Global conservation transient flow decoupling calculation method, device, medium and equipment suitable for multi-element medium pipe network transmission

Abstract

The present application relates to a kind of global conservation transient flow decoupling calculation method, device, medium and equipment suitable for multi-medium pipe network transport, method includes: according to pipe network multi-medium flow state parameter and spatial distribution characteristics, construct the dynamic conservation model of pipe network multi-medium transient flow field considering the emergence or disappearance of multi-medium;According to the dynamic conservation model of pipe network multi-medium transient flow field, dynamic tracking multi-medium disappears or appears and flow state changes, based on pipe network multi-medium spatial distribution characteristics real-time construction pipe network multi-medium transient flow field dynamic conservation model, and decoupling is solved to pipe network model.This method can ensure the stability and adaptability of algorithm when different medium disappears or adds and medium state changes, also has certain applicability to oil and gas medium;And when pipe network is solved, ensure the conservation of the whole of pipe network solution, can decoupling be solved to pipe and junction for pipe network structure, to improve calculation efficiency.

Description

Technical Field

[0001] This invention relates to a method, apparatus, medium, and equipment for calculating transient flow decoupling with global conservation applicable to multi-medium pipeline transportation, belonging to the fields of multi-medium pipeline simulation and new energy transportation technology. Background Technology

[0002] The safe and efficient integration and co-transport of different new energy media such as carbon dioxide, methanol, and oil and gas in pipeline networks, maximizing the use of existing infrastructure, has become a future development trend. This flexible multi-media transportation mode can not only alleviate the problem of redundant pipeline construction during the energy transition period, but also promote the transformation of the energy system from "production-oriented" to "demand-response", providing key support for building a clean, low-carbon, safe and efficient modern energy system.

[0003] The operation and development of my country's pipeline network presents new trends, mainly in the following aspects: (1) Construction and commissioning of supercritical / dense phase CO2 multiphase transport pipelines. (2) Integrated transport and distribution of multi-media pipelines such as methanol-conventional oil and gas resources. (3) Large-scale development of deep-water oil and gas multi-component media pipeline networks. However, in the flexible transport process of multi-media pipeline networks, due to the different types of energy media, there are significant interphase interfaces of multiphase media such as supercritical-dense phase, methanol-finished oil, and oil-gas during transport; and due to the continuous changes in temperature and pressure along the pipeline, interphase mass transfer occurs frequently during the flow process, which greatly increases the difficulty of tracking various media and significantly increases the difficulty of predicting flow parameters. Therefore, accurate and rapid calculation of flow parameters in the multi-media transport process and mastering the distribution of multi-media along the pipeline are crucial for the safe and efficient operation of multi-media pipeline networks. The calculation method for multi-media pipeline transportation can not only simulate the production and operation status in real time, ensure the safe operation of the pipeline and realize media tracking, but also simulate and optimize working conditions such as shutdown, pipeline cleaning, leakage, and cross-section tracking, thereby reducing operating costs and improving economic benefits.

[0004] Currently, the difficulty in solving transient problems related to flexible transportation in multi-medium pipeline networks stems primarily from two factors: Firstly, multi-medium pipeline networks present significant challenges in numerical solution methods. Explicit solution methods are strictly constrained by the CFL criterion, while implicit solution methods are difficult to construct. Furthermore, when different media disappear or are added during pipeline operation, existing methods typically maintain computational stability by artificially limiting the range of media presence, leading to a loss of the conservation of the original equations and an increase in numerical errors. Secondly, compared to single-medium systems, multi-medium pipeline networks face greater challenges in terms of computational complexity. Multi-medium pipeline networks involve more equations and unknowns, resulting in a dramatic increase in computational load and low computational efficiency. Moreover, in the handling of pipeline sinks, multi-medium pipeline networks present the problem of tracking the states of different media. Properly handling the calculation of unknowns at sinks has a significant impact on ensuring the conservation and stability of the equations.

[0005] Therefore, there is an urgent need to propose an efficient and conservation-based transient decoupling algorithm for multi-medium pipeline networks. This algorithm should not only be applicable to the flow prediction of new energy media (multi-state, multi-medium), but also have certain applicability to oil and gas media. This will help adapt to the development trend of flexible transportation in my country's multi-medium pipeline networks and contribute to the efficient and safe operation of multi-medium pipeline transportation. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a method, apparatus, medium, and equipment for decoupled transient flow calculation with global conservation applicable to multi-medium pipeline networks. This method ensures the stability and adaptability of the algorithm when different media disappear or are added, or when the media state changes. It is applicable not only to the flow prediction of new energy media (multi-state, multi-medium) but also to oil and gas media. Furthermore, it ensures the overall conservation of the pipeline network solution and can decouple the pipelines and sinks for solution based on the pipeline structure, thereby improving computational efficiency. In addition, this algorithm can update the flow parameters of multi-medium pipeline networks and the flow conditions of different media at the same time level and is not limited by the CFL criterion.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A method for decoupling transient flow with global conservation applicable to multi-medium pipeline transportation includes:

[0009] Based on the flow state parameters and spatial distribution characteristics of multi-medium media in the pipeline network, a dynamic conservation model of transient flow field of multi-medium media in the pipeline network is constructed, taking into account the appearance or disappearance of multi-medium media.

