Fluid machine safety evaluation method based on interaction node state control solving

Abstract

The application discloses a kind of fluid machinery safety evaluation methods based on interactive node state control solution, it is related to fluid machinery safety evaluation technical field, first fluid machinery system is divided into subsystem, and determines interactive node;Preliminary give the state parameter of each interactive node and its evolution history with time, and solve the conservation equation residual of each interactive node, judge whether to meet accuracy requirement.If meet, then judge whether fluid machinery system meets preset safety requirement, otherwise determine state parameter correction amount by the method of interactive node state control, and then determine the state parameter of each interactive node and its evolution history in next round iteration, and repeat the above steps.The application converts the solution process of fluid machinery safety state into the control process of interactive node state between subsystem, can efficiently obtain the state parameter evolution history of fluid machinery system, and carries out safety evaluation, improves the evaluation efficiency of system safety performance.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fluid machinery safety evaluation, and more particularly to a fluid machinery safety evaluation method based on interactive node state control solving. BACKGROUND

[0002] Fluid machinery equipment is often used in engineering to realize energy exchange, conversion and utilization with fluid as working medium. Such mechanical equipment involves complex flow and heat exchange processes, which are generally modeled as fluid machinery systems in the design or analysis process. The system describes the dynamic process of each component of the mechanical equipment with components, and models the information exchange interface between each component with nodes. The evolution process of the state parameters at the nodes is the focus of attention in the safety evaluation of fluid machinery equipment. With the increasing refinement of analysis, such systems may involve hundreds or thousands of components. There are highly coupled dynamic conservation relationships between these components, which need to be solved simultaneously to obtain the matching working points of all components and then calculate the system state or performance. Due to the large number of components involved and the prominent coupling of conservation relationships, the process of obtaining the system state and performance is complex, thereby increasing the time cost of complex fluid machinery safety design and analysis, which is not conducive to research and development. For the safety state acquisition and evaluation method of fluid machinery systems, the existing technology mainly includes the following three kinds: (1) global coupling solving method; (2) fixed point iteration method based on interactive node state; (3) gradient correction method based on interactive node state.

[0003] At least the following problems exist in the prior art:

[0004] (1) Poor convergence. For the global coupling solving method, it directly uses the same solving step to solve all conservation equations in the system, but the time and space scales and inertias of each component are not the same, and direct solving may cause the coefficient matrix to be ill-conditioned during solving, resulting in poor convergence. For the fixed point method based on interactive node state, each subsystem needs to be solved sequentially, and in the process of sequentially assigning boundary conditions, the iteration error may be continuously amplified, thereby significantly affecting the convergence of the algorithm. For the gradient correction method based on interactive node state, it depends on gradient calculation, so it must be based on a calculation initial value close to the true value to converge, and not to diverge or converge to a local optimum.

[0005] (2) High requirement of computing resources. For the globally coupled solution method, the conservation equation sets of all components are solved simultaneously, and the dimension of the coefficient matrix is very high, which consumes a lot of computing resources. The strong coupling computing architecture is difficult to implement distributed parallel computing. For the fixed point method based on the interactive node state, each subsystem must be calculated sequentially, which is difficult to implement parallel computing. For the gradient correction method based on the interactive node state, since it depends on the gradient calculation, a small gradient calculation step must be used, so it also needs to consume high computing resources and the method is complex.

[0006] (3) Poor generalizability. For the globally coupled solution method, the control equation sets of all components must be solved using the same format, so it solves the union of all component control equation types. If a new component or a new control equation type is introduced, the coupled algorithm must be modified. For the fixed point method based on the interactive node state, the sequential calculation process is suitable for the case where the same interactive node is connected to only two components or subsystems. For the case where the same interactive node is connected to multiple components or subsystems, the parts exceeding the number must be merged, which has poor freedom.

[0007] Therefore, how to more quickly, efficiently and accurately obtain the state parameter evolution history of the fluid mechanical system and perform safety evaluation is a problem that needs to be solved by those skilled in the art. SUMMARY

[0008] Therefore, the present application provides a fluid mechanical safety evaluation method based on interactive node state control solution to solve the problems of complex state parameter acquisition method, poor universality, slow speed of the existing fluid mechanical system, and thus unable to quickly, efficiently and accurately evaluate the safety of the fluid mechanical system.

