the pipeline at each grid point, and pay attention to the velocity changes at key locations such as pipeline intersections and bends. Then, based on the airflow velocity distribution data, the local turbulence intensity and turbulent kinetic energy are calculated, and important turbulence characteristics are extracted to generate turbulence intensity data. Turbulence intensity is an important indicator reflecting the instability of airflow. A larger turbulence intensity indicates that the airflow fluctuations are more severe. At the same time, by analyzing the turbulence intensity and kinetic energy data, the large eddy scale and small eddy scale in the airflow are identified, and turbulence scale data is generated to help analyze the various turbulence scales and their distribution in the airflow. Next, the turbulence scale data is quantified to evaluate the impact of turbulence on the flow of airflow in the pipeline, mainly examining the impact of turbulence on the velocity distribution and the friction of the pipeline wall. During this process, we consider that small-scale turbulence often leads to uneven flow velocities, while large-scale turbulence can easily cause macroscopic changes in the flow, thus affecting airflow stability. Ultimately, based on the results of turbulence impact quantification, turbulence impact assessment data is generated. The report includes the impact of turbulence scale on airflow stability and transmission efficiency, identifies turbulence hotspots, and provides optimization recommendations, such as adding airflow control devices or adjusting duct dimensions, to optimize duct design and ensure the stability and efficiency of the air supply flow pattern.

[0147] 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.

[0148] 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. A model design method for a long-distance steam supply pipeline, characterized in that: The following steps are involved: Step S1: obtaining the positions of the pipeline starting point and the pipeline target point; performing mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, wherein the mid-range landform division data includes cross-road landform data and cross-river landform data; Step S2: Basic pipeline modeling is performed based on the locations of the pipeline starting point and the pipeline target point to generate basic pipeline model design data; secondary internal stress analysis of the pipeline casing is performed on the basic pipeline model design data using the cross-road topography data to generate pipeline cross-road internal stress data; suspended pipe section self-vibration analysis is performed on the basic pipeline model design data using the cross-river topography data to generate pipeline cross-river self-vibration data; Step S3: Optimizing the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and the pipeline crossing road internal stress data, thereby generating pipeline segment design optimization data; and confirming the pipeline segment connection points of the basic pipeline model design data based on the pipeline segment design optimization data. Step S4: Analyze the influence of pipeline supply flow dynamics on pipeline segment connection points, and optimize the basic pipeline model design data according to the analysis results and pipeline segment design optimization data, thereby generating a design model for the long-distance steam supply pipeline.

2. The model design method for a long-distance steam supply pipeline according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: obtaining the pipeline starting point and pipeline target point positions based on GPS; Step S12: Calculate the pipeline plane straight-line distance according to the pipeline starting point and the pipeline target point, and calculate the mean of the pipeline plane straight-line distance to generate the pipeline center distance point; Step S13: collecting digital elevation data at the pipeline center distance point to obtain pipeline center elevation data; analyzing the terrain profile of the pipeline center elevation data to obtain pipeline terrain profile data; Step S14: Identify the terrain information of the pipeline center distance point, and classify the landform type based on the terrain information and pipeline terrain profile data to generate medium-distance landform division data, where the medium-distance landform division data includes cross-road landform data and cross-river landform data.

3. The model design method for a long-distance steam supply pipeline according to claim 2, characterized in that: The landform type classification based on the land feature information and pipeline terrain profile data in step S14 includes: When any of the following conditions occurs, it is determined to be a cross-road landform and cross-road landform data is obtained: the road feature point in the terrain information intersects the pipeline path in the pipeline terrain profile data, and the height change of the pipeline path at the intersection is greater than 50 cm, and the ground undulation amplitude of the road section is greater than 20%; When any of the following conditions occurs, it is determined to be a cross-river landform and cross-river landform data is obtained: the river features in the terrain information coincide with the pipeline path in the pipeline terrain profile data, the bottom height of the pipeline path is less than 10 meters below the river water level, the river width is greater than 50 meters, and the flow velocity is greater than 2m / s; Integrate cross-road landform data and cross-river landform data into medium-range landform division data.

4. The model design method for a long-distance steam supply pipeline according to claim 1, characterized in that: In step S2, the length of the gas supply pipeline is determined based on the positions of the pipeline starting point and the pipeline target point, and basic pipeline modeling is performed, including: The actual length of the pipeline is calculated based on the mid-range landform division data at the starting point and target point of the pipeline to obtain the actual length data of the pipeline; Based on the actual length data of the pipeline and the predetermined path of the pipeline, the pipeline path modeling is performed to generate pipeline path model data; Analyze pipeline path model data by pipeline diameter, material, and load requirements to generate basic pipeline design parameter data; Structural stability and bearing capacity are evaluated based on basic pipeline design parameter data to generate basic pipeline model design data.

5. The model design method for a long-distance steam supply pipeline according to claim 1 is characterized in that: In step S2, the secondary internal stress analysis of the pipeline casing is performed on the basic pipeline model design data using the cross-road topography data, including: Extract terrain features from cross-road geomorphic data, analyze geological structure changes under the road, and generate sub-road geological data; Conduct pipeline casing load analysis based on basic pipeline model design data and subsurface geological data to generate preliminary load data; Calculate the elastic modulus and material strength of the pipe casing based on the preliminary load data to obtain the stress state data of the pipe casing; Conduct secondary internal stress analysis on the stress state data of the pipeline casing to generate secondary stress distribution data, where the secondary internal stress analysis includes road traffic load stress analysis and surface settlement stress analysis; Based on the secondary stress distribution data and combined with the preset pipeline design standards, the stress limit is checked to generate the pipeline cross-road stress data.