[0010] Based on the dynamic conservation model of transient flow field of multi-medium in pipeline network, the disappearance or appearance of multi-medium and the change of flow state are dynamically tracked. Based on the spatial distribution characteristics of multi-medium in pipeline network, the dynamic conservation model of transient flow field of multi-medium in pipeline network is constructed in real time, and the pipeline network model is decoupled and solved.

[0011] The aforementioned method for decoupling and conserving transient flow in multi-medium pipeline networks, preferably, constructs a dynamic conservation model of the transient flow field of multi-medium pipelines that considers the presence or absence of multi-medium components, based on the flow state parameters and spatial distribution characteristics of the multi-medium flow in the pipeline network. Specifically, this is manifested as follows:

[0012] Read the overall structure of the pipeline network, form pipeline modules and node modules, and assign status parameters;

[0013] Based on the flow state parameters and spatial distribution characteristics of the multi-medium media in the pipeline module and node module, a dynamic conservation model of the transient flow field of multi-medium media in the pipeline network is constructed, taking into account the appearance or disappearance of multi-medium media.

[0014] The aforementioned method for decoupling and conserving transient flow in multi-medium pipeline networks, preferably, includes a dynamic conservation model for the transient flow field of multi-medium pipeline networks, which mainly comprises:

[0015] Dynamic conservation model of transient flow field in a pipeline with multiple media:

[0016]

[0017] Dynamic conservation model of transient flow field in nodal multi-medium medium:

[0018]

[0019] in, f(res T The overall behavior exhibits conservation characteristics in both the time domain and the flow field. It exhibits dynamic conservation characteristics and can adaptively respond to the dynamic changes of multi-media. When complex working conditions such as the appearance or disappearance of different media occur, it can dynamically adjust the conservation equation in real time to maintain the overall dynamic conservation relationship of the system; res is the residual equation, the subscripts P and J represent the scope of the equation, and the sub-tables represent the pipes and nodes; ρ is the density of the multi-media. Φ is the spatial phase content of the multi-component medium; v is the velocity of the multi-component medium; A is the area of ​​the control volume; t is time; x is the distance to the control volume; Φ is the mass transfer at the interface between different multi-component media; P is the spatial pressure of the multi-component medium; g is the gravitational acceleration; θ is the tilt angle of the control volume; F w F represents the frictional force between the multi-medium medium and the wall surface. i For the interaction force between different multi-component media; F eThe work done on the multi-component medium by external forces, excluding the medium itself; T is the temperature of the multi-component medium; C P Specific heat at constant pressure; subscript i represents the type of multi-component medium, such as CO2, methanol, oil and gas, etc.; subscript k represents the thermodynamic state of the multi-component medium, such as gas phase, liquid phase, dense phase, supercritical phase, etc.; subscript d represents the disappearing or appearing medium term; M represents the continuous term of disappearing medium transfer.

[0020] The aforementioned method for decoupling and calculating transient flow with global conservation applicable to multi-medium pipeline transportation preferably involves, based on a dynamic conservation model of the transient flow field of the multi-medium pipeline, dynamically tracking the disappearance or appearance of the multi-medium media, constructing a dynamic conservation model of the transient flow field of the multi-medium pipeline in real time based on the spatial distribution characteristics of the multi-medium media in the pipeline, and decoupling and solving the pipeline model. Specifically, this is manifested as follows:

[0021] By combining the time, space and interface flux discretization schemes of pipeline module and node module with the current multi-medium flow state, a multi-medium flow matrix is ​​constructed for different modules;

[0022] The PJFNK fully implicit algorithm is used in conjunction with the multi-medium flow matrix to dynamically track the disappearance or appearance of multi-medium media and decouple the solution to solve the dynamic conservation model of transient multi-medium flow field in the pipeline network.

[0023] The aforementioned method for decoupling and calculating transient flow with full conservation applicable to multi-medium pipeline transportation preferably employs the PJFNK fully implicit algorithm combined with the multi-medium flow matrix to dynamically track the disappearance or appearance of multi-medium media and decouple and solve the dynamic conservation model of the transient flow field of multi-medium media in the pipeline network. Specifically, this is manifested as follows:

[0024] Based on the pipeline network topology, the pipelines and nodes are separated into independent calculation modules. The PGMRES method is used in combination with the multi-medium flow matrix to solve the dynamic conservation model of the transient multi-medium flow field of the pipeline-node, and the flow parameters are updated through intra-time iteration.

[0025] Based on the flow parameters of the pipeline module and node module within the time-layer iterative step, the disappearance or appearance of the multi-element medium is dynamically tracked. Based on the current state of the multi-element medium, the dynamic conservation model of the transient flow field of the multi-element medium is dynamically updated and the flow matrix of the multi-element medium is reconstructed until the entire pipeline network converges, and then the flow parameters of the next time step are updated.

[0026] A second aspect of the present invention provides a transient flow decoupling calculation device with global conservation suitable for multi-medium pipeline transportation, comprising:

[0027] The pipeline information identification module is used to identify relevant pipeline information and node information by combining the input pipeline information, thereby constructing pipeline modules and node modules;

[0028] The multi-medium flow parameter prediction module is used to calculate the flow parameters of each multi-medium in the pipeline module and node module, including the spatial medium content, pressure, velocity, temperature, viscosity, and specific heat information of each medium.