[0009] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0010] A fluid mechanical safety evaluation method based on interactive node state control solution, comprising the following steps:

[0011] Step 1, dividing the fluid mechanical system into several subsystems and determining the interactive nodes between the subsystems;

[0012] Step 2, initially giving the state parameters of each interactive node and their evolution history over time as the initial value of iteration;

[0013] Step 3, solving the conservation equation residual of each interactive node based on the state parameters of each interactive node and their evolution history over time;

[0014] Step 4, judging whether the conservation equation residual of each interactive node meets the accuracy requirement, if yes, entering step 6, otherwise entering step 5;

[0015] Step 5, based on the conservation equation residual, determine the state parameter correction amount by the method of interactive node state control, and further determine the state parameter of each interactive node in the next round of iteration and its evolution history over time, and return to step 3;

[0016] Step 6, according to the state parameter and its evolution history over time in the current iteration process, judge whether the fluid mechanical system meets the preset safety requirements.

[0017] Optionally, in the step 3, the method for solving the conservation equation residual of each interactive node is:

[0018] Step 3.1, based on the dynamic conservation equation, solve the response flow function of each subsystem under the excitation of the state parameter;

[0019] Step 3.2, based on the response flow function of each subsystem, solve the conservation equation residual of each interactive node.

[0020] Optionally, in the step 3.1, the dynamic conservation equation of the first j interactive node is:

[0021]

[0022] Wherein, is the state parameter vector of the interactive node j , is the dynamic inertia vector of the interactive node , is the physical time, j is the response flow function vector of the first subsystem under the excitation of the state parameter . i Based on the dynamic conservation equation of the first interactive node, solve the response flow function of the first

[0023] subsystem under the excitation of the state parameter j of the interactive node j . i

[0024] Optionally, in the step 3.2, based on the response flow function of each subsystem, the conservation equation residual of the first j interactive node at time is:

[0025]

[0026] Wherein, is the conservation equation residual vector of the interactive node j ,​​​ is an interaction node j is a state parameter vector of the interaction node at the last time step, is an interaction node j is a state parameter of the interaction node at the current time step, is a physical time, is the last time step, is an interaction node j is a response flow function vector of the i-th subsystem connected to the interaction node i under the excitation, is the number of subsystems connected to the interaction node n j

[0027] Optionally, in the step 5, the state parameter correction amount of the i-th interaction node is determined based on the conservation equation residual as follows: j

[0028]

[0029] wherein, is a state parameter correction amount of the i-th interaction node at the j-th iteration, j is a physical time, k is an iteration number, is a state parameter of the i-th interaction node at the j-th iteration, k j is a conservation equation residual of the i-th interaction node at the j-th iteration, k are proportional, integral and differential constants respectively; when , the proportional term or the proportional-differential term is counted only because the differential term cannot be calculated.

[0030] Optionally, in the step 5, the state parameter of each interaction node in the next round of iteration is as follows:

[0031]

[0032] wherein, is a state parameter correction amount of the i-th interaction node at the j-th iteration, j is a state parameter of the i-th interaction node at the j-th iteration, k is a state parameter of the i-th interaction node at the j-th iteration, is a positive integer set. j k j

[0033] ​​​​​​​​​​​​Via the technical solutions, the application provides a fluid mechanical safety evaluation method based on an interactive node state control solution, which has the following beneficial effects compared with the prior art:

[0034] (1) Good numerical convergence. The method provided by the application is not dependent on gradient calculation, but directly drives parameter correction with the goal of zero conservation equation residual, which is conducive to avoiding the situation of solution divergence or converging to a local optimal solution due to gradient disappearance. At the same time, it has been verified that the method based on proportional-integral-derivative control is conducive to reducing the sensitivity of the initial value, that is, it can converge in a larger initial value range.

[0035] (2) High state parameter acquisition efficiency. The process of solving the response of each component or subsystem under the excitation of the interactive node state parameter can be executed in parallel. At the same time, due to the differences in time and space scales of each component or subsystem, these parallel solving processes can use different solving steps and different computing resources to execute on multiple computers. In fact, the algorithm provided by the application only needs to exchange information after the solving of all components or subsystems is completed, so it can improve the solving efficiency and realize efficient parallel computing.

