CN111027240B - Buried pipeline safety assessment method and related equipment - Google Patents
Buried pipeline safety assessment method and related equipment Download PDFInfo
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- CN111027240B CN111027240B CN201911117523.3A CN201911117523A CN111027240B CN 111027240 B CN111027240 B CN 111027240B CN 201911117523 A CN201911117523 A CN 201911117523A CN 111027240 B CN111027240 B CN 111027240B
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Abstract
The embodiment of the invention discloses a buried pipeline safety evaluation method and related equipment, wherein after a pipe-soil three-dimensional nonlinear finite element model of a buried pipeline is established, a training set is established according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein the pipeline stress corresponding to the pipeline stress influence parameters under different working conditions is obtained through a finite element numerical simulation method, and is more accurate and more convenient than a theoretical calculation mode; the neural network has strong nonlinear processing capability, so that the training set can be utilized to train the neural network to obtain a pipeline stress prediction model, and when the structural reliability of the buried pipeline is calculated according to the pipeline structural reliability calculation algorithm, the pipeline stress can be quickly obtained by utilizing the pipeline stress prediction model, so that the calculation time required by the pipeline stress is shortened on the premise of ensuring the accuracy of a calculation result, the calculation efficiency of the structural reliability of the buried pipeline is improved, and the safe operation management and technical level of the buried pipeline is improved.
Description
Technical Field
The present invention relates to the field of pipeline technology, and in particular, to a method for evaluating the safety of a buried pipeline, a device for evaluating the safety of a buried pipeline, a terminal device, and a computer storage medium.
Background
In the service process of the buried pipeline, due to factors such as pipe body leakage, rain wash, construction disturbance and the like, partial soil around the pipeline is hollowed out, erosion pits are formed around the pipeline (the pipeline can also be called as pipeline suspension when the pipe section loses partial soil support), certain bending deformation or pipe orifice rotation is generated under the action of upper soil covering body load and traffic load, so that the pipeline is finally damaged and unstable, and the pipeline is an irreversible and difficult-to-judge slow catastrophe process, and huge economic loss and adverse effects are caused to society. Therefore, there is a need to solve this technical problem.
Disclosure of Invention
The embodiment of the invention provides a buried pipeline safety evaluation method and related equipment, which can evaluate the structural reliability of a buried pipeline, thereby improving the level of safety operation management and technology of the buried pipeline.
In one aspect, an embodiment of the present invention provides a method for evaluating safety of a buried pipeline, including:
establishing a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
establishing a training set according to the corresponding relation between pipeline stress influence parameters and pipeline stress of different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
performing network training by using the training set to obtain a pipeline stress prediction model;
and obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm.
Optionally, the pipeline structure reliability calculation algorithm comprises a first order second order moment method, a Monte Carlo method and a response surface method.
Optionally, the obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm includes:
randomly sampling according to probability distribution of the pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
obtaining N pipeline stresses according to the sampling value and the pipeline stress prediction model;
obtaining N bearable stresses according to the difference between the ultimate strength of the buried pipeline and the pipeline stress;
obtaining the number M of the supportable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
and calculating the structural reliability P of the buried pipeline according to the N and the number M, wherein the calculation formula of the structural reliability P is P=1-M/N.
Optionally, the method for determining the number of random samples includes:
acquiring a preset confidence coefficient, a preset allowable error and a preset structure failure probability of the buried pipeline;
and acquiring the times of random sampling according to the preset confidence level, the preset allowed error and the preset structure failure probability.
Optionally, the pipeline stress influencing parameter further comprises one or more of pipeline parameters, soil body characteristic parameters, environment parameters and load parameters.
In another aspect, an embodiment of the present invention provides a safety evaluation device for a buried pipeline, including:
the model building module is used for building a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
the training set acquisition module is used for establishing a training set according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
the model training module is used for carrying out network training by utilizing the training set to obtain a pipeline stress prediction model;
and the evaluation module is used for acquiring the structural reliability of the buried pipeline according to the pipeline stress prediction model and the pipeline structural reliability calculation algorithm.
Optionally, the pipeline structure reliability calculation algorithm comprises a first order second order moment method, a Monte Carlo method and a response surface method.
Optionally, the evaluation module includes:
the sampling sub-module is used for randomly sampling according to the probability distribution of the pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
the stress acquisition sub-module is used for acquiring N pipeline stresses according to the sampling value and the pipeline stress prediction model;
the loadable stress obtaining submodule is used for obtaining N loadable stresses according to the difference value of the ultimate strength of the buried pipeline and the pipeline stress;
the number calculation sub-module is used for obtaining the number M of the bearable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
and the reliability calculation submodule is used for calculating the structural reliability P of the buried pipeline according to the N and the number M, and the calculation formula of the structural reliability P is P=1-M/N.