[0029] A module for constructing a dynamic conservation model of transient flow field in multiple media is used for dynamic updates of the module in the pipeline module and node module.

[0030] The fully implicit method solution module is used for fully implicit solutions of pipe and node modules, including the construction of the PGMRES method, the appearance or disappearance of multi-component media, and the implementation of the PJFNK method.

[0031] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-medium pipeline transportation as described in any one of the preceding claims.

[0032] The fourth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-medium pipeline transportation as described in any one of the above.

[0033] The present invention has the following advantages due to the adoption of the above technical solutions:

[0034] The computational method of this invention maintains stability and adaptability even when different media disappear or are added, or when the state of the media changes. It is applicable not only to the flow prediction of new energy media (multi-state, multi-media) but also to oil and gas media. Furthermore, it ensures the overall conservation of the pipeline network solution and can decouple pipelines and sinks based on the pipeline network structure to improve computational efficiency. In addition, this algorithm can update the flow parameters of multi-media pipeline networks and the flow conditions of different media at the same time level, and is not limited by the CFL criterion. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating a transient flow decoupling calculation method with global conservation applicable to multi-medium pipeline transportation, provided by an embodiment of the present invention.

[0036] Figure 2 This is a flowchart illustrating step 100 provided in this embodiment of the present invention;

[0037] Figure 3 This is a flowchart illustrating step 200 provided in this embodiment of the present invention;

[0038] Figure 4 This is a flowchart illustrating step 230 of this embodiment of the invention;

[0039] Figure 5 This is a schematic diagram of the transient results of the changes in the internal phase (Figure a), flow rate (Figure b), temperature (Figure c), and pressure (Figure d) of the CO2 pipeline from the initial supercritical phase state to the stable operation in Example 1 of the present invention.

[0040] Figure 6 This is a schematic diagram of the transient results of diesel content (Figure a), pressure (Figure b), diesel mass flow rate (Figure c), and methanol mass flow rate (Figure d) along the methanol-diesel multi-media pipeline during transient operation in Example 2 of the present invention.

[0041] Figure 7 This is a schematic diagram of a certain gathering and transmission pipeline structure in this specific application example of the present invention;

[0042] Figure 8 This is a schematic diagram of the steady-state results of temperature (Figure b), pressure (Figure a), gas phase mass flow rate (Figure d), liquid phase mass flow rate (Figure c), and total mass flow rate (Figure e) along the pipes Pipe 1, Pipe 2, and Pipe 4 connected to Junction 1 in Example 3 of the present invention.

[0043] Figure 9 This is a schematic diagram showing the transient results of the phase content (Figures a and b), pressure (Figures c and d), and liquid mass flow rate (Figures e and f) along the pipelines Pipe1, Pipe2, and Pipe4 connected to Junction1 as a function of the present invention over time in Example 4 of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described clearly and completely below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0045] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," "third," "fourth," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0046] For ease of description, spatial relative terms may be used in the text to describe the relationship of one element or feature relative to another element or feature as shown in the figure. These relative terms include, for example, "inside," "outside," "middle," "outer," "below," "above," etc. Such spatial relative terms are intended to include different orientations of the device in use or operation, other than those depicted in the figure.

[0047] On the one hand, explicit solution methods are strictly limited by the CFL criterion, while implicit solution methods are difficult to construct. Furthermore, when different media disappear or are added during pipeline operation, existing methods typically maintain computational stability by artificially limiting the range of media, leading to a loss of the conservation of the original equations and an increase in numerical errors. On the other hand, compared to single-media systems, multi-media pipelines face greater challenges in terms of computational complexity. Multi-media pipelines involve more equations and unknowns, resulting in a surge in computational load and low efficiency. Moreover, in the handling of pipeline sinks, multi-media pipelines present the problem of tracking the states of different media. Properly handling the calculation of unknowns at sinks significantly impacts the conservation and stability of the equations. Therefore, there is an urgent need to propose an efficient and conservation-based transient decoupling algorithm for multi-media pipelines to adapt to the development trend of flexible transportation in my country's multi-media pipelines and contribute to the efficient and safe operation of multi-media pipeline transportation.

[0048] To address the aforementioned technical issues, this invention provides a method, apparatus, medium, and equipment for decoupling transient flow with global conservation applicable to multi-medium pipeline transportation. This method ensures the stability and adaptability of the algorithm when different media disappear or are added, or when the media state changes. It is applicable not only to the flow prediction of new energy media (multi-state, multi-medium) but also to oil and gas media. Furthermore, it guarantees the overall conservation of the pipeline network solution and can decouple pipelines and sinks based on the pipeline structure to improve computational efficiency. In addition, this algorithm can update the flow parameters of the multi-medium pipeline network and the flow conditions of different media at the same time level and is not limited by the CFL criterion.

[0049] like Figure 1 As shown, the transient flow decoupling calculation method with global conservation applicable to multi-medium pipeline transportation provided by this invention includes the following specific steps:

[0050] Step 100: Based on the flow state parameters and spatial distribution characteristics of the multi-medium flow in the pipeline network, construct a dynamic conservation model of the transient flow field of the multi-medium flow in the pipeline network that considers the appearance or disappearance of the multi-medium and changes in the flow state.