[0036] (3) Strong generalization. As long as the control equation of the analysis target meets the dynamic conservation form provided by the application, the state parameter solving and safety evaluation can be performed according to the method provided by the application. The application object of the method includes but is not limited to fluid mechanical equipment such as an aero-engine, and can also be used for a power station water cooling pipe network system, etc. In addition, the method provided by the application is not only suitable for mechanical networks involving simple flow and heat exchange. For systems involving complex physical fields such as magnetic fluids, as long as their dynamic control equations meet the form described in the application, they can be processed according to the method provided by the application. At the same time, the method is also suitable for solving complex mechanical network systems with multiple dimensions (for example, a part of the subsystem is described by a low-dimensional lumped parameter, while another part of the subsystem is described by a high-dimensional method with high space-time resolution), multiple physical fields (for example, a part of the subsystem involves fluid domain, while another part of the subsystem involves solid domain), and multiple solving domains (for example, a part of the subsystem involves simulation software domain, while another part of the subsystem involves test hardware domain).

[0037] In summary, the method of the application can more quickly, efficiently and accurately obtain the state parameter evolution history of the fluid mechanical system and perform safety evaluation, thereby improving the evaluation efficiency of the safety performance of the fluid mechanical system. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0039] Figure 1 Schematic diagram of a complex fluid mechanical system applicable to the method of the present application

[0040] Figure 2 Schematic diagram of the flow of the method of the present application

[0041] Figure 3 Schematic diagram of the control principle logic of the method of the present application

[0042] Fig. 4(a) is a schematic diagram of the topology of the convection heat exchange system in the specific embodiment of the present application

[0043] Fig. 4(b) is a schematic diagram of the subsystem division of the convection heat exchange system in the specific embodiment of the present application

[0044] Figure 5 Fig. 5 is a comparison diagram of the convergence process and the calculation error of the convection heat exchange system in the specific embodiment of the present application

[0045] Figure 6 Fig. 6 is a comparison diagram of the convergence speed of the convection heat exchange system in the specific embodiment of the present application when different control parameters are used DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0047] The embodiment of the present application discloses a fluid mechanical safety evaluation method based on interactive node state control solving, referring to Figure 2 , comprising the following steps:

[0048] Step 1, divide the fluid mechanical system into several subsystems, and determine the interactive nodes between the subsystems.

[0049] In order to realize the efficient calculation of the complex fluid mechanical system, it is first needed to be divided into multiple subsystems, referring to Figure 1The partitioning should be based on ensuring that the complexity or computation time of each subsystem is roughly equivalent. Therefore, the type of governing equations, spatiotemporal scale, system inertia, and number of components of each subsystem should be comprehensively considered. Simultaneously, the coupling between subsystems should also be considered, and partitioning should occur at locations with weaker coupling. During partitioning, nodes on the boundaries of each subsystem naturally become interaction nodes between subsystems, and subsequent parameter corrections or solution processes are performed at these interaction nodes.

[0050] Step 2: Initially define the state parameters of each interaction node and their evolution over time as the initial values ​​for iteration.

[0051] This invention requires obtaining the evolution history of state parameters at the interaction nodes between subsystems so that the residuals of the dynamic conservation equations remain zero. Therefore, the first step is to specify the evolution of node state parameters over time at each interaction node of the subsystem, serving as the initial values ​​for iterative calculations. The initial state parameters are given based on changes in the system's boundary conditions. The closer the given initial state parameters are to the actual physical conditions, the fewer iterations are required later. When the fluid machinery system is too complex and the parameter evolution is difficult to predict, the initial state of the system can be referenced, using constants as the initial values ​​for iterations throughout the entire time history. Since the method proposed in this invention does not rely on gradient calculations and has low sensitivity to initial values, it also exhibits good convergence. This process typically involves multiple interaction nodes, requiring only the provision of initial values ​​for each node.

[0052] For example, for the first j There are 10 interactive nodes, assuming there are a total of 1000 nodes. n If a subsystem is connected to it, then at this interaction node, its dynamic conservation equation can be written as:

[0053]

[0054] in, For interactive nodes j The state parameter vector, For interactive nodes j The dynamic inertia vector, For physical time, For the first i The subsystem in state parameters The response stream function vector under excitation. It should be noted that, except for time, all physical quantities involved in the above equations are vectors. Therefore, the above set of equations actually considers the dynamic conservation relationships such as mass, momentum, angular momentum, and energy that may be involved in a fluid-thermomechanical network system in a unified form.

[0055] Step 3, solve the response flow function of each subsystem under the excitation of the state parameters and their evolution history, and solve the conservation equation residual of each interaction node based on the response flow function of each subsystem.