In another aspect, an embodiment of the present invention provides a terminal device, including: a processor and a memory;
the processor is connected with the memory, wherein the memory is used for storing program codes, and the processor is used for calling the program codes to execute the buried pipeline safety assessment method.
In another aspect, embodiments of the present invention provide a computer storage medium storing a computer program comprising program instructions that, when executed by a processor, perform the buried pipeline security assessment method.
After a pipe-soil three-dimensional nonlinear finite element model of a buried pipeline is established, a training set is established according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline; performing network training by using the training set to obtain a pipeline stress prediction model, and obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm; the pipeline stress in the training set data is obtained by a finite element numerical simulation method, and the method is more accurate and more convenient than a theoretical calculation mode; the neural network has strong nonlinear processing capability, so that the training set can be utilized to train the neural network to obtain a pipeline stress prediction model, and when the structural reliability of the buried pipeline is calculated according to the pipeline structural reliability calculation algorithm, the pipeline stress can be quickly obtained by utilizing the pipeline stress prediction model, so that the calculation time required by the pipeline stress is shortened on the premise of ensuring the accuracy of a calculation result, the calculation efficiency of the structural reliability of the buried pipeline is improved, and the safety operation management and technical level of the buried pipeline are further improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for evaluating safety of a buried pipeline according to an embodiment of the present invention;
fig. 2a, fig. 2b, fig. 2c are schematic diagrams of a pipe-soil three-dimensional nonlinear finite element model of a buried pipeline safety evaluation method according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for evaluating safety of a buried pipeline according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a safety evaluation device for buried pipelines according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a safety evaluation device for buried pipelines according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
It should be understood that the terms "comprising" and "having" and any variations thereof in the description and claims of the present application and in the drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
As known in the prior art, the safety and reliability of the buried pipeline cannot be evaluated, especially for the condition that the pipeline is suspended, therefore, the method of the embodiment of the invention is provided to evaluate the structural reliability of the buried pipeline. Specifically, please refer to fig. 1, which is a schematic flow chart of a method for evaluating safety of a buried pipeline according to an embodiment of the present invention; the buried pipeline safety assessment method comprises the following steps:
s101, establishing a pipe-soil three-dimensional nonlinear finite element model of a buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
specifically, with the application of the finite element technology in multiple fields, nonlinear parameters of materials can be defined to perform structural static calculation, contact calculation, stress-strain calculation and the like; when solving the problem, different load steps and convergence criteria can be defined, and great convenience is provided for solving the nonlinear finite element, so that the finite element model of the buried pipeline is built in the embodiment of the invention; in order to reflect the performance influence of the erosion pit on the buried pipeline, when a model is built, the erosion pit needs to be introduced, a virtual model of the buried pipeline and soil body, namely, a three-dimensional nonlinear finite element model of a pipe-soil with the erosion pit is built, and referring to fig. 2a, 2b, 2c, 2a, 2b and 2c, a three-dimensional nonlinear finite element model schematic diagram of the pipe-soil of the buried pipeline safety evaluation method provided by the embodiment of the invention is shown, wherein the buried pipeline 22 is in the soil body 21, and the erosion pit 23 is generally positioned at the lower part of the buried pipeline 22.
Step S102, a training set is established according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
specifically, the pipe stress influencing parameter refers to a parameter that has an influence on the stress of the buried pipe, and may be a single pipe stress influencing parameter or a plurality of different pipe stress influencing parameters. Modifying parameters of the pipe-soil three-dimensional nonlinear finite element model according to the pipeline stress influence parameters of different working conditions, and performing simulation analysis according to the pipe-soil nonlinear finite element after parameter modification to obtain the pipeline stress of the buried pipeline; and finally, establishing a training set according to the corresponding relation between the pipeline stress influence parameters of different working conditions and the pipeline stress.
Step S103, performing network training by using the training set to obtain a pipeline stress prediction model;
specifically, training the neural network according to the obtained training set to obtain a trained pipeline stress prediction model.
And step S104, obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm.
Specifically, the structural reliability refers to the probability of performing a predetermined function within a prescribed time and under prescribed conditions.
