A Five-Factor Dual-Competition Strain Prediction Model for High-Strength Steel Pipelines under Landslide Action

Abstract

The present invention belongs to the field of pipeline safety assessment and relates to a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides. The present invention establishes a three-dimensional finite element model of a high-grade steel pipeline under the action of landslides through the finite element method, simulates and calculates the maximum axial strain of the pipeline under different pipe diameters, wall thicknesses, internal pressures, landslide widths and landslide cross-sectional areas, and establishes a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides according to the simulation results; this model takes into account the coupling effect between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area, and can calculate the maximum axial strain on both the left and right sides of the pipeline at the same time, so as to determine the maximum axial strain of the pipeline. A five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides has been verified with high prediction accuracy, providing an effective mathematical calculation method for strain prediction of high-grade steel pipelines under the action of landslides and having strong practicability.

Description

Technical Field

[0001] The present invention belongs to the field of pipeline safety assessment, and relates to a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides. Background Art

[0002] With the continuous development of oil and natural gas, the total mileage of oil and gas pipelines continues to increase, and high-grade steel materials are widely used in long-distance natural gas pipelines. During the laying process of long-distance natural gas pipelines, it is inevitable to cross mountainous areas prone to landslides. The risk of fracture failure of high-grade steel pipelines under the action of landslides increases. If the pipeline fails due to fracture, it will not only cause serious economic losses but also cause environmental pollution. Therefore, it is necessary to study the mechanical behavior prediction method of high-grade steel pipelines under the action of landslides.

[0003] At present, the oil and gas industry generally studies the stress changes of pipelines under the action of landslides. However, high-grade steel materials have good ductility, and the elongation rate exceeds 10%. Stress cannot fully reflect the mechanical behavior of high-grade steel pipelines, and the mechanical behavior should be studied based on the strain of high-grade steel pipelines.

[0004] The strain of high-grade steel pipelines under the action of landslides is affected by multiple parameters, and there are interactions between some factors, which makes strain prediction very difficult. At present, many scholars have studied strain prediction models. He et al. established a stress prediction model for three points of the pipeline using a genetic-backpropagation neural network for pipelines with girth welds under the action of landslides. Xiang et al. established a mathematical model for strain prediction in three directions of the pipeline based on the strain simulation results of landslide pipelines under different influencing factors. Liu Peng et al. established a prediction model for the mechanical behavior of pipelines using machine learning methods by combining pipeline landslide tests and numerical simulations.

[0005] At present, most of the prediction models for the mechanical behavior of pipelines under the action of landslides rely on machine learning algorithms to construct, but the mathematical models for strain are relatively scarce. Therefore, based on the simulation results of the three-dimensional finite element model of high-grade steel pipelines under the action of landslides, the present invention establishes a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides, providing a new method for the field of pipeline strain prediction models. Summary of the Invention

[0006] Aiming at the deficiencies of the existing strain prediction models, the present invention proposes a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides.

[0007] The establishment process of a five-factor dual-competition strain prediction model for high-grade steel pipelines under the action of landslides mainly includes the following four steps:

[0008] S101: Considering the non-linear discontinuous action between the landslide and the pipeline, a three-dimensional finite element model of the high-grade steel pipeline under the action of the landslide is established by the finite element method;

[0009] S102: According to the main influencing factors of the axial strain of the landslide pipeline, calculate the maximum axial strains of the pipeline in the 3 o'clock (near the landslide direction) and 9 o'clock (far from the landslide direction) directions under different pipe diameters, wall thicknesses, internal pressures, landslide widths and landslide cross-sectional areas respectively;

[0010] S103: Establish a five-factor maximum axial strain prediction function model of the high-grade steel pipeline under the action of the landslide,

[0011] ε = a·f(D)+b·f(t)+c·f(L)+d·f(A)+e·f(P)+C

[0012] Where: ε—the maximum axial strain of the pipeline; a~e—coefficients; f(x)—the functional relationship between the x factor and the strain; C—constant term;

[0013] S104: According to the finite element simulation results, use the non-linear regression algorithm to determine the coefficient terms and constant term of the maximum axial strain prediction function model,

[0014]

[0015]

[0016] Where: ε3—the maximum axial strain in the 3 o'clock direction of the pipeline, dimensionless; ε9—the maximum axial strain in the 9 o'clock direction of the pipeline, dimensionless; D—pipe diameter of the pipeline, mm; t—wall thickness of the pipeline, mm; L—landslide width, m; A—landslide cross-sectional area, m 2 ; P—internal pressure of the pipeline, MPa.

[0017] The finite element simulation and the prediction model consider the influence of the landslide cross-sectional area on the maximum axial strain of the pipeline.

[0018] The prediction model can calculate the maximum axial strains in the 3 o'clock and 9 o'clock directions of the pipeline respectively, and determine the true maximum axial strain of the pipeline by comparing the results of the two.

[0019] A five-factor double-competition strain prediction model of a high-grade steel pipeline under the action of a landslide considers the coupling effect between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area, and establishes a coupling model between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area Description of the Drawings

[0020] Figure 1 It is a linear fitting diagram of the predicted value and the simulated value in the 3 o'clock direction of the pipeline in a five-factor double-competition strain prediction model of a high-grade steel pipeline under the action of a landslide.