[0056] solving the response flow function of each subsystem under the excitation of the evolution history of state parameters For example, the flow rate of the return node of the fluid mechanical subnetwork under the excitation of the pressure boundary, or the enthalpy flow or heat flow of the return node under the excitation of the temperature boundary, or the power flow of the return node under the excitation of the rotational speed boundary, etc.

[0057] The response flow function is related to the type and structure of the subsystem. For a general subsystem, the response is generally nonlinear. Only when the subnetwork system structure is simple, its response flow function can be expressed by an analytical relationship. For example, there is only one flow resistance element in a certain subnetwork, then the flow response of the subnetwork under the excitation of the total pressure, total temperature and static pressure boundaries at its inlet can be solved by the following formula:

[0058]

[0059]

[0060] wherein, are the total pressure, total temperature and static pressure boundaries at the inlet of the flow resistance, is the flow response of the subnetwork; is a gas dynamics function, K is a constant related to the physical properties of the fluid, A is the flow area of the flow resistance.

[0061] The number of response flow functions is consistent with the number of state parameters. The solving process of each subsystem can be performed in parallel, or can be flexibly deployed on multiple servers. In each iteration, only the evolution history of the state parameters of the interaction node related to the subsystem and the response flow function returned to the node need to be transmitted between servers. Considering that each subsystem may involve different time and space scales or resolutions, different subsystems can use different solving time steps. When the time and space scale of the calculation is more refined than that of the boundary condition, interpolation or other methods can be used for preprocessing. In this process, the same subsystem may involve multiple interaction nodes as the boundary conditions for solving.

[0062] After obtaining the response flow function of each subsystem, the conservation equation residual of the i-th interaction node at time t is solved according to the following formula: j

[0063] ​​​

[0064] in, For interactive nodes j The residual vector of the conservation equation, For interactive nodes j The state parameter vector from the previous time step can be considered a constant in the current time step. For interactive nodes j The state parameters at the current time step For physical time, For the previous time step, For interactive nodes j The connected first i Subsystems in The response stream function vector under excitation, n For interaction with nodes j The number of connected subsystems. When the solution times of different subsystems are not the same, the response of other subsystems should be interpolated first by referring to the subsystem with the highest resolution, and then the residuals should be calculated.

[0065] Step 4: Determine whether the residuals of the conservation equations of each interaction node meet the accuracy requirements. If they do, proceed to step 6; otherwise, proceed to step 5.

[0066] Throughout the entire time process, when the residuals of all conservation equations at all interaction nodes meet the accuracy requirements, the iterative calculation can be terminated, and the process can proceed to step 6, outputting the corresponding state parameters and the state of each subsystem under the excitation. If the residuals in any time step do not meet the accuracy requirements, step 5 is executed.

[0067] Step 5: Based on the residual of the conservation equation, determine the state parameter correction amount through the interaction node state control method, and then determine the state parameters of each interaction node in the next iteration and their evolution over time, and return to step 3;

[0068] The above steps demonstrate that solving the fluid mechanical system's... j The process of maintaining the dynamic conservation equations at each node is actually the process at each moment. Above, seek its state parameters This makes the residual of the dynamic conservation equation at that node... The value is zero. Therefore, at each time step, the node can be set to zero. State parameters at Analogous to the actuation or control handle in a control system, the residual of the corresponding conservation equation. Analogous to a sensed quantity or control objective, and drawing upon algorithms such as proportional-derivative-integral (PDI) control in the control field, the numerical values ​​of the node state parameters are adjusted based on residuals. Therefore, at each interaction node, a PDI controller is assigned to each solution time step, such as... Figure 3 As shown. Based on the residuals of the conservation equation, the first... j The state parameter correction amount for each interactive node is:

[0069]

[0070] in, For interactive nodes based on proportional-derivative-integral control j First k The state parameter correction amount for the next iteration. For physical time, k For the number of iterations, For interactive nodes j In the k The residuals of the conservation equation in the next iteration These are the proportional, integral, and differential constants, respectively; when Since the differential term cannot be calculated, only the proportional term or the proportional-differential term can be included.

[0071] The state parameters of each interaction node in the next iteration are:

[0072]

[0073] in, For interactive nodes j First k The state parameter correction amount for the next iteration. For interactive nodes j First k The state parameters for the next iteration. For interactive nodes j First The state parameters for the next iteration. It is a set of positive integers.