From the above, the pipeline stress in the training set data is obtained by a finite element numerical simulation method, which is more accurate and more convenient than the theoretical calculation mode; because the pipeline stress influence parameter and the pipeline stress have nonlinear correlation, and the neural network has high nonlinear mapping capability, a training set obtained by using a finite element technology is used for model training to obtain a pipeline stress prediction model capable of predicting the pipeline stress, and the model can be used for approximately replacing the original finite element simulation analysis, so that the stress analysis time of the buried pipeline is effectively saved; when the structural reliability of the buried pipeline is calculated according to the pipeline structural reliability calculation algorithm, the pipeline stress can be quickly obtained by utilizing the pipeline stress prediction model, the calculation time required by the pipeline stress is reduced on the premise of ensuring the accuracy of the calculation result, the calculation efficiency of the structural reliability of the buried pipeline is improved, and the safety operation management and the technical level of the buried pipeline are further improved.
Further, the pipeline stress influence parameters comprise more than one of pipeline parameters, soil body characteristic parameters, environment parameters and load parameters besides erosion pit parameters. Referring to fig. 2b, 2c, the pit parameters include the axial length Vd, the lateral depth Vl, the circumferential angle θ of pit 23; pipe parameters refer to various specific parameters of the buried pipe, including pipe material type (pipe type, such as PVC-polyvinyl chloride pipe, DI-cast iron pipe), pipe outside diameter, wall thickness, pipe length, elastic modulus, ultimate strength, poisson's ratio, expansion coefficient, etc.; the soil characteristic parameters comprise soil type (such as protoplasm soil and backfill soil), soil density, elastic modulus, poisson ratio, friction angle, cohesive force and the like; the environmental parameters comprise the burial depth, temperature, internal pressure of the buried pipeline and the like; the load parameters comprise ground traffic load, frost heaving load and the like.
The following specifically describes the implementation process of the step S101 and the step S102:
s101, establishing a pipe-soil three-dimensional nonlinear finite element model of a buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
specifically, according to the structural design and actual construction drawing of the buried pipeline, ABAQUS finite element software (also can be FLAC3D, ANSYS and other finite element software) is used, deformation characteristics of soil under specific conditions (conditions of the buried pipeline to be evaluated), elastoplastic constants of the soil, tangential friction between pipe and soil, rigidity of the pipeline itself when being stressed and reaction of surrounding soil when the pipeline is subjected to structural deformation are comprehensively considered, and a preliminary three-dimensional nonlinear finite element model of the pipe and the soil is built according to the length, section, density, poisson ratio, elastic modulus and density, poisson ratio, elastic modulus, friction angle and cohesive force of the buried pipeline by adopting a pipe-soil nonlinear contact finite element analysis method; referring to the installation method of pipeline embankment filling in actual construction engineering, five analysis steps are established in the model to simulate the staged construction process. According to the design requirement of pipeline stress, adopting a life-death unit technology to introduce etching pits around the pipeline, defining the sizes of the etching pits, including the axial length, the transverse depth and the circumferential angle of the etching pits, and finally completing the establishment of a three-dimensional nonlinear finite element model of the pipe-soil with the etching pits, wherein the size data of the etching pits defined herein can be the size data of virtual etching pits or the size data of etching pits obtained by real measurement.
From the above, it can be seen that a three-dimensional non-linear finite element model of the pipe-soil with erosion pit is built according to the pipeline stress influence parameters of the buried pipeline.
Step S102, a training set is established according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
specifically, in order to simulate different working conditions of the buried pipeline, a control variable method is adopted to generate a plurality of groups of different pipeline stress influence parameters, the specific values of the different pipeline stress influence parameters can be modified at a time according to a permutation and combination mode to generate a plurality of groups of different pipeline stress influence parameters, the number of parameters in the pipeline stress influence parameters is the same as the number of parameters of the pipeline stress influence parameters used for originally establishing a model, for example, if the pipeline stress influence parameters have five types of erosion pit parameters, pipeline parameters, soil body characteristic parameters, environmental parameters and load parameters, the pipeline stress influence parameters of various working conditions can be obtained by modifying the values of one type of parameters or modifying the values of two types of parameters or modifying three types of parameters, and the like. And then, the parameters in the original model are replaced by the pipeline stress influence parameters under different working conditions, and the pipeline stress of the buried pipeline can be obtained by utilizing finite element analysis software, wherein the pipeline stress comprises longitudinal stress, hoop stress and radial stress. And finally, establishing a database according to the corresponding relation between the pipeline stress influence parameters of different working conditions and the pipeline stress, wherein the pipeline stress influence parameter of one working condition corresponds to one pipeline stress, and taking the database as a training set of the neural network.