[0051] Step 200: Based on the dynamic conservation model of transient flow field of multi-medium in pipeline network, dynamically track the disappearance or appearance of multi-medium and the change of flow state. Based on the spatial distribution characteristics of multi-medium in pipeline network, construct the dynamic conservation model of transient flow field of multi-medium in pipeline network in real time, and decouple and solve the pipeline network model.

[0052] Specifically, based on the flow state parameters and spatial distribution characteristics of multi-medium media in a pipeline network, a dynamic conservation model of the transient flow field of multi-medium media in a pipeline network is constructed, considering the presence or absence of multi-medium media. This includes not only the construction of the dynamic conservation model of the transient flow field of multi-medium media in a pipeline network but also the decomposition of the pipeline network structure and the storage of flow parameters, such as... Figure 2 As shown, step 100 specifically includes the following steps:

[0053] Step 110: Read the overall structure of the pipeline network, including the number of pipelines and nodes. Create a separate module for each pipeline and an overall module for all nodes.

[0054] Specifically, for a pipeline network containing N pipelines and M nodes connecting the pipelines, the number of pipeline modules is M, the number of node modules is 1, and the total number of modules is M+1.

[0055] Step 120: Read the physical information of each pipeline and save it to each pipeline module; read the physical information of each node and save it to the node module.

[0056] Specifically, the pipeline module includes diameter, wall thickness, thermal conductivity, elevation, mileage, fluid state information of the multi-medium media within the pipeline, and information on adjacent connection nodes. The fluid state information within the pipeline includes the spatial media content, pressure, velocity, temperature, viscosity, and specific heat of each medium along the pipeline route. The node module includes information on the pipelines adjacent to the node and the fluid state information of the multi-medium media at the node. The physical information of the node mainly includes the physical information of the pipelines adjacent to the node. The fluid state information at the node includes the spatial media content, pressure, velocity, temperature, viscosity, and specific heat of each medium at the node, along with the fluid state information of the media in the pipelines adjacent to the node.

[0057] Step 130: Based on the flow state parameters and spatial distribution characteristics of the multi-medium in the pipeline module and node module, construct a dynamic conservation model of the transient flow field of the multi-medium in the pipeline network that considers the appearance or disappearance of the multi-medium.

[0058] Specifically, the dynamic conservation characteristic of the transient flow field is a dual-dimensional conservation characteristic encompassing both the time domain and the flow field. It not only accurately captures the mass, energy, and momentum conservation laws of the multi-component media in the pipeline system over time, tracking the evolution of parameters such as position, temperature, and pressure of the multi-component media over time, but also accurately describes the spatial distribution and flow characteristics of the multi-component media in complex pipeline topologies, ensuring that physical quantities such as mass flow rate and energy flux at each node and pipe segment in the flow field meet conservation conditions. Finally, this dynamic conservation characteristic can adaptively respond to the dynamic changes of the multi-component media. When different media appear or disappear, or when the flow state changes under complex conditions, it can adaptively adjust the parameters of the conservation equations, dynamically maintaining the overall conservation relationship of the system, thus achieving accurate modeling and analysis of the transient process of the multi-component media in the pipeline network. The dynamic conservation model of the transient flow field of the multi-component media in the pipeline network mainly includes:

[0059] Dynamic conservation model of transient flow field in a pipeline with multiple media:

[0060]

[0061] And i≠d,k∈(l,g,s,d)

[0062]

[0063] And i≠d,k∈(l,g,s,d)

[0064]

[0065] Dynamic conservation model of transient flow field in nodal multi-medium medium:

[0066]

[0067] And i≠d,k∈(l,g,s,d)

[0068]

[0069] in, The equations for the conservation of dynamic residuals of different multi-component media; For the momentum dynamic residual conservation equations of different multi-component media; f(res) T The equation represents the temperature dynamic residual conservation equation under the combined action of multiple media. The subscripts P and J represent the scope of the equation, and the sub-tables represent pipes and nodes. ρ is the density of the multiple media, in kg / m³. 3 ; ν is the spatial density of the multi-component medium; v is the velocity of the multi-component medium, in m / s; A is the area of ​​the control volume, in m². 2 t represents time in seconds (s); x represents the distance to the control volume in meters (m); Φ represents the interfacial mass transfer between different multi-component media in kg / m³. 3 P represents the spatial pressure of the multi-component medium, in Pa; g represents the acceleration due to gravity, in m / s². 2 θ is the tilt angle of the control volume, in degrees; F w F represents the frictional force between the multi-component medium and the wall surface, expressed in Pa / m. i F represents the interaction force between different multi-component media, with units of Pa / m. e The work done on the multi-component medium by external forces, excluding the medium itself, is expressed in Pa / m; T is the temperature of the multi-component medium, expressed in °C; C P Specific heat at constant pressure, in units of J / (kg·℃); subscript i represents the type of multi-component medium, such as CO2, methanol, oil and gas, etc.; subscript k represents the thermodynamic state of the multi-component medium, such as gas phase, liquid phase, dense phase, supercritical phase, etc.; subscript d represents the disappearing or appearing medium term; M represents the continuous term of disappearing medium transfer.