[0074] Based on this, a more accurate evolution history of the state parameters of the interaction nodes can be obtained, which can then be used as the initial values ​​for the next iteration. This process is repeated until the residuals of all interaction nodes, all time steps, and all conservation equations meet the accuracy requirements. According to control theory, as the number of iterations increases... As the interaction nodes accumulate, the state parameters gradually converge to reasonable values, causing the residuals of the dynamic conservation equations to approach zero. By iteratively correcting each interaction node at each time step using the aforementioned method, the state and evolution of the fluid mechanical system can be obtained.

[0075] Step 6: Output the corresponding state parameters that meet the accuracy requirements and their evolution over time, as well as the state of each subsystem under its excitation. Based on the state parameters of the current iteration process and their evolution over time, determine whether the fluid machinery system meets the preset safety requirements.

[0076] The calculated parameter evolution process contains characteristics such as extreme values ​​and rates of change. This can be used for safety assessment of fluid machinery. During the design process of fluid machinery, the method proposed in this invention can be used to assess whether parameter characteristics are within acceptable ranges, thereby evaluating whether the equipment's safety meets safety requirements. During equipment operation, the method proposed in this invention can also be used to monitor equipment safety in real time. When certain parameter characteristics are detected to exceed permissible limits, the equipment will implement safety measures such as shutdown or parameter reduction operation to ensure equipment safety.

[0077] The method of the present invention is illustrated in detail below with examples. However, the present invention can also be applied to other embodiments that are different from this one. Therefore, the scope of protection of the present invention is not limited to the following examples.

[0078] Convection heat transfer systems are common fluid mechanical systems in engineering, and their topology is shown in Figure 4(a). The dashed box in the figure represents the fluid domain, which includes the inflow boundary, heat transfer resistance, back pressure boundary, and two internal fluid nodes; the solid box represents the solid domain, which includes the thermal resistance and six internal heat transfer nodes.

[0079] At fluid nodes, the conservation of gas mass, angular momentum, energy, and composition (oil-to-gas ratio and water-to-gas ratio) is achieved, i.e.:

[0080]

[0081]

[0082]

[0083]

[0084]

[0085] in, These are the state parameters at the nodes, including fluid density, swirling velocity, temperature, oil-gas ratio, and water-gas ratio. These are the inertial parameters at the node, including volume, radius, and specific heat capacity. The first under state excitation i Each subsystem returns the quality flow rate of its nodes; For time.

[0086] The heat flux conservation is realized at the heat exchange node, i.e.

[0087]

[0088] wherein, are the state parameters of the solid density and temperature at the node, respectively; are the inertia parameters of the volume and specific heat capacity at the node, respectively; is the heat flux returned to the node by the i th subsystem under the state excitation; is the time.

[0089] The coupling effect of the system is realized through the heat exchange resistance, and the control equation is:

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098] wherein, the subscripts in and out represent the inlet and outlet positions of the heat exchange resistance, respectively. is the mass flow rate; is the rotational flow rate, r is the radius position; T is the fluid temperature, is the fluid specific heat capacity, Q is the heat exchange amount of the fluid and the solid; is the oil-gas ratio, is the water-gas ratio; is the convective heat transfer coefficient, A is the heat exchange area, is the wall temperature; is the Nusselt criterion number of heat exchange, l is the characteristic scale of heat exchange, is the fluid thermal conductivity, Re is the Reynolds criterion number of the fluid, Pr is the Prandtl criterion number of the fluid.

[0099] For the thermal resistance of the solid domain, the control equation is:

[0100]

[0101] where, Q is the solid heat conduction, is the solid thermal conductivity, A is the heat exchange area, is the thickness, is the temperature difference before and after the thermal resistance.

[0102] The system is initially stable. The temperature at the inflow boundary is increased by 33% in 10 seconds according to the slope rule. Therefore, the system is divided into two subsystems according to the fluid domain and the solid domain, as shown in Figure 4 (b), and the wall surface temperature evolution of the heat exchange flow resistance is transmitted between the two subsystems through the interaction node, and the heat flow evolution of the fluid flowing through the heat exchange flow resistance and the solid heated by the fluid is returned to the node under the excitation of the temperature.

[0103] The change of the conservation equation residual of the interaction node with the number of iterations is shown in Figure 5 It can be seen from Figure 5 that the method proposed in the application has good convergence. At the same time, as the iteration residual tends to zero, the maximum error of the method proposed in the application relative to the traditional method in the whole time history also tends to zero. This shows that the method proposed in the application can effectively converge to the true value.