According to the method, the modeling function of the finite element software is strong, modeling is convenient, and the modeling is more accurate than theoretical calculation, so that the pipeline stress in the training set data is obtained through a finite element numerical simulation method, and the modeling method is more accurate and more convenient than the theoretical calculation method.
Taking the longitudinal stress of the pipeline as an example, taking the numerical values of the modified pipeline parameter, the environment parameter and the load parameter as examples, the calculation process of the longitudinal stress of the pipeline is described as follows:
when the soil body support is lost below the buried pipeline to enable the pipeline to be locally suspended, the pipeline under the effect of the erosion pit is approximately regarded as a locally suspended beam, and certain bending deformation occurs under the effect of the upper load. Under the action of erosion pits, the pipeline generates longitudinal stress, circumferential stress and radial stress under the action of various loads. The pipeline longitudinal stress is the sum of the longitudinal stress generated by horizontal tension and the longitudinal stress caused by the internal pressure, uniform load and temperature difference of the pipeline, and the pipeline longitudinal stress is calculated by the following formula:
wherein D is the outer diameter of the pipeline, t is the wall thickness of the pipeline, P is the inner pressure of the pipeline, M (x) is the bending moment of the section of the pipeline, W is the bending resistance section coefficient of the pipeline, N is the horizontal pulling force of the pipeline, S is the cross-sectional area of the pipeline wall, E is the elastic modulus of the pipeline, and Deltat is the temperature difference.
Further, the specific implementation procedure of step S103 is as follows:
the neural network is trained according to the training set to build a neural network that correctly maps inputs (pipe stress influencing parameters) to outputs (pipe stress), i.e., a pipe stress prediction model. In the embodiment of the invention, the pipeline stress is taken as an example of simulating the pipeline longitudinal stress, and the pipeline stress prediction model predicts the pipeline longitudinal stress.
Further, in step S104, the pipeline structure reliability calculation algorithm includes a first order second order moment method, a monte carlo method, and a response surface method. The first order second moment method is a reliability analysis method that calculates the reliability of a structure based on the mean and variance of variables. The basic principle of the Monte Carlo method is a reliability analysis design method for reliability calculation statistics by utilizing random sampling, so the Monte Carlo method is called a random sampling method. The response surface method is based on statistics, can be used for solving the relation problem between random input and random correspondence of a system, and sometimes random input and random output functional relation of a structure is not easy to obtain, and can be used for approximate simulation at the moment. The specific theoretical guidance of the response surface method is that a polynomial with a definite expression form is constructed to approximately express the structural function which cannot be expressed by the display function, and the structural function is in an explicit form, and then the reliability of the calculation structure such as the Jc method (equivalent normalization method) is utilized, so that the calculation efficiency can be greatly improved.
When the reliability calculation algorithm of the pipeline structure is a Monte Carlo method, a pipeline limit state equation, namely a calculation equation of the bearing stress of the buried pipeline, needs to be established. After determining the ultimate strength of the buried pipeline, the safety coefficient of the pipeline subjected to various loads under the influence of the erosion pit is an important index for judging whether the pipeline is reliable or not. Set X 1 ，X 2 ，…，X n To influence the reliability of the pipe structure, n random variables (i.e. pipe stress influencing parameters), e.g. random variable X 1 ，X 2 ，…，X n Is the geometric dimension of the pipeline, the soil body characteristic parameter, the external environment factor and the like. According to the ultimate strength theory, the pipeline ultimate state function under the action of the erosion pit can be expressed as:
Z＝σ s -σ(X 1 ,X 2 ,…X n )，
wherein: sigma (sigma) s For ultimate strength of the pipe, σ (X 1 ,X 2 ,…X n ) Is the longitudinal stress of the pipeline under the action of random variables.
When Z is more than 0, the structure of the buried pipeline has a specified function, namely is in a reliable state;
when Z <0, the structure of the buried pipeline loses the specified function, namely is in a failure state;
when z=0, the structure of the buried pipeline is in a critical state or called a limit state.
With continued reference to fig. 3, fig. 3 is a flowchart of a method for evaluating safety of a buried pipeline according to an embodiment of the present invention, where the step S104 includes:
step S301, randomly sampling according to probability distribution of pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
specifically, the probability distribution of the pipeline stress influence parameters comprises uniform distribution and normal distribution, and N groups of specific values of the pipeline stress influence parameters are obtained by randomly sampling N times according to the probability distribution of the pipeline stress influence parameters.
Step S302, N pipeline stresses are obtained according to the sampling values and the pipeline stress prediction model;
specifically, inputting the sampled values into the pipeline stress prediction model may result in N pipeline stresses, where N pipeline longitudinal stresses are taken as an example.