[0021] Figure 2 It is a linear fitting diagram of the predicted value and the simulated value in the 9 o'clock direction of the pipeline in the five-factor double-competition strain prediction model of high-grade steel pipelines under landslide action. Specific implementation manner

[0022] The specific implementation manner of a five-factor double-competition strain prediction model of high-grade steel pipelines under landslide action is as follows:

[0023] Step 1: Considering the non-linear discontinuous action between the landslide and the pipeline, a three-dimensional finite element model of the high-grade steel pipeline under landslide action is established by the finite element method.

[0024] Step 2: According to the main influencing factors of the axial strain of the landslide pipeline, both the finite element simulation and the prediction model consider the influence of the landslide cross-sectional area on the maximum axial strain of the pipeline, and calculate the maximum axial strains of the pipeline in the 3 o'clock (close to the landslide direction) and 9 o'clock (far from the landslide direction) directions under different pipe diameters (609, 800, 1016, 1219, 1422 mm), wall thicknesses (10.6, 13.6, 15.6, 18.4, 21.8 mm), internal pressures (4, 6, 8, 10, 12 MPa), landslide widths (10, 20, 30, 40, 50 m) and landslide cross-sectional areas (28, 55, 64, 96, 114 m 2 ) respectively.

[0025] Step 3: Establish a five-factor maximum axial strain prediction function model of the high-grade steel pipeline under landslide action,

[0026] ε = a·f(D) + b·f(t) + c·f(L) + d·f(A) + e·f(P) + C

[0027] In the formula: ε—the maximum axial strain of the pipeline; a~e—coefficients; f(x)—the functional relationship between the x factor and the strain; C—constant term.

[0028] Step 4: Considering the coupling effect between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area, establish a coupling model between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area; according to the finite element simulation results, adopt a non-linear regression algorithm to determine the coefficient terms and constant terms of the maximum axial strain prediction function model. The prediction model can calculate the maximum axial strains of the pipeline in the 3 o'clock and 9 o'clock directions respectively, and determine the true maximum axial strain of the pipeline by comparing the two results.

[0029]

[0030]

[0031] Where: ε3—the maximum axial strain in the direction of point 3 of the pipeline, dimensionless; ε9—the maximum axial strain in the direction of point 9 of the pipeline, dimensionless; D—the pipeline diameter, mm; t—the pipeline wall thickness, mm; L—the landslide width, m; A—the landslide cross-sectional area, m 2 ; P—the internal pressure of the pipeline, MPa.

[0032] The linear fitting diagrams of the predicted values and the simulated values in the directions of point 3 and point 9 of the pipeline in a five-factor double-competition strain prediction model for high-grade steel pipelines under landslide action are shown respectively in Figure 1 and Figure 2 . The slopes of the fitting lines are 0.954 and 0.969 respectively, indicating that the prediction model has high accuracy.

[0033] The practicability of a five-factor double-competition strain prediction model for high-grade steel pipelines under landslide action is verified through on-site application. According to the on-site landslide pipeline parameters in Table 1, the maximum relative error of the model strain prediction is 11.36%, and the average relative error is 9.78%. It shows that the model can accurately predict the maximum axial strain and its position of the landslide pipeline and has good practicability.

[0034] Table 1 On-site landslide pipeline parameters

[0035] Pipe diameter / mm Wall thickness / mm Landslide width / m <![CDATA[Landslide cross-sectional area / m 2 > Internal pressure 1016 15.6 25 35 6

[0036] Table 2 Strain detection and prediction results of on-site landslide pipelines

[0037]

Claims

1. A five-factor double-competition strain prediction model for high-grade pipelines under landslide action, characterized in that, It includes the following processes: S101: Considering the nonlinear discontinuous action between the landslide and the pipeline, establish a three-dimensional finite element model of the high-grade steel pipeline under the action of the landslide by the finite element method; S102: According to the main influencing factors of the axial strain of the landslide pipeline, calculate the maximum axial strains of the pipeline at point 3 near the landslide direction and point 9 far from the landslide direction under different pipe diameters, wall thicknesses, internal pressures, landslide widths and landslide cross-sectional areas respectively; S103: Establish a prediction function model for the maximum axial strain of the high-grade steel pipeline with five factors under the action of the landslide, ε = a·f(D) + b·f(t) + c·f(L) + d·f(A) + e·f(P) + C where: ε—the maximum axial strain of the pipeline; a to e—coefficients; f(x)—the functional relationship between the x factor and the strain; C—constant term; S104: According to the finite element simulation results, use the nonlinear regression algorithm to determine the coefficient terms and constant term of the maximum axial strain prediction function model, Where: ε3—the maximum axial strain in the direction of point 3 of the pipeline, dimensionless; ε9—the maximum axial strain in the direction of point 9 of the pipeline, dimensionless; D—the pipeline diameter, mm; t—the pipeline wall thickness, mm; L—the landslide width, m; A—the landslide cross-sectional area, m 2 ; P—the internal pressure of the pipeline, MPa.

2. The five-factor dual-competition strain prediction model for high-grade pipelines under landslide action according to claim 1, wherein The finite element simulation and the prediction model consider the influence of the landslide cross-sectional area on the maximum axial strain of the pipeline.

3. The five-factor dual-competition strain prediction model for high-grade pipelines under landslide action according to claim 1, characterized in that, The prediction model can calculate the maximum axial strains in the directions of point 3 and point 9 of the pipeline respectively, and determine the true maximum axial strain of the pipeline by comparing the results of the two.

4. A five-factor dual-competition strain prediction model for high-grade pipelines under landslide action according to claim 1, characterized in that The prediction model considers the coupling effect between the pipe diameter, wall thickness, landslide width and landslide cross-sectional area: A coupling model among pipe diameter, wall thickness, landslide width and landslide cross-sectional area was established

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