[0104] The influence of different control parameters on the convergence is shown in Figure 6 It can be seen that the maximum overshoot and the number of iterations of the algorithm can be adjusted by setting different control parameters, which is consistent with the conclusion in the classical control theory. This confirms the rationality of borrowing from the control theory in the solution process of the fluid machinery system.

[0105] Another embodiment of the application also discloses a fluid machinery safety evaluation system based on the state control solution of the interaction node, comprising:

[0106] An interaction node determination module is used to divide the fluid machinery system into a plurality of subsystems and determine the interaction nodes between the subsystems;

[0107] An initial state parameter determination module is used to initially give the state parameters of each interaction node and the evolution thereof with time as the initial value of iteration;

[0108] A conservation equation residual determination module is used to solve the conservation equation residual of each interaction node based on the state parameters of each interaction node and the evolution thereof with time;

[0109] The precision judgment module is configured to judge whether the conservation equation residual of each interaction node meets the precision requirement, and if yes, the safety judgment module is entered, otherwise, the state parameter correction module is entered.

[0110] The state parameter correction module is configured to determine a state parameter correction amount based on the conservation equation residual by a method of interaction node state control, and then determine the state parameter of each interaction node in the next round of iteration and the evolution history of the state parameter over time, and return to the conservation equation residual determination module.

[0111] The safety evaluation module is configured to judge whether the fluid mechanical system meets the preset safety requirement according to the state parameter of the current iteration process and the evolution history of the state parameter over time.

[0112] For the system modules disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0113] The embodiments in the specification are described in a progressive manner, and each embodiment mainly explains the difference from other embodiments. The same and similar parts between the embodiments can be referred to each other.

[0114] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for safety assessment of a fluid machine based on interaction node state control solving, characterized in that, The method comprises the following steps: Step 1, dividing the fluid mechanical system into several subsystems and determining the interaction nodes between the subsystems; Step 2, initially giving the state parameters of each interaction node and the evolution history thereof with time as initial values of iteration; Step 3, solving the conservation equation residual of each interaction node based on the state parameters of each interaction node and the evolution history thereof with time; The fluid mechanical system is a convection heat exchange system; The interaction nodes include an inflow boundary and a heat exchange flow resistance, a fluid internal node between the heat exchange flow resistance and a back pressure boundary, and a heat exchange internal node; the node parameters include fluid density, rotational flow velocity, temperature, oil-gas ratio, water-gas ratio at the fluid internal node, and solid density and temperature at the heat exchange internal node; In the step 3, the method for solving the conservation equation residual of each interaction node is as follows: Step 3.1, solving the response flow function of each subsystem under the excitation of the state parameters based on the dynamic conservation equation; Step 3.2, solving the conservation equation residual of each interaction node based on the response flow function of each subsystem; In step 3.1, the dynamic conservation equation of the first j interaction node is: ； wherein, is a state parameter vector of the interaction node j , is a dynamics inertia vector of the interaction node j , is a physical time, is a response flow function vector of the i th subsystem under the excitation of the state parameter . solving a response flow function of the first subsystem under excitation of state parameters of the first interaction node based on a dynamic conservation equation of the first interaction node j j i ​​​​​ In step 3.2, the first j conservation equation residual of the individual interaction nodes at time is solved based on the response flow functions of the individual subsystems. ； wherein, is a conservation equation residual vector for the interaction node j , is a conservation equation residual vector for the interaction node j , is a state parameter vector at the previous time step for the interaction node j , is a state parameter at the current time step for the interaction node , is a physical time, j is a previous time step, i is a response flow function vector for the i-th subsystem connected to the interaction node under the excitation, n is a number of subsystems connected to the interaction node j . Step 4, judging whether the conservation equation residual of each interaction node meets the accuracy requirement, if yes, entering step 6, otherwise entering step 5; Step 5, determining the state parameter correction amount through the method of interaction node state control based on the conservation equation residual, and then determining the state parameters of each interaction node and the evolution history thereof with time in the next round of iteration, and returning to step 3; Step 6, judging whether the fluid mechanical system meets the preset safety requirement according to the state parameters and the evolution history thereof with time in the current iteration process.

2. The method according to claim 1, wherein, In the step 5, the state parameters of each interaction node in the next round of iteration are as follows: ； wherein, is an interaction node j at the first iteration of the state parameter correction, k is an interaction node at the first iteration of the state parameter, j is an interaction node k at the first iteration of the state parameter, is an interaction node j at the first iteration of the state parameter, is an interaction node is a set of positive integers.

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