Step S303, obtaining N bearable stresses according to the difference value of the ultimate strength of the buried pipeline and the pipeline stress;
specifically, N loadable stresses may be obtained according to N pipeline stresses and the pipeline limit state equation, and N Z may be obtained when the pipeline stresses are pipeline longitudinal stresses.
Step S304, obtaining the number M of the bearable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
specifically, the preset value can be adjusted according to the evaluation requirement of the reliability of the pipeline structure, and can be set to any value between the ultimate strength and 0.
Step S305, calculating structural reliability P of the buried pipeline according to the N and the number M, where a calculation formula of the structural reliability P is p=1-M/N.
Specifically, M/N is the failure probability of the buried pipeline, namely the failure probability of the buried pipeline, and the structural reliability P of the buried pipeline is 1-M/N, so that the structural reliability of the buried pipeline can be estimated according to P, and the safety management and the operation level of the buried pipeline are further improved.
The method for determining the random sampling times N comprises the following steps:
step A1, acquiring preset confidence coefficient, preset allowable error and preset structural failure probability of the buried pipeline;
specifically, specific values of the preset confidence coefficient and the preset allowable error can be set according to needs, and the preset structural failure probability of the buried pipeline is a pre-estimated structural failure probability of the buried pipeline, which is generally smaller.
And step A2, acquiring the random sampling times according to the preset confidence level, the preset allowed error and the preset structure failure probability.
Specifically, taking the confidence that the preset confidence is 95% as an example, after the preset allowable error is set, the calculation formula of the error epsilon is as follows:
wherein P is f In order to preset the structural failure probability, N is the number of random sampling, so that the larger N is, the smaller the error epsilon is, it can be seen that the number of random sampling is related to the calculation accuracy of the final structural reliability, and the accuracy of the structural failure probability tends to be stable only when the Monte Carlo simulation number is enough, namely the accuracy of the structural reliability tends to be stable. N is as followsThe formula:
N≥100/P f ，
assuming that the failure probability of the preset structure is below 0.1%, the random sampling frequency is more than 10 ten thousand times.
The process of calculating the reliability of the pipeline structure by using the first order second moment method and the response surface method can refer to the calculation process in the prior art, and will not be described in detail.
The following describes the calculation process of the reliability of the whole structure by taking a water supply pipe (including two pipes of PVC and DI, taking a PVC pipe as an example):
step S1, a riser-soil three-dimensional nonlinear finite element model is built according to the pipeline stress influence parameters in Table 1, and the pipeline longitudinal stress is taken as an example, so that the parameters influencing the pipeline longitudinal stress are numerous, and in the example, the influence of pipe diameter, wall thickness, burial depth, pipeline internal pressure, soil body characteristics and erosion pit size on the pipeline longitudinal stress is mainly analyzed. Finite element software can calculate the longitudinal stress of the pipeline by using the influence parameters.
TABLE 1
And S2, modifying the specific values of the influence parameters to obtain pipeline stress influence parameters simulating different working conditions, and obtaining corresponding pipeline longitudinal stress by utilizing finite element analysis software.
And S3, training data (pipeline stress influence parameters under different working conditions and corresponding pipeline longitudinal stress) of finite element simulation analysis by adopting a neural network due to the nonlinear recessive relation between the influence parameters and the pipeline longitudinal stress, so as to obtain a pipeline stress prediction model.
And S4, referring to the data, and determining the ultimate strength of the PVC pipe. And establishing a pipeline limit state equation (safety margin expression).
And S5, determining probability distribution of each parameter according to main parameters affecting longitudinal stress of the pipeline, such as pipe diameter, wall thickness, burial depth, soil body elastic modulus, pipeline internal pressure and erosion pit length, as shown in table 2. Root of Chinese characterBased on the probability distribution of each parameter, 10 is carried out by adopting a random sampling method 5 Subsampling to obtain 10 5 Substituting the data corresponding to the X6 into a pipeline stress prediction model to obtain 10 5 And the value of the limit function Z.
TABLE 2
And S6, calculating the structural reliability of the pipeline according to the law of large numbers, and finally calculating the structural reliability of the pipeline to be 0.963.