[0070] When one or more media appear / disappear or the flow state changes in a multi-media pipeline, the above equations update the dynamic conservation equations of the multi-media residuals. Furthermore, due to the immiscibility between media, the dynamic conservation equations of the flow residuals of the disappearing multi-media are retained, thereby achieving dynamic conservation.

[0071] Specifically, based on the dynamic conservation model of the transient flow field of multi-medium media in the pipeline network, the disappearance or appearance of multi-medium media is dynamically tracked. This also includes constructing the multi-medium flow matrix and decoupling the solution of the multi-medium pipeline network flow model, such as... Figure 3 As shown, step 200 specifically includes the following steps:

[0072] Step 210: Determine the time, space, and interface flux discretization schemes for the pipeline module and node module, and read the information of the multi-media pipeline module and node module.

[0073] Step 220: Construct multi-medium flow matrices for different modules based on the current multi-medium flow states of the pipeline module and node module.

[0074] Specifically, the construction of the multi-medium flow matrix is ​​based on a dynamic conservation model of the transient flow field of the multi-medium medium constructed from the current flow state of the multi-medium medium in the pipe or node, and the following relationships are established for the flow model:

[0075]

[0076] In the formula, Pre represents the flow of multiple media, the symbol / represents OR, and when the pipeline is divided into m segments, and each segment contains m media, the matrix size is 2n(m+1)-1. To find the vector; This represents the constant term solved in the previous time step; the subscript o indicates the pipe or node module to which it belongs, n is the number of segments, and m is the number of multi-element media.

[0077] If the appearance or disappearance of multiple media occurs, the multiple media flow matrix is ​​reconstructed based on the above equations. At this time, it is only necessary to rewrite the values ​​of the disappearing part of the multiple media flow matrix in the pipeline module and node module, without wasting resources to reconstruct the multiple media flow matrix of the pipeline module and node module, thereby speeding up the solution speed of the pipeline network.

[0078] Step 230: Use the PJFNK fully implicit algorithm combined with the multi-medium flow matrix to dynamically track the disappearance or appearance of multi-medium media and decouple the solution to solve the dynamic conservation model of the transient flow field of multi-medium media in the pipeline network.

[0079] Specifically, the solution processes for the pipe module and the node module are independent of each other and have no critical impact. Only the decoupling relationship at the nodes needs to be considered. Therefore, the solution process for each pipe module and node module can be solved separately using the PJFNK method to solve the dynamic conservation model of the multi-component transient flow field constructed by the pipe module and the node module. Figure 4 For the specific solution process of the dynamic conservation model of transient flow field of multi-medium pipeline network, step 230 may include the following steps:

[0080] Step 231: Based on the pipeline network structure, the pipeline is decomposed into separate calculation modules for each pipeline and for all nodes. Then proceed to step 232.

[0081] Step 232: Based on the initial &x obtained from the multi-medium flow matrix, update the multi-medium flow parameters in each pipeline module and node module, and determine whether the overall residual of the multi-medium pipeline network has converged. If it has converged, proceed to step 235; otherwise, proceed to step 233.

[0082] Step 233: Based on the updated multi-medium flow parameters of each pipeline module and node module, use PGMRES combined with the multi-medium flow matrix to solve the dynamic conservation model of the transient flow field of the multi-medium at the current moment for each pipeline module and node module, and determine whether the overall residual of the multi-medium pipeline network has converged. If it has converged, proceed to step 235; otherwise, proceed to step 234.

[0083] Specifically, PGMRES is a GMRES method based on the left pre-processing matrix theory. Unlike the original GMRES method, this method can make the residual equation converge quickly in a specified direction. The multi-medium flow matrix in the pipeline module and node module mentioned in this invention is a left pre-processing matrix.

[0084] Specifically, the PGMRES method approximates the matrix-vector product using differences as follows:

[0085]

[0086] Among them, Pre -1 The inverse of the multi-medium flow matrix, and J(x) k ) approximate; ε is the established difference step size, obtained based on computer precision.

[0087] In the above method, by To determine whether the PGMRES method has converged, after convergence... η is a constant between 0 and 1 to control the residual to always be in a decreasing direction, when ||b(x k+1 )||<||b(x k When ||, the process then proceeds to the outer loop step to determine whether the overall residual of the multi-medium pipeline network has converged.

[0088] Step 234: Based on the flow parameters of the pipeline module and node module in the time layer of the iterative step, dynamically track the disappearance or appearance of the multi-component medium, and dynamically update the dynamic conservation model of the transient flow field of the multi-component medium and reconstruct the multi-component medium flow matrix based on the current state of the multi-component medium, and then return to step 233.

[0089] Step 235: Determine whether the calculation time has reached the preset time. If not, update the multi-medium pipeline flow parameters, dynamically update the multi-medium transient flow field dynamic conservation model based on the current state of the multi-medium, and construct the multi-medium flow matrix. If the preset calculation time has been reached, proceed to step 236.

[0090] Step 236: Output the overall simulation results of the multi-media pipeline network.