6. The model design method for a long-distance steam supply pipeline according to claim 1, characterized in that: In step S2, the suspended pipe section self-vibration analysis is performed on the basic pipeline model design data using the cross-river topography data, including: Analyze riverbed geology and water flow characteristics on cross-river geomorphological data to generate riverbed geology data and water flow interaction data; Based on the basic pipeline model design data and riverbed geological data, the suspended pipe section position of the pipeline is identified and marked, and the suspended pipe section position data is generated; Calculate the natural frequency of the suspended pipe section position data; The external force vibration of the suspended pipe section is simulated by using water flow interaction data and natural frequency to generate pipeline vibration data under external force; The pipeline crossing river natural vibration characteristics are analyzed based on the pipeline vibration data and natural frequency, and the pipeline crossing river natural vibration data is generated.

7. The model design method for a long-distance steam supply pipeline according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: using the natural vibration data of the pipeline crossing the river to divide the basic pipeline model design data into frequency response regions, identify vibration sensitive areas and resonance risk areas, and generate vibration impact areas; Step S32: using the pipeline cross-path stress data to identify stress concentration locations on the basic pipeline model design data and calculate stress peaks to generate pipeline stress hotspot distribution data; Step S33: Adapting and optimizing the pipeline segment topography to the basic pipeline model design data using the vibration impact area and pipeline stress hotspot distribution data to generate optimized pipeline segment topography mechanical performance data; Step S34: Optimizing the selection of pipeline materials and geometric dimensions using the pipeline segment geomorphological mechanical performance optimization data to obtain pipeline segment design optimization data; Step S35: performing pipeline topology analysis on the basic pipeline model design data according to the pipeline segment design optimization data, and performing geomorphic pipeline intersection verification on the results of the topology analysis, thereby identifying pipeline segment connection points.

8. The model design method for a long-distance steam supply pipeline according to claim 7, characterized in that: Verification of geomorphic pipeline intersection based on the results of topological analysis includes: Based on the topological analysis results, the intersection points between the pipeline path and the terrain features in the basic pipeline model design data are extracted, and the verification criteria for the intersection points are set: The slope change of the pipeline path should be greater than 10% and less than 25% to ensure that the slope of the pipeline at the intersection is suitable for the interconnection design; the relative height difference of the intersection should be greater than 30 cm and less than 150 cm to ensure that the height difference at the intersection is within a reasonable range and does not affect the connection of the pipeline segments; the shortest distance between the intersection and the surrounding terrain features should be less than 300 meters to ensure that there is an operational connection distance between the intersection and the surrounding terrain features; According to the verification standard of the intersection point, the geomorphic pipeline intersection verification condition is set for the intersection point: If the slope change of the intersection point is between 10% and 25%, the relative height difference is between 30 and 150 cm, and the shortest distance between the intersection point and the surrounding landform features is less than 300 meters, the intersection point is determined to be a connecting point of the pipeline section; if it does not meet the above value range, the intersection point is determined to be a non-connecting point and is eliminated. Identify all pipeline segment connection points that meet the geomorphic pipeline intersection verification conditions and generate pipeline segment connection point data.

9. The model design method for a long-distance steam supply pipeline according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing internal airflow simulation on the pipeline connection points to generate pipeline connection point airflow simulation data; performing airflow turbulence characteristic analysis on the pipeline connection point airflow simulation data to generate pipeline airflow turbulence impact data; Step S42: Evaluate the airflow interference effect of the connecting points of the pipeline sections based on the pipeline airflow turbulence impact data, and generate analysis results of the pipeline air flow state impact; Step S43: Adjust the cross-sectional shape and layout design of the basic pipeline model design data according to the analysis results, and optimize the overall pipeline model of the basic pipeline model design data in combination with the pipeline segment design optimization data, thereby generating a design model of the long-distance steam supply pipeline.

10. A model design system for a long-distance steam supply pipeline, characterized in that: For executing the model design method of the long-distance steam supply pipeline according to claim 1, the model design system of the long-distance steam supply pipeline comprises: The landform division module is used to obtain the locations of the pipeline starting point and the pipeline target point; perform mid-range landform analysis based on the pipeline starting point and the pipeline target point to generate mid-range landform division data, where the mid-range landform division data includes cross-road landform data and cross-river landform data; The pipeline segment analysis module is used to perform basic pipeline modeling based on the locations of the pipeline starting point and pipeline target point, generating basic pipeline model design data; perform secondary internal stress analysis of the pipeline casing on the basic pipeline model design data using cross-road topography data to generate pipeline cross-road internal stress data; and perform suspended pipe segment self-vibration analysis on the basic pipeline model design data using cross-river topography data to generate pipeline cross-river self-vibration data; The segmented design module is used to optimize the pipeline segment geomorphology design of the basic pipeline model design data using the pipeline crossing river self-vibration data and pipeline crossing road internal stress data, and generate pipeline segment design optimization data; based on the pipeline segment design optimization data, the pipeline segment connection points of the basic pipeline model design data are confirmed; The gas supply optimization module is used to analyze the impact of pipeline section connection points on pipeline gas flow dynamics, and optimize the basic pipeline model design data based on the analysis results and pipeline section design optimization data, thereby generating a design model for long-distance steam supply pipelines.

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