Based on the description of the above embodiment of the method for evaluating the safety of the buried pipeline, the embodiment of the invention also discloses a device for evaluating the safety of the buried pipeline, referring to fig. 4, fig. 4 is a schematic structural diagram of the device for evaluating the safety of the buried pipeline, provided by the embodiment of the invention, the device for evaluating the safety of the buried pipeline comprises a model building module 401, a training set obtaining module 402, a model training module 403 and an evaluating module 404; wherein:
the model building module 401 is used for building a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
the training set acquisition module 402 is configured to establish a training set according to corresponding relations between pipeline stress influence parameters and pipeline stress under different working conditions, where finite element simulation analysis is performed according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain pipeline stress of the buried pipeline, and the pipeline stress influence parameters include erosion pit parameters;
the model training module 403 is configured to perform network training by using the training set to obtain a pipeline stress prediction model;
and the evaluation module 404 is used for obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and the pipeline structural reliability calculation algorithm.
The specific functional implementation manners of the model building module 401, the training set obtaining module 402, the model training module 403, and the evaluation module 404 may refer to step S101 to step S104 in the foregoing embodiments, and will not be described herein.
Further, the simulated pipeline stress influence parameters further comprise more than one of pipeline parameters, soil body characteristic parameters, environment parameters and load parameters. The pipeline structure reliability calculation algorithm comprises a first order second moment method, a Monte Carlo method and a response surface method.
Further, referring to fig. 5, fig. 5 is a schematic structural diagram of a buried pipeline safety assessment device according to an embodiment of the present invention; the evaluation module 404 includes a sampling submodule 501, a stress acquisition submodule 502, a loadable stress acquisition submodule 503, a number calculation submodule 504, and a reliability calculation submodule 505, wherein:
the sampling submodule 501 is configured to randomly sample according to probability distribution of a pipeline stress influence parameter of the buried pipeline, where the number of random sampling is N, and obtain N groups of sampling values related to the pipeline stress influence parameter;
the stress obtaining sub-module 502 is configured to obtain N pipeline stresses according to the sampling value and the pipeline stress prediction model;
a loadable stress obtaining sub-module 503, configured to obtain N loadable stresses according to a difference between the ultimate strength of the buried pipeline and the pipeline stress;
a number calculation sub-module 504, configured to obtain a number M of the loadable stresses less than or equal to a preset value, where the preset value is less than the value of the ultimate strength;
and the reliability calculation submodule 505 is configured to calculate structural reliability P of the buried pipeline according to the N and the number M, where a calculation formula of the structural reliability P is p=1-M/N.
The specific functional implementation manners of the sampling submodule 501, the stress obtaining submodule 502, the loadable stress obtaining submodule 503, the number calculating submodule 504 and the reliability calculating submodule 505 may be referred to step S301-step S305 in the above embodiment, and will not be described herein.
Further, the apparatus further includes a sampling number determining module, the sampling number determining module including:
the preset value acquisition sub-module is used for acquiring preset confidence coefficient, preset allowable error and preset structure failure probability of the buried pipeline;
the frequency calculation sub-module is used for obtaining the frequency of the random sampling according to the preset confidence coefficient, the preset allowed error and the preset structure failure probability.
The specific function implementation manner of the preset value obtaining sub-module and the number calculating sub-module may refer to step A1 to step A2 in the above embodiment, and will not be described herein.
It should be noted that each unit or module in the buried pipeline safety assessment apparatus shown in fig. 4 and 5 may be separately or all combined into one or several other units or modules, or some unit(s) or module(s) thereof may be further split into a plurality of units or modules with smaller functions, which may achieve the same operation without affecting the implementation of the technical effects of the embodiments of the present invention. The above units or modules are divided based on logic functions, and in practical applications, the functions of one unit (or module) may be implemented by a plurality of units (or modules), or the functions of a plurality of units (or modules) may be implemented by one unit (or module).
Based on the description of the method embodiment and the device embodiment, the embodiment of the invention also provides a terminal device.
Fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 6, the above-described buried pipeline security assessment apparatus of fig. 4 to 5 may be applied to the terminal apparatus 600, and the terminal apparatus 600 may include: processor 601, network interface 604 and memory 605, in addition, the terminal device 600 may further comprise: a user interface 603, and at least one communication bus 602. Wherein the communication bus 602 is used to enable connected communications between these components. The user interface 603 may include a Display screen (Display), a Keyboard (Keyboard), and the optional user interface 603 may further include a standard wired interface, a wireless interface, among others. The network interface 604 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 605 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 605 may also optionally be at least one storage device located remotely from the processor 601. As shown in fig. 6, an operating system, a network communication module, a user interface module, and a device control application program may be included in the memory 605, which is one type of computer storage medium.