[0091] Specific application examples are as follows:

[0092] To demonstrate the adaptability, stability, and extensibility of the algorithm of this invention, the following examples are used: (1) A simulation example of a supercritical / dense phase CO2 pipeline, demonstrating that the algorithm of this invention can simulate the multi-state (supercritical / dense phase) change process of CO2 medium flow. (2) A simulation example of a methanol-diesel multi-medium pipeline, demonstrating that the algorithm of this invention can simulate the interface tracking and dynamic change process of methanol-diesel multi-medium flow. (3) A simulation example of a deep-water oil and gas multi-component medium pipeline network, demonstrating that this invention can simulate the phase changes and interface mass transfer process in complex gas-liquid multi-phase pipeline network flow, showing that the algorithm of this invention is not only applicable to the flow prediction of new energy media (multi-state, multi-medium), but also has certain applicability to oil and gas media.

[0093] Example of simulation of supercritical / dense-phase CO2 pipeline: The operating and structural parameters of a supercritical / dense-phase impurity CO2 pipeline are shown in Table 1, where the flow composition is 96% CO2 and 4% N2. During the operation of the CO2 pipeline, due to changes in temperature and pressure, the phase state of CO2 will change between supercritical and dense phase, exhibiting multi-state operation, further increasing the simulation difficulty. However, the method provided by this invention can simulate and solve the above problems. Specific results are shown in [Table 1]. Figure 5 .

[0094] Table 1. Operational and Structural Parameters of CO2 Pipelines

[0095]

[0096] Specifically, Figure 5 The figure shows the changes in phase, flow rate, temperature, and pressure within a CO2 pipeline from its initial supercritical state to stable operation. The calculated pressure in the figure differs from the actual pressure by approximately 1 bar, while the calculated temperature is approximately the same as the actual temperature along the pipeline, with an error of 0.5°C. Figure 5As shown in 'a', a dense phase appeared inside the pipe during operation. The dense phase operating range gradually increased over time until it stabilized. This simulation effectively demonstrated the sudden appearance of a dense phase inside the pipe. This was due to changes in pressure and temperature causing impurities in CO2 to enter the dense phase region from the supercritical region. Throughout the process, it can be seen that there were no oscillations or non-convergence issues in the simulation results along the line. This demonstrates the stability and adaptability of the algorithm and model when multiple states occur during the flow process of impurities in CO2-containing media.

[0097] Simulation Example of a Methanol-Diesel Multi-Media Pipeline: The operation and structural parameters of a methanol-diesel pipeline are shown in Table 2. The flow process begins with diesel filling the pipeline initially, followed by methanol flowing into the pipeline, forming a methanol-diesel multi-media flow. After 2.4 hours, diesel flows into the pipeline, forming a diesel-methanol-diesel multi-media flow. During the operation of the methanol-diesel multi-media pipeline, a multi-media interface forms between diesel, methanol, and diesel, resulting in a multi-media operating state. This increases the difficulty of tracking the diesel-methanol-diesel interface and simulating its changes. However, the method provided by this invention can simulate and solve the above problems. Specific results are shown in [Table 2]. Figure 6 .

[0098] Table 2. Operational and Structural Parameters of Methanol-Diesel Pipelines

[0099]

[0100] Specifically, Figure 6 In the figure, 'ad' represents the changes in diesel content, pressure, diesel mass flow rate, and methanol mass flow rate along the methanol-diesel multi-media pipeline during transient operation. The calculated pressure result in the figure has an error of 2.2 bar compared to the actual result. Since methanol-diesel is a liquid flowing at room temperature, the temperature effect is negligible. Figure 6 As shown in 'a', the pipeline initially flows entirely with diesel, then methanol is injected, creating a methanol-diesel multi-medium flow. After 2.4 hours, diesel flows into the pipeline, forming a diesel-methanol-diesel multi-medium flow. Figure 6 As can be seen in (a)-(d), the model can effectively simulate and track the flow and flow rate changes at the diesel-methanol-diesel interface without any non-convergence or oscillations. This demonstrates the stability and adaptability of the algorithm and model when calculating multi-medium flow.

[0101] Example of simulation of deep-water oil and gas multi-component medium pipeline network: The structure of a certain deep-water oil and gas pipeline network is as follows Figure 7As shown in the diagram, Nodes 1, 2, 3, and 4 are deepwater oil and gas inlet nodes, which are transported to Nodes 5 and 6 via a ring network. The network operating parameters and the number of pipe structures are shown in Table 3. It is worth noting that after the deepwater oil and gas medium flows into the pipeline, mixing occurs at the nodes, leading to different pipes. Furthermore, due to the two rings in the network, there will be gas-liquid phase flow distribution, pressure balance, and temperature mixing at Junctions 1, 2, 3, 4, 5, and 6. Unlike natural gas pipelines, which only have gas phase flow distribution, deepwater oil and gas pipelines consider the flow distribution of both gas and liquid phases. The imbalance in gas-liquid phase flow distribution results in some pipes having high liquid phase flow and others having high gas phase flow. Additionally, the disappearance and reappearance of gas and liquid phases may occur within the pipeline, making the solution more difficult and computationally time-consuming compared to single-phase pipelines. However, the method provided by this invention can simulate and solve the above problems. Specific simulation results are shown in Table 3. Figure 8 , Figure 9 .