In the terminal device 600 shown in fig. 6, the network interface 604 may provide a network communication function; while the user interface 603 is primarily an interface for providing input to the user; and processor 601 may be used to invoke a device control application stored in memory 605 to implement:
establishing a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
establishing a training set according to the corresponding relation between pipeline stress influence parameters and pipeline stress of different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
performing network training by using the training set to obtain a pipeline stress prediction model;
and obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm.
In one embodiment, the simulated pipeline stress influencing parameters further comprise one or more of pipeline parameters, soil body characteristic parameters, environment parameters and load parameters. The pipeline structure reliability calculation algorithm comprises a first order second moment method, a Monte Carlo method and a response surface method.
In one embodiment, the processor 601, when executing the process of obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and the pipeline structural reliability calculation algorithm, specifically performs the following steps:
randomly sampling according to probability distribution of the pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
obtaining N pipeline stresses according to the sampling value and the pipeline stress prediction model;
obtaining N bearable stresses according to the difference between the ultimate strength of the buried pipeline and the pipeline stress;
obtaining the number M of the supportable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
and calculating the structural reliability P of the buried pipeline according to the N and the number M, wherein the calculation formula of the structural reliability P is P=1-M/N.
In one embodiment, the processor 601 is further configured to perform the steps of:
acquiring a preset confidence coefficient, a preset allowable error and a preset structure failure probability of the buried pipeline;
and acquiring the times of random sampling according to the preset confidence level, the preset allowed error and the preset structure failure probability.
It should be understood that the terminal device 600 described in the embodiments of the present invention may perform the description of the method for evaluating the safety of the buried pipeline in the embodiments corresponding to fig. 1 to 3, and may also perform the description of the apparatus for evaluating the safety of the buried pipeline in the embodiments corresponding to fig. 4 to 5, which are not repeated herein. In addition, the description of the beneficial effects of the same method is omitted.
Furthermore, it should be noted here that: the embodiment of the present invention further provides a computer storage medium, in which a computer program executed by the above-mentioned buried pipeline safety assessment device is stored, and the computer program includes program instructions, when the processor executes the program instructions, the description of the buried pipeline safety assessment method in the embodiment corresponding to fig. 1 to 3 can be executed, and therefore, the description will not be repeated here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer storage medium according to the present invention, please refer to the description of the method embodiments of the present invention.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The foregoing disclosure is illustrative of the present invention and is not to be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (10)
1. A method for evaluating the safety of a buried pipeline, comprising:
establishing a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
establishing a training set according to the corresponding relation between pipeline stress influence parameters and pipeline stress of different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
performing network training by using the training set to obtain a pipeline stress prediction model;
and obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm.
2. The method of claim 1, wherein the pipeline structure reliability calculation algorithm comprises a first order second order moment method, a monte carlo method, a response surface method.
3. The method according to claim 1 or 2, wherein the obtaining the structural reliability of the buried pipeline according to the pipeline stress prediction model and a pipeline structural reliability calculation algorithm comprises:
randomly sampling according to probability distribution of the pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
obtaining N pipeline stresses according to the sampling value and the pipeline stress prediction model;
obtaining N bearable stresses according to the difference between the ultimate strength of the buried pipeline and the pipeline stress;
obtaining the number M of the supportable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
and calculating the structural reliability P of the buried pipeline according to the N and the number M, wherein the calculation formula of the structural reliability P is P=1-M/N.
4. A method according to claim 3, wherein the method of determining the number of random samples comprises:
acquiring a preset confidence coefficient, a preset allowable error and a preset structure failure probability of the buried pipeline;
and acquiring the times of random sampling according to the preset confidence level, the preset allowed error and the preset structure failure probability.
5. The method of claim 1 or 2, wherein the pipe stress influencing parameters further comprise one or more of pipe parameters, soil body characteristic parameters, environmental parameters, load parameters.
6. A buried pipeline safety assessment device, comprising:
the model building module is used for building a pipe-soil three-dimensional nonlinear finite element model of the buried pipeline, wherein the pipe-soil three-dimensional nonlinear finite element model comprises an erosion pit;
the training set acquisition module is used for establishing a training set according to the corresponding relation between pipeline stress influence parameters and pipeline stress under different working conditions, wherein finite element simulation analysis is carried out according to the pipeline stress influence parameters and the pipe-soil three-dimensional nonlinear finite element model to obtain the pipeline stress of the buried pipeline, and the pipeline stress influence parameters comprise erosion pit parameters;
the model training module is used for carrying out network training by utilizing the training set to obtain a pipeline stress prediction model;
and the evaluation module is used for acquiring the structural reliability of the buried pipeline according to the pipeline stress prediction model and the pipeline structural reliability calculation algorithm.