[0102] Table 3 Pipeline network operating parameters

[0103]

[0104] Specifically, Figure 8 In the figure, 'af' represents the temperature, pressure, gas phase mass flow rate, liquid phase mass flow rate, and total mass flow rate changes along the pipelines Pipe 1, Pipe 2, and Pipe 4 connected to Junction 1 when the pipeline network is calculated to be in steady state. The calculated pressure result in the figure has an error of 1.2 bar compared to the actual result, and the calculated temperature result is basically the same as the actual temperature along the pipeline, with an error of 0.3℃. Figure 8 As can be seen from the 'af' function, interphase mass transfer occurs in Pipe1, Pipe2, and Pipe4 during the flow in the pipeline. Therefore, the gas phase mass flow rate and liquid phase mass flow rate along the pipeline are not conserved, but the total mass flow rate along the pipeline is conserved. Furthermore, at the junction, the total mass flow rate out of Pipe1 is equal to the sum of the total mass flow rates of Pipe2 and Pipe4. This well demonstrates the conservation of the algorithm and equations, as well as the automaticity of flow distribution. When simulating complex ring network calculations, the model algorithm did not exhibit any non-convergence issues, and it does not require manual input of the inflow and outflow of the multiphase flow ring network. This well demonstrates the stability and adaptability of the model algorithm.

[0105] To better illustrate the model's ability to automatically identify the appearance or disappearance of phases, a transient simulation of the pipeline network was conducted. Initially, it was assumed that the pipeline network consisted entirely of gas. When deep-water oil and gas media flowed into the pipeline network from the inlet, the entire network transformed from a single-phase network into a two-phase gas-liquid flow network. Figure 9In the figure, 'af' represents the changes in phase content, pressure, and liquid mass flow rate along the pipelines Pipe1, Pipe2, and Pipe4 connected to Junction1 during transient calculations. As shown in the figure, initially, the pipelines are filled with gas, and the liquid mass flow rate is zero. As the deep-water oil and gas medium flows into the pipeline, the phase flow gradually transitions from a single phase to a two-phase flow of gas and liquid, and the liquid mass flow rate gradually increases. When it reaches Junction1 node, the proposed model algorithm achieves the distribution of phase content and liquid mass flow rate, and also simulates the appearance of phases well at the nodes. Throughout the process, it can be seen that there are no oscillations or non-convergence issues in the simulation results along the pipeline, which once again proves the stability and adaptability of the model algorithm.

[0106] The present invention also provides a computational device for decoupling transient flow with global conservation applicable to multi-medium pipeline transportation, including a pipeline information identification module, a multi-medium flow parameter prediction module, a multi-medium transient flow field dynamic conservation model construction module, and a fully implicit method solution module.

[0107] The pipeline information identification module is used to identify relevant pipeline and node information by combining the input pipeline information, thereby constructing pipeline and node modules.

[0108] The multi-medium flow parameter prediction module is used to calculate the flow parameters of each multi-medium medium in the pipeline module and node module, including the spatial medium content, pressure, velocity, temperature, viscosity, and specific heat information of each medium.

[0109] The module for constructing a dynamic conservation model of transient flow field in multiple media is used for dynamic updates of the dynamic conservation model of transient flow field in multiple media in the pipeline module and node module.

[0110] The fully implicit method solution module is used for fully implicit solutions of pipe and node modules, including the construction of the PGMRES method, the appearance or disappearance of multi-component media, and the implementation of the PJFNK method.

[0111] This invention also provides a computational device operation flow for decoupling transient flow with global conservation applicable to multi-medium pipeline transportation. The specific flow is as follows: (1) Identify the pipeline structure and construct pipeline and node modules based on the input pipeline information. (2) Update the flow parameters of the pipeline and node modules based on the multi-medium flow parameter prediction module using initial temperature and pressure. (4) Dynamically update the multi-medium transient flow field dynamic conservation model based on the multi-medium transient flow field dynamic conservation model construction module. (5) Decouple and solve the multi-medium flow parameters of the pipeline and node modules based on the multi-medium flow matrix construction and solution module, the multi-medium flow parameter prediction module, and the fully implicit method solution module, and update the multi-medium flow parameters of the pipeline and node modules.

[0112] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-medium pipeline transportation as described in any one of the above-described methods.

[0113] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-medium pipeline transportation as described above.