7. The apparatus of claim 6, wherein the pipeline structure reliability calculation algorithm comprises a first order second order moment method, a monte carlo method, a response surface method.
8. The apparatus of claim 6 or 7, wherein the evaluation module comprises:
the sampling sub-module is used for randomly sampling according to the probability distribution of the pipeline stress influence parameters of the buried pipeline, wherein the number of random sampling is N, and N groups of sampling values about the pipeline stress influence parameters are obtained;
the stress acquisition sub-module is used for acquiring N pipeline stresses according to the sampling value and the pipeline stress prediction model;
the loadable stress obtaining submodule is used for obtaining N loadable stresses according to the difference value of the ultimate strength of the buried pipeline and the pipeline stress;
the number calculation sub-module is used for obtaining the number M of the bearable stress smaller than or equal to a preset value, wherein the preset value is smaller than the value of the ultimate strength;
and the reliability calculation submodule is used for calculating the structural reliability P of the buried pipeline according to the N and the number M, and the calculation formula of the structural reliability P is P=1-M/N.
9. A terminal device, comprising: a processor and a memory;
the processor is connected to a memory, wherein the memory is configured to store program code, and the processor is configured to invoke the program code to perform the buried pipeline security assessment method of any of claims 1-5.
10. A computer storage medium storing a computer program comprising program instructions which, when executed by a processor, perform the buried pipeline security assessment method of any one of claims 1 to 5.
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| CN112149332B (en) * | 2020-09-27 | 2022-12-27 | 大唐东北电力试验研究院有限公司 | Safety state evaluation method for steam-water pipeline supporting and hanging system of thermal power plant |
| CN112487712B (en) * | 2020-11-25 | 2024-08-23 | 中国科学院力学研究所 | Intelligent identification method for buried suspended pipeline working condition parameters based on genetic algorithm and multidimensional dynamic time regularity |
| CN114323941A (en) * | 2021-12-22 | 2022-04-12 | 广东省特种设备检测研究院珠海检测院 | Reliability evaluation method for buried PE pipe electric melting joint with outer surface axial cracks |
| CN115544702B (en) * | 2022-10-25 | 2023-05-02 | 中国石油大学(北京) | Oil-gas pipeline immersed tube construction stress checking method, device, equipment and storage medium |
| CN116305947B (en) * | 2023-03-20 | 2023-10-17 | 中国石油大学(北京) | Buried pipeline stress prediction method, safety evaluation method, equipment and storage medium |
| CN116341295B (en) * | 2023-05-30 | 2023-07-25 | 交通运输部公路科学研究所 | Road stability assessment method and system based on underground pipeline |
| CN117195573B (en) * | 2023-09-15 | 2024-05-31 | 西南石油大学 | Buried pipeline reliability calculation method |
| CN117852325B (en) * | 2024-03-08 | 2024-06-11 | 应急管理部国家自然灾害防治研究院 | Pipeline failure stress simulation calculation method under earthquake action |
| CN118629546A (en) * | 2024-08-14 | 2024-09-10 | 山东固风科技有限公司 | Stress analysis and prediction system for epoxy structural adhesive |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1979496A (en) * | 2005-12-02 | 2007-06-13 | 中国科学院金属研究所 | Copper-alloy pipe-material casting-milling technology parameter designing and optimizing method |
| CN108959721A (en) * | 2018-06-11 | 2018-12-07 | 长安大学 | A kind of Longspan Bridge member reliability calculation method under windmill load action |
| CN109855993A (en) * | 2019-03-04 | 2019-06-07 | 广东省特种设备检测研究院珠海检测院 | A kind of buried PE gas pipeline life detecting method containing defect |
-
2019
- 2019-11-14 CN CN201911117523.3A patent/CN111027240B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1979496A (en) * | 2005-12-02 | 2007-06-13 | 中国科学院金属研究所 | Copper-alloy pipe-material casting-milling technology parameter designing and optimizing method |
| CN108959721A (en) * | 2018-06-11 | 2018-12-07 | 长安大学 | A kind of Longspan Bridge member reliability calculation method under windmill load action |
| CN109855993A (en) * | 2019-03-04 | 2019-06-07 | 广东省特种设备检测研究院珠海检测院 | A kind of buried PE gas pipeline life detecting method containing defect |
Non-Patent Citations (1)
| Title |
|---|
| Xiaoben Liu 等.An ANN-based failure pressure prediction method for buried high-strength pipes with stray current corrosion defect.Energy Science & Engineering.2019,全文. * |
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