[0114] This invention is described based on flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to specific embodiments. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the flowcharts and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0115] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for decoupling transient flow with global conservation applicable to multi-medium pipeline transportation, characterized in that, include: Based on the flow state parameters and spatial distribution characteristics of multi-medium media in pipeline networks, a dynamic conservation model for transient flow fields of multi-medium media in pipeline networks, considering the presence or absence of multi-medium media, is constructed, specifically as follows: Read the overall structure of the pipeline network, form pipeline modules and node modules, and assign status parameters; Based on the flow state parameters and spatial distribution characteristics of the multi-medium media in the pipeline module and node module, a dynamic conservation model of the transient flow field of multi-medium media in the pipeline network is constructed, which considers the appearance or disappearance of multi-medium media. Based on the dynamic conservation model of transient flow field of multi-medium media in pipeline network, the disappearance or appearance of multi-medium media and changes in flow state are dynamically tracked. A dynamic conservation model of transient flow field of multi-medium media in pipeline network is constructed in real time based on the spatial distribution characteristics of multi-medium media in pipeline network, and the pipeline network model is decoupled and solved. Specifically, this is reflected in: By combining the time, space, and interface flux discretization schemes of pipeline and node modules with the current multi-medium flow state, a multi-medium flow matrix is ​​constructed under different modules; The PJFNK fully implicit algorithm is used in conjunction with the multi-medium flow matrix to dynamically track the disappearance or appearance of multi-medium media and decouple the solution to solve the dynamic conservation model of the transient multi-medium flow field in the pipeline network. Specifically, this is reflected in: Based on the pipeline network topology, the pipelines and nodes are separated into independent calculation modules. The PGMRES method is used in combination with the multi-medium flow matrix to solve the dynamic conservation model of the transient multi-medium flow field of the pipeline-node, and the flow parameters are updated through intra-time iteration. Based on the flow parameters of the pipeline module and node module within the time-layer iterative step, the disappearance or appearance of the multi-element medium is dynamically tracked. Based on the current state of the multi-element medium, the dynamic conservation model of the transient flow field of the multi-element medium is dynamically updated and the flow matrix of the multi-element medium is reconstructed until the entire pipeline network converges, and then the flow parameters of the next time step are updated.

2. The transient flow decoupling calculation method with global conservation applicable to multi-medium pipeline transportation according to claim 1, characterized in that, The dynamic conservation model for transient flow fields in pipeline networks using multiple media includes: Dynamic conservation model of transient flow field in a pipeline with multiple media: ； ； Dynamic conservation model of transient flow field in nodal multi-medium medium: ； ； in, The overall behavior exhibits conservation characteristics in both the time domain and the flow field. , , It exhibits dynamic conservation characteristics; res For the residual equation, the subscripts are... The equation's scope is represented by the pipe and the node, respectively. For the density of multi-component media; The spatial phase content of a multi-component medium; For multi-medium velocity; To control the volume area; For time; To control the distance between bodies; For mass transfer at the interface between different multi-component media; The spatial pressure of the multi-medium medium; It is the acceleration due to gravity; To control the tilt angle of the body; This refers to the frictional force between the multi-component medium and the wall surface. These are the interaction forces between different multi-component media; In addition to the work done on the multi-element medium itself by external forces; T Temperature of the multi-component medium; Specific heat at constant pressure; subscript Represents various media types, including Methanol and oil and gas, subscript Represents the thermodynamic state of a multi-component medium, subscript d For the disappearance or appearance of the medium item, M For continuous terms that are transmitted through a disappearing medium.

3. A transient flow decoupling calculation device for global conservation of multi-medium pipeline transportation, characterized in that, include: The pipeline information identification module is used to identify relevant pipeline and node information by combining the input pipeline information, thereby constructing pipeline and node modules, specifically as follows: Read the overall structure of the pipeline network, form pipeline modules and node modules, and assign status parameters; Based on the flow state parameters and spatial distribution characteristics of the multi-medium media in the pipeline module and node module, a dynamic conservation model of the transient flow field of multi-medium media in the pipeline network is constructed, which considers the appearance or disappearance of multi-medium media. The multi-medium flow parameter prediction module is used to calculate the multi-medium flow parameters in the pipeline module and node module, including the spatial medium content, pressure, velocity, temperature, viscosity, and specific heat information of each medium. The module for constructing a dynamic conservation model of transient flow fields in multi-medium media is used to dynamically update the dynamic conservation model of transient flow fields in multi-medium media in the pipe module and node module. Specifically, it is implemented as follows: By combining the time, space, and interface flux discretization schemes of pipeline and node modules with the current multi-medium flow state, a multi-medium flow matrix is ​​constructed under different modules; The PJFNK fully implicit algorithm is used in conjunction with the multi-medium flow matrix to dynamically track the disappearance or appearance of multi-medium media and decouple the solution to solve the dynamic conservation model of the transient multi-medium flow field in the pipeline network. Specifically, this is reflected in: Based on the pipeline network topology, the pipelines and nodes are separated into independent calculation modules. The PGMRES method is used in combination with the multi-medium flow matrix to solve the dynamic conservation model of the transient multi-medium flow field of the pipeline-node, and the flow parameters are updated through intra-time iteration. Based on the flow parameters of the pipeline module and node module within the time-layer iterative step, the disappearance or appearance of the multi-element medium is dynamically tracked. Based on the current state of the multi-element medium, the dynamic conservation model of the transient flow field of the multi-element medium is dynamically updated and the flow matrix of the multi-element medium is reconstructed until the entire pipeline network converges, and then the flow parameters of the next time step are updated. The fully implicit method solution module is used for fully implicit solutions of pipe and node modules, including the construction of the PGMRES method, the appearance or disappearance of multi-component media, and the implementation of the PJFNK method.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-media pipeline transportation as described in claim 1 or 2.

5. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes a computer program, it implements the steps of the transient flow decoupling calculation method for global conservation applicable to multi-medium pipeline transportation as described in claim 1 or 2